On 2013 Dec 22, William Brieger commented:

Since this study was conducted, WHO's Global Malaria Program has updated its recommendations about intermittent preventive treatment in pregnancy (IPTp). The guideline and briefing paper can be found at http://www.who.int/malaria/areas/high_risk_groups/pregnancy/en/index.html - in short IPTp is now recommended for every antenatal care visit after quickening (doses one month apart), meaning up to 4 doses if countries are practicing focused antenatal care.

On 2015 Sep 30, Jan Egger commented:

This article is related to: http://www.springerplus.com/content/3/1/167

Best wishes, Jan

On 2014 Nov 25, Harri Hemila commented:

The paper has been commented on at the PLOS ONE pages, see: http://www.plosone.org/annotation/listThread.action?root=73909; which is also available as an A4 layout: http://hdl.handle.net/10138/42535.

On 2014 May 26, Ivan Oransky commented:

This paper has been retracted: http://retractionwatch.com/2014/05/26/forged-authorship-sinks-melanoma-paper/

On 2014 Jan 01, Qian Liu commented:

This is an official government file for Chinese thoracic surgeons.

On 2015 Nov 13, University of Kansas School of Nursing Journal Club commented:

Reviewers: (Team 10) Lucy Bush, Sydney Jordan, Elijah Penny, Alex Noller, Parwana Noori, Cassidy Playter, Brittany Winter (Senior Nursing Students – Class of 2016)

Background:

This article was chosen based on how it directly correlates with the transformational leadership section we recently covered in lecture. This study explores how transformational leadership effects nursing innovation and the role of an organizational climate. This article bridges the gap in knowledge present between transformational leadership of management and the behavior of employees subjected to this leadership style. As discussed by Marquis and Huston (2015), transformational leadership by definition is designed to encourage nurses to be innovative, compassionate, and caring; however, this definition does not cover what kinds of innovative behaviors nurses under transformational management exhibit. The purpose of us analyzing this article was to discover what specific behaviors that could be evoked by the consistent support of a manager with a transformational leadership style. The authors of the article conducted the study in three regional hospitals in Taiwan that yielded a different cultural perspective of nursing and leadership, (Weng, Huang, Chen, & Chang, 2013, p. 427). Much effort and resources are focused on nurses’ performance in the clinical setting, and transformational leadership has its proper place in the drive to improve nursing innovation.

Methods:

The databases used to retrieve this article were The Biosemantics Group, CINAHL, and PubMed. The article we choose was originally not found when using the following Boolean search: “transformational leadership” AND “nursing.” Even though the subject heading being searched was adjusted from title to abstract, CINAHL revealed no articles of interest. When PubMed was searched for: “the impact of transformational leadership,” the article we decided upon was found. The study employed a cross-sectional research design that used personal reporting from nursing professionals. Data was collected using a questionnaire survey consisting of a 5-point Likert scale sent out to 150 selected nurses from three separate Taiwan hospitals (Weng et al., 2013, p. 431). The questionnaires were sent out anonymously to nurses in the selected hospitals. A total of 450 questionnaires were sent out from 11 April to 15 May 2011 and the research team obtained a total of 439 questionnaires with viable data (Weng et al., 2013, p. 431). The target population of nurses was selected primarily based upon their age, educational background, role in the clinical ladder, marital status, department of employment, and hospital experience in order to eliminate extraneous factors that could have affected the implication of the results on nursing practice (Weng et al., 2013, p. 431). The study also recognized that inspirational motivation, idealized influence, and a patient safety climate could also positively influence the innovation of staff nurses in Taiwan hospitals. After removing all potentially compromising variables, the research team analyzed the impact of transformational leadership on nurse innovation.

Findings:

The key findings of this study showed that their initial hypothesis one was correct: transformational leadership has a significantly positive influence on nurse innovation behavior. The questionnaires would go on to reveal that nurse managers can indirectly, positively influence nurse innovative behaviors through the establishment of a culture of patient safety and innovation (Weng et al., 2013). In other words, organizational climate directed by transformational leadership could impacts innovative behavior. A large limitation is that the study was only carried out in three Taiwanese hospitals; therefore, it would be hard to say that the results are externally valid or applicable to all nursing care across the world. Further research will need to be carried out in U.S. hospital settings to determine if the effects seen in Taiwanese hospitals were not influenced by other factors such as geography, culture or traditions not evident in the U.S. care settings. Another difference noted in this study was the time frame of data collection. The questionnaires were only sent out for a little over a month-long period in 2011; therefore, the data collected only represents a time-limited analysis of the effects of transformational leadership on nurse innovative behaviors. In the future, it would be recommended that the study be carried out over a considerably longer time frame to ensure data collection evidenced sustained nursing innovative behaviors. On a macro-system level, this problem impacts nearly all nursing units across the world because nursing innovations in patient care could be applicable to all scenarios in which nursing care is needed. From a microsystem perspective, nurse managers interested in boosting creativity and innovation among their unit staff should understand the indirect influence transformation leadership and organizational climate can have on nursing innovative behaviors. The importance of innovation is highly applicable to all hospital development and especially nursing care development, as nurses are deeply involved in direct patient care and the practice of healthcare.

Implications:

The study reports the significance of transformational leadership. This implies that hospitals should develop and encourage transformational leadership approach by designing and implementing leadership training programs aimed at developing cultures of patient safety and innovation. On the microsystems level, the findings of this study demonstrate that nurse managers can foster innovation by involving nurses in team projects to develop and implement creative ideas. Throughout the implementation and evaluation phases of nurse innovative projects, nurse manager should recognize success and encourage behaviors attributed to the success in an effort to sustain such innovation. Weng (2013) also stated the importance of establishing a culture of patient safety through development of a patient safety problem-reporting network. Not only does patient safety reporting make nurse managers aware of threats to patient safety, but it also supports development of innovations through staff involvement. This literature is important to our group because it allows us to explore what transformational leadership can look like at the microsystems level. Only through continual reflection on our own practices, can we accomplish changes in our leadership behaviors in the clinical setting. This article models the important affects that we as future nurse leaders can have on the safety of the patients we are caring for. Personal empowerment exercises like the discovery of these cultures of innovation have proved to be inspirational to us throughout our learning process.

References

Weng, R. H., Huang, C. Y., Chen, L. M., & Chang, L. Y. (2013). Exploring the impact of transformational leadership on nurse innovation behavior: a cross‐sectional study. Journal of nursing management. 23,4. doi:10.1111/jonm.12149

Marquis, B., & Huston, C. (2015). Leadership Roles and Management functions in Nursing: Theory and Application. (8th ed). Wolster & Kluwer. Philadelphia. Chapter 3: Twenty-First Century Thinking about Leadership and Management, pp. 60-61.

On 2014 Mar 09, Gyanshankar Mishra commented:

This is an excellent study on pulmonary function tests in diabetes with/without COPD.

We had done a similar study on pulmonary function tests in Diabetics with obstructive airway diseases like Asthma or COPD. Available online at http://www.applied-cardiopulmonary-pathophysiology.com/05_mishra.html

In fact our prior study was on Pulmonary functions in Diabetes. http://www.ncbi.nlm.nih.gov/pubmed/21302598

On 2014 Mar 02, Andrea Messori commented:

The systematic review by Adam and co-workers [1] is probably the most comprehensive analysis currently available on the comparative effectiveness of new oral anticoagulants for thromboprophylaxis in patients subjected to orthopaedic surgery. One problem for readers who are interested in this issue is that PubMed now includes at least 20 meta-analyses or systematic reviews focused on this issue [1-20]. This confirms that a problem exists with multiple overlapping meta-analyses that study the same randomized trials published on the same topic[21-22]. However, there seems to be no straightforward solution to this problem.

Andrea Messori HTA Unit, Regional Health Service 50100 Firenze ITALY

References

1: Adam SS, McDuffie JR, Lachiewicz PF, Ortel TL, Williams JW Jr. Comparative effectiveness of new oral anticoagulants and standard thromboprophylaxis in patients having total hip or knee replacement: a systematic review. Ann Intern Med. 2013 Aug 20;159(4):275-84. doi: 10.7326/0003-4819-159-4-201308200-00008.Review. PubMed PMID: 24026260.

2: New Oral Anticoagulants for the Prevention of Thromboembolic Events in Patients with Atrial Fibrillation [Internet]. Ottawa (ON): Canadian Agency forDrugs and Technologies in Health; 2012. Available from http://www.ncbi.nlm.nih.gov/books/NBK169793/ PubMed PMID: 24279001.

3: Hull RD, Liang J, Bergqvist D, Yusen RD. Benefit-to-harm ratio of thromboprophylaxis for patients undergoing major orthopaedic surgery. A systematic review. Thromb Haemost. 2014 Jan 29;111(2):199-212. doi: 10.1160/TH13-08-0654. Epub 2013 Oct 24. PubMed PMID: 24154501.

4: Castellucci LA, Cameron C, Le Gal G, Rodger MA, Coyle D, Wells PS, Clifford T, Gandara E, Wells G, Carrier M. Efficacy and safety outcomes of oral anticoagulants and antiplatelet drugs in the secondary prevention of venous thromboembolism: systematic review and network meta-analysis. BMJ. 2013 Aug 30;347:f5133. doi: 10.1136/bmj.f5133. Review. PubMed PMID: 23996149; PubMed Central PMCID: PMC3758108.

5: Hamidi V, Ringerike T, Hagen G, Reikvam Å, Klemp M. New anticoagulants as thromboprophylaxis after total hip or knee replacement. Int J Technol Assess Health Care. 2013 Jul;29(3):234-43. doi: 10.1017/S0266462313000251. Epub 2013 Jun 17. PubMed PMID: 23768996.

6: Mahmoudi M, Sobieraj DM. The cost-effectiveness of oral direct factor Xa inhibitors compared with low-molecular-weight heparin for the prevention of venous thromboembolism prophylaxis in total hip or knee replacement surgery. Pharmacotherapy. 2013 Dec;33(12):1333-40. doi: 10.1002/phar.1269. Epub 2013 Apr 26. PubMed PMID: 23625693.

7: Pebanco GD, Kaiser SA, Haines ST. New pharmacologic methods to prevent venous thromboembolism in older adults: a meta-analysis. Ann Pharmacother. 2013 May;47(5):605-16. doi: 10.1345/aph.1R247. Epub 2013 Apr 19. PubMed PMID:23606553.

8: Kwok CS, Pradhan S, Yeong JK, Loke YK. Relative effects of two different enoxaparin regimens as comparators against newer oral anticoagulants: meta-analysis and adjusted indirect comparison. Chest. 2013 Aug;144(2):593-600. doi: 10.1378/chest.12-2634. PubMed PMID: 23519234.

9: Yoshida Rde A, Yoshida WB, Maffei FH, El Dib R, Nunes R, Rollo HA. Systematic review of randomized controlled trials of new anticoagulants for venous thromboembolism prophylaxis in major orthopedic surgeries, compared with enoxaparin. Ann Vasc Surg. 2013 Apr;27(3):355-69. doi:10.1016/j.avsg.2012.06.010. Epub 2013 Jan 23. Review. PubMed PMID: 23351997.

10: Hellwig T, Gulseth M. New oral therapies for the prevention and treatment of venous thromboembolism. Am J Health Syst Pharm. 2013 Jan 15;70(2):113-25. doi:10.2146/ajhp110601. Review. PubMed PMID: 23292264.

11: John M. Eisenberg Center for Clinical Decisions and Communications Science. Venous Thromboembolism Prophylaxis in Orthopedic Surgery. 2012 Aug 30. Comparative Effectiveness Review Summary Guides for Clinicians [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2007-. Available from http://www.ncbi.nlm.nih.gov/books/NBK107166/ PubMed PMID: 23035277.

12: Harenberg J, Marx S, Dahl OE, Marder VJ, Schulze A, Wehling M, Weiss C. Interpretation of endpoints in a network meta-analysis of new oral anticoagulants following total hip or total knee replacement surgery. Thromb Haemost. 2012 Nov;108(5):903-12. doi: 10.1160/TH12-07-0482. Epub 2012 Sep 26. PubMed PMID: 23014668.

13: Gómez-Outes A, Terleira-Fernández AI, Suárez-Gea ML, Vargas-Castrillón E. Dabigatran, rivaroxaban, or apixaban versus enoxaparin for thromboprophylaxis after total hip or knee replacement: systematic review, meta-analysis, and indirect treatment comparisons. BMJ. 2012 Jun 14;344:e3675. doi:10.1136/bmj.e3675. Review. PubMed PMID: 22700784; PubMed Central PMCID:PMC3375207.

14: Bozzato S, Galli L, Ageno W. Thromboprophylaxis in surgical and medical patients. Semin Respir Crit Care Med. 2012 Apr;33(2):163-75. doi:10.1055/s-0032-1311795. Epub 2012 May 30. Review. PubMed PMID: 22648489.

15: Thirugnanam S, Pinto R, Cook DJ, Geerts WH, Fowler RA. Economic analyses of venous thromboembolism prevention strategies in hospitalized patients: a systematic review. Crit Care. 2012 Mar 9;16(2):R43. [Epub ahead of print] PubMed PMID: 22405349.

16: Cohen A, Drost P, Marchant N, Mitchell S, Orme M, Rublee D, Simon TA, Sutton A. The efficacy and safety of pharmacological prophylaxis of venous thromboembolism following elective knee or hip replacement: systematic review and network meta-analysis. Clin Appl Thromb Hemost. 2012 Nov;18(6):611-27. doi:10.1177/1076029612437579. Epub 2012 Mar 2. Review. PubMed PMID: 22387582.

17: Falck-Ytter Y, Francis CW, Johanson NA, Curley C, Dahl OE, Schulman S, Ortel TL, Pauker SG, Colwell CW Jr; American College of Chest Physicians. Prevention of VTE in orthopedic surgery patients: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012 Feb;141(2 Suppl):e278S-325S. doi:10.1378/chest.11-2404. PubMed PMID: 22315265; PubMed Central PMCID: PMC3278063.

18: Raskob GE, Gallus AS, Pineo GF, Chen D, Ramirez LM, Wright RT, Lassen MR. Apixaban versus enoxaparin for thromboprophylaxis after hip or knee replacement: pooled analysis of major venous thromboembolism and bleeding in 8464 patients from the ADVANCE-2 and ADVANCE-3 trials. J Bone Joint Surg Br. 2012 Feb;94(2):257-64. doi: 10.1302/0301-620X.94B2.27850. PubMed PMID: 22323697.

19: Kwong LM. Therapeutic potential of rivaroxaban in the prevention of venous thromboembolism following hip and knee replacement surgery: a review of clinical trial data. Vasc Health Risk Manag. 2011;7:461-6. doi: 10.2147/VHRM.S4441. Epub 2011 Jul 18. Review. PubMed PMID: 21822393; PubMed Central PMCID: PMC3148419.

20: Maratea D, Fadda V, Trippoli S, Messori A. Prevention of venous thromboembolism after major orthopedic surgery: indirect comparison of three new oral anticoagulants. J Thromb Haemost. 2011 Sep;9(9):1868-70. doi:10.1111/j.1538-7836.2011.04421.x. PubMed PMID: 21711443.

21: Moher D. The problem of duplicate systematic reviews. BMJ. 2013 Aug 14;347:f5040. doi: 10.1136/bmj.f5040. PubMed PMID: 23945367.

22: Siontis KC, Hernandez-Boussard T, Ioannidis JP. Overlapping meta-analyses on the same topic: survey of published studies. BMJ. 2013 Jul 19;347:f4501. doi: 10.1136/bmj.f4501. PubMed PMID: 23873947; PubMed Central PMCID: PMC3716360.

On 2014 Jan 07, Robert Badgett commented:

This review includes the important trial comparing acupuncture to simulated acupuncture by Cherkin in 2009 and noted this trial was one of the 7 trials with low risk of bias.(1) However, this trial, which has an unfavorable conclusion when comparing acupuncture to simulated acupuncture, is not included in the analyses within this review.

Reference:

Cherkin CD et al. A randomized trial comparing acupuncture, simulated acupuncture, and usual care for chronic low back pain. Arch Intern Med. 2009. doi:10.1001/archinternmed.2009.65. PMID: 19433697

On 2014 Jan 30, Vivian McAlister commented:

Some concepts of normal anatomy come from study of diseased cadavers. This paper describes an erroneous concept, perpetuated for 200 years through plagiarism. See final draft here.

On 2014 Nov 17, Raphael Levy commented:

Comments available at my blog, authored by 1) Mathias Brust, Liverpool, 2) Quanmin Guo, Birmingham and, 3) Philip Moriarty, Nottingham.

A detailed analysis of this article, and more broadly of this body of work is published today in PloS One by Stirling et al; from the abstract: “through a combination of an exhaustive re-analysis of the original data with new experimental measurements of a simple control sample comprising entirely unfunctionalised particles, we conclusively show that all of the STM evidence for striped nanoparticles published to date can instead be explained by a combination of well-known instrumental artefacts, strong observer bias, and/or improper data acquisition/analysis protocols.”

On 2014 Mar 02, Daniel Schwartz commented:

This review is exceptionally thorough and provides nice insights into the therapeutic options in this uncommon but serious complication of hepatitis C infection. http://qxmd.com/r/24024840

On 2015 Feb 07, Jayaprakash Sahoo commented:

Current existing literature supports the association of serum testosterone with decreased adiposity and estradiol with increased adiposity in men.Finkelstein et al in their original article have introduced a new paradigm of estrogen deficiency contributing to increases in body fat in men. However, the conclusions of this study are not supported by some plausible pathophysiology.

The sex steroids (total) are not the only determinants of the fat mass. Alterations in fat mass in study subjects could be contributed by concomitant changes in GH-IGF-1, thyroid, cortisol axes and free sex steroid levels.Local conversion of androgen to estradiol at pituitary level is required for adequate production of GH in a normal adult male. Aromatase inhibitors may lead to adult GH deficiency resulting increased fat mass in them. Additionally, probable GnRH analogue induced hypothyroidism and estradiol induced thyroxine binding globulin changes can also contribute to fat mass alterations by disturbing the thyroid axis. Alteration of free cortisol due to estradiol induced change in cortisol binding globulin levels may be another significant contributor. Hence, a similar study incorporating all hormonal determinants of fat mass is required for clearing uncertainty in the pathophysiology.

On 2013 Dec 20, Serdar Balci commented:

See Erratum Invalid PMID: 24213311 Corrects abstract as "171 patients (90%) were alive"

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2014 Jan 10, Christopher Sampson commented:

And who would the 'heroes' be? Those for whom the compensation is most likely to compensate them for the loss of their organ (i.e. the poor).

Here in the UK, when one mentions a hero it is usually in reference to a soldier. The hero narrative is rampant. So who joins the army? In a cursory glance at the literature I find few data for the UK, but plenty for the US. For one, it seems that people are less likely to enlist if they have college educated parents. Why else would the British Army choose to focus its recruitment efforts in the poorest of schools? One wonders whether the (largely) privately educated graduates of Sandhurst will face the same danger to life as their soldier counterparts. Are we really comfortable with our heroes being less well educated than the beneficiaries of their heroism? I, for one, am not.

There is every reason to suspect that the same would apply to living organ donation. The hero narrative is only "appropriate and useful" as a means of dispelling guilt.

On 2014 May 26, Marc Girard commented:

As a drug specialist with a more than 30-year experience in safety, I was often missioned as a medical expert witness in criminal or civil inquiries on vaccine litigations, where I repeatedly pointed out the worrying lack of knowledge of most vaccine experts regarding the basic scientific and regulatory requirements normally applicable to pharmaceutical products – esp. as far as adverse reactions were concerned: this represents a tragic shortcoming for such preventive drugs, targeted towards people in perfect health with the problematic aim of protecting them against diseases the occurrence of which in a severe form is often an unlikely event, and for which therefore the risk of side-effects should not go beyond extremely narrow limits… Amongst many others examples, this paper by Tozzi et al. is an impressive illustration of this lack of expertise a far as drug safety is concerned.

Whatever the authors’ views on the matter, the primary tool to assess drug safety is not “epidemiological studies” but double-blind investigations versus placebo (a genuine placebo, namely a completely inert product and not another vaccine…) performed during development on a sufficient duration: as everybody knows, vaccine makers have managed the exploit to get exempted of this otherwise inescapable step. Additional indicators of amateurism in vaccine development include “fast track” procedures (whose consequences have been recently illustrated by the narcoleptic risk of Pandemrix), as well as the striking poverty of the dose-ranging studies (which account for regular turmoil in “experts” recommendations regarding the scheme of immunization as well as the timing of boosters).

As far as “epidemiological studies” are concerned, their main default is of being inextricably polluted by major conflicts of interests, as in most cases, they are performed either by the manufacturers or, even more frequently, by national or international health agencies (or their “experts”) whose most obvious interest is to hide the – sometimes tragic – drama they may have triggered by their irresponsible campaigns to promote some vaccines: this is the reason why, amongst a dozen of such studies performed on the neurological risks of hepatitis B vaccination, the only one showing a clear increase was also the sole whose financing was independent of any promoters of this immunization…

To come now to the assessment of causality of individual adverse reactions, the first remark is that the methodological inspiration of Tozzi et al. is regrettably obsolete. The use of algorithms has been almost completely abandoned by most regulatory bodies, for one reason which was pointed out more than 25 years ago [1]: namely, that use of algorithms (or decision table) is a tool for clinical decisions (e.g. to perform a laparotomy in view of such and such signs or symptoms), whereas assessing causality in drug toxicity is a process of knowledge, and not of decision (there is not the slightest signification in “deciding” whether a drug is, or not, the cause of an effect – and the reader has just to consider that this incredible way of reasoning is never used to assess drug efficacy, yet another pharmacological effect…). Lack of validation regarding the inter-raters agreement is an additional indicator of the methodological amateurism of the authors: this step should have been a strong prerequisite, taking account the vague of some items (e.g. that concerning an “appropriate time window after vaccine administration”, when experience of such an assessment with academic vaccine “experts” shows that it is almost invariably assessed as too short or too delayed… The same holds true for the item of “biological plausibility”, when experience, once again, teaches the fanatical obstinacy of most vaccine experts to challenge even the biological mechanisms which are most probable or convincing [2]).

Jacob Puliyel has listed a number of cases where Tozzi et al.’s algorithm would miss obvious vaccine causality. Let’s suggest another, that I witnessed in a number of sad instances: 3 weeks after a first injection, a person develops unexplained asthenia associated with paresthesia; one week after the second immunization, he/she develops motor symptoms, dysuria and visual disturbances; the day following the third injection, he/she is admitted to hospital where the diagnosis of multiple sclerosis is rapidly established. For any specialist in drug safety, the causal role of the vaccination would be highly probable: but not for Tozzi et al.…

Actually, amongst the 20 items of their checklist, no less than 15 (75%) are devoted to refute a vaccine-induced causality: no need to have read the Complete Psychological Works of Sigmund Freud to recognize the “resurfacing of the repressed” in such a bias. After all and as the authors confess with an astonishing ingenuousness, the main point is it not to “maintain public confidence in immunization programs”? Tell me: in any of the “immunization programs” – including those devised by vaccine makers [3]?...

REFERENCES

[1] Girard M. Quality of ADRs. Adv Drug React Ac Pois Rev 1987;4:231-232

[2] Comenge Y, Girard M. Multiple sclerosis and hepatitis B vaccination: adding the credibility of molecular biology to an unusual level of clinical and epidemiological evidence. Med Hypotheses 2006; 66: 84-86

[3] Cohen D, Carter P. WHO and the pandemic flu "conspiracies". BMJ 2010; 340:c2912

On 2014 Apr 18, Amitav Banerjee commented:

When death is the outcome temporally associated with an intervention such as immunization, it is better to err on the side of safety by presuming all deaths as probably AEFI unless other etiology is established beyond reasonable doubt. Establishing the cause of adverse event or death may not always be possible in developing countries as health facilities are lacking in rural and remote areas. In such situations, "Counting" without "Classifying" would be a more appropriate strategy to establish any AEFI by comparing with baseline data which can again be established by "Counting." Frequent exercises of classification of AEFI, though conceptually sound will not be sensitive enough to detect all cases of AEFI, without the backup facilities required to establish the correct cause of all deaths or adverse events following immunization in remote areas of developing countries. In such resource poor settings better penetration and more equitable distribution of health services and attention to under five malnutrition, in which we fare very badly, would prevent more cases of deaths due to pneumonia in children rather than adding on more and more vaccines. After promoting the pentavalent vaccine in developing countries, one would expect the same experts to promote the pneumococcus vaccine in these countries. One would wish that the policy makers concentrate more on "Health Promotion" which implies better sanitation, nutrition and education rather than on "Vaccine Promotion" which is a piecemeal solution to the problem of communicable diseases at an exorbitant cost. Amitav Banerjee, Professor Community Medicine, Dr D Y Patil Medical College, Pune, India

On 2014 Apr 09, B M Hegde commented:

"Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius and a lot of courage to move in the opposite direction,” wrote E. F. SCHUMACHER some time ago. We have many such expert groups in science and, more so, in medicine. “The algorithm should provide countries and health officials at the global level with an instrument to respond to vaccine safety alerts, and support the education, research and policy decisions on immunization safety.” This statement in the last part of the abstract tells the whole story. With the new instrument the response to every ‘vaccine safety alert’ will be denial. The new AEFI algorithm makes it possible to declare almost every vaccine related death as ‘unrelated to the vaccine’ based on the fact that deaths were not attributed to vaccine in the pre licensure studies.

It was Charles Sherrington, a Nobel Laureate in physiology, who wrote in 1899 when he became the professor of Physiology at the age of 42 in Liverpool University that “positive sciences can never answer the question “why”. They can, at best, answer “how or how much” but NOT “why?” As a physiologist I can say how the heart contracts, but not “why” the heart contracts. In reductionist science of medicine we take shelter under this wisdom to bury all the inconvenient questions. No one can for sure say “why” the child died after vaccination, new AEFI notwithstanding. Common sense, circumstantial evidence, emotional and spiritual quotients in our rounded education to be doctors should help us to answer such questions of cause-effect most of the time. Now even if a healthy child dies within minutes following vaccination and there is no alternate explanation for the AEFI, even then the powers that be could easily declare that death as coincidental and not due to the vaccine, thanks to the new AEFI. This is dangerous ‘science’.

B. M. Hegde MD, FRCP(Lond.), FRCP(Edin.), FRCP(Glas.), FRCP(Dub.), FACC(U.S.A.). Formerly Vice Chancellor, Manipal Academy of Higher Education, Manipal India

On 2014 Mar 26, J Stone commented:

None

On 2014 Mar 24, Toni Bark commented:

None

On 2014 Mar 12, Lokesh Tiwari commented:

There is conceptual flaw in the ‘Assessment of causality of individual adverse events following immunization (AEFI): A WHO tool for global use’ developed by Tozzi et al. If we apply common sense, fundamental safety rule is to identify threats to safety and fix them. Having so many deaths reported after immunization, particularly following pentavalent vaccine in the developing countries, it is important to develop a more sensitive tool to identify AEFI and classify them according to severity of threat they impose to human life and thoroughly investigate them. As pointed out by Puliyel J and Madhvi Y, Tool developed by Tozzi et al will under report AEFI. Considering sequence of events in the world pertaining to development of vaccines, their business, conflict of interests of health agencies and members of guideline committees, it seems that huge business in vaccine industry is affecting science of vaccines and we are developing various ways to promote the business at the cost of human lives. Compared to Brighton classification, tool developed by Tozzi et al has much less sensitivity to detect adverse events following immunization as it masks probable and possible reactions related to immunization and classifies them as inconsistent or indeterminant categories, giving ways to continue the use of potential risky vaccines. Going for a less sensitive tool for safety concerns is not only illogical but risky for the children of the world.

On 2014 Feb 20, Jacob Puliyel commented:

None

On 2014 Apr 26, Meenakshi Girish commented:

The admonition "be scientific" - whenever one does not back one's argument by scientific data - now sounds so hollow! Every scientific 'fact', it seems, has two sides. Of late this has become truer for medical science. And if, I as a clinician can get confused, imagine the plight of the lay public for whom it is confusion confounded. While preparing for a debate recently on vaccinations, I was perplexed that the IAP Committee on Immunisation states "The committee reviewed studies on the distribution and prevalence of different pneumococcal serotypes in the country, including some recent studies done by vaccine manufacturers in India like Pneumonet by M/s Pfizer and Alliance for Surveillance of Invasive Pneumococci (ASIP) by M/s GSK (unpublished). The committee concluded that the data on prevalence of different pneumococcal serotypes in the country was sparse and limited to few hospital based studies. On the basis of available data, it is difficult to evaluate the coverage of serotypes included in the existing Pneumococcal conjugate vaccine (PCV) formulations" [Indian Pediatrics July,2012]. Despite this the vaccine has been included in the IAP immunisation recommendations. Is the IAP justified in doing so? On the other hand, would they be wrong if they were to withold the recommendations till large scale studies are carried out.

On 2014 Mar 24, Paul King commented:

Dear Jacob Puliyel,

 The points you have raised are excellent.

 However, from the scientists' point of view, the reality is that all adverse events following inoculation (AEFIns) should be reported and, unless a causal relationship has been proven or unequivocally disproved, no attempt should be made to classify such AEFIns as they occur.

 Instead, a centralized open database system, like the U.S. Vaccine Adverse-Events Reporting System (VAERS), but one which has meaningful penalties for any healthcare provider's failure to report any possible AEFIn to those maintaining this AEFIn database, who after confirming the source of the report, its general validity, the vaccine's identity and lot identifier, and, in as much detail as possible, the temporal and symptoms information associated with that AEFIn, will post it to the database where an open search tool is provided for anyone to examine the data as they see fit (e.g., a search engine like the one available at <http://www.medalerts.org>).

 Then, on  vaccine type and specific vaccine source, temporal clustering and, for multiple-dose vaccines, the dose effect should be continually assessed for evidence of a signal (temporal clustering or associated much more with one manufacturer's vaccine than another manufacturer's comparable vaccine or a disproportionate number of AEFIns after the first dose as compared to the second dose when dosing occurs within a several weeks pattern). 

For new vaccines, all observed AEFIns following vaccination, regardless of the events found in the clinical trials used to get the vaccine approved for use, should be treated as possibly causally related UNLESS an in-depth autopsy clearly establishes that the vaccine could not possibly have been a causal or aggravating factor.

 In addition, for new vaccines, the government should require the manufacturer to distribute each lot in a suitable small contiguous population segment such that, if there is any possible "lot" effect, the "lot" effect should be more easily ascertained.

 Furthermore, before any vaccine is administered to a child, the child' temperature, pulse rate, weight, apparent health and the child's general health history should be recorded and, 30 to 60 minutes after the inoculations given, the child's temperature and pulse rate should be again recorded along with any apparent inoculation-site effects (e.g., redness and swelling) and inoculation-triggered reactions (e.g., fainting).

 Finally, absent unequivocal proof that a vaccine inoculation could not have caused conditions that led to a vaccinated individual's death or been a contributing factor thereto, all AEFIns that have death as an outcome should be labeled as probably vaccination related.

 From the viewpoint of the scientific method, any classification that establishes artificial barriers and criteria to the inclusion of observed events into the body of knowledge (as the WHO's proposed system so clearly does) should be REJECTED because it interferes with the scientific method's ability to observe all of the data and to generate testable hypotheses and draw inferences from the entire body of post-inoculation AEFIn information that has been generated by the actual events that have transpired. 

 Finally, in speaking of post-inoculation adverse events, term "immunization" should be replaced by "inoculation" because, as others have noted, it takes some time (weeks to months) for any significant level of protection to be generated after an inoculation; not all who are inoculated will develop that protection; and many, if not most, AEFIn events occur shortly after inoculation.

 The sooner all start being honest about the realities surrounding vaccine inoculation, the more likely it will be that the public will rely on the information provided.

 However, if, as the WHO seems to be doing and, in the USA, the U.S. Centers for Disease Control and Prevention (CDC) has been doing for years, public health officials continue to inflate the benefits of vaccination (by at least a factor of 10) and minimize the risks associated with vaccine inoculation (by a factor of 100), then, as is increasingly being observed in the USA and other developed countries, the public will become increasingly wary of vaccination.

 In much of the world, people understand that there are no true coincidences -- only events that have been made to appear to be coincidental by either a genuine lack of understand of the overall facts leading to the "coincidence" reported or by the deliberate suppression of the facts, including when, for example, AEFIns that result in death are made to "disappear". 

 Hopefully, the WHO will realize the scientific falsity of its current approach to classifying AEFIns in a manner that, in essence, pretends that the death did not occur after the vaccination or that it was a "coincidence" or "is unclassifiable", and abandon that approach.

 If the WHO does not recognize the preceding reality, then all of the scientists who study AEFIns in a given country need to demand that their governments reject the WHO scheme as vigorously as they are able!

On 2014 Mar 18, Jacob Puliyel commented:

Dr Malik, as part of the India Government Ministry of Health, has information on the AEFIs with Pentavalent vaccine and their investigation. I mention individual instances because Dr Malik is familiar with them and it best illustrates the harm done by the new system of AEFI classification.

Of the 54 deaths reported to the Government of India some have been investigated and the AEFI reports are available here

The deaths as described below could well have been caused by ‘multisystem generalized reaction to one or more vaccine components’ (page 50 of the CIOMS/WHO report). But a case definition for this entity has not been developed as yet by the Brighton group. When such multisystem reactions occur they appear like the multiple organ dysfunction syndrome (MODS) that follow sepsis but it must not be confused with it. The AEFI committee assumes that all MODS are due to due to sepsis or, if it is associated with unconsciousness, it must be meningitis/encephalitis. The new AEFI algorithm seems to promote and propagate this confusion.

1) The manner in which the deaths are declared as unrelated to the vaccine is instructive. The first of these deaths was in a child who was vaccinated at 11 AM. That evening at 5 PM the child had fever for which she was given paracetamol. The baby woke up several times that night crying. She was found dead in her bed next morning. There was blood around the nostrils.

On postmortem examination a large swelling around the injection site 9.8 x 7.9 x 4.7 cm with edema and infiltration involving muscle and subcutaneous tissue was noted. The internal organs including brain, kidneys and lungs were congested. There were petechiae on the surface of the lungs and bilateral adrenal bleeds. The report said the autopsy findings were consistent with death due to hypersensitivity reaction.

The AEFI report however says the death is unlikely to be a programme error or ‘due to vaccine associated to the vaccination’ (sic)

2) The central team looked at the 15 deaths in Kerala . One death in Pathanamthitta is reported in detail. The healthy 6 week baby was vaccinated on 26 December 2012 at 12 noon. The mother noted swelling of legs and the baby was ‘grunting’ and reluctant to feed. She was given 4 drops of paracetamol syrup for 'fever and crying' at 5 PM and 2 times on the next day. The baby was found dead with blood stained discharge from the nose at 4-30 AM on the morning of the 28th. No postmortem examination was performed.

The AEFI report classified this death as “Unknown unclassifiable category” in spite of the fact that the parents are available and gave a detailed history as part of the verbal autopsy.

3) The AEFI report has more interesting details that I quote verbatim: “Temporality of vaccination with death cannot be established as a causal relationship since it may also be possible that in the child had a subclinical infection (therefore no obvious signs and symptoms) and it aggravated in cold conditions, led to Bronchiolitis and death. This may be the reason for death due to pulmonary edema (manifesting as blood from the nose and in some postmortem findings of blood in respiratory tract).”

The cold conditions reported as leading to pulmonary edema and death is intriguing. Kerala has a climate that borders between a tropical savanna climate and a tropical monsoon climate. As a result it does not experience distinct seasons. The mean maximum temperature is 34 °C mean minimum temperature is 21 °C and the lowest temp recorded in December in Thiruvanthapuram was 20 °C..

The death in babies in Kerala who were apparently completely well in the morning when they went for immunization but who became unwell soon after vaccination and deteriorated rapidly to death cannot rationally be attributed to ‘subclinical bronchiolitis infection aggravated by cold conditions’ leading rapidly to pulmonary edema and death.

Any explanation no matter how outlandish seems adequate but the likelihood of there being a causative association with the vaccination, which is obvious, is not considered.

This is akin to a person found dead under the rubble after a house collapse. The house-insurance-company may refuse to pay the next of kin, saying the house collapse could have been coincidental and cannot be blamed for the death till it is proved that the deceased had not suffered a heart attack just before the house collapsed.

4) 8 deaths in Kashmir were investigated by the AEFI team.

There had been 1 death each in June September and December 2013, but in October there were 11 deaths according to a RTI response (AD/FW/K/RTI/822-24).

Many local newspapers reported the deaths in October were associated with use of a brand of Pentavalent vaccine called Easyfive which vaccine had previously been disqualified because of quality concerns but had just been reintroduced. Easyfive is not being used in the Kashmir Government immunization programme currently.

Like in Kerala, the deaths in Kashmir were attributed blithely to sepsis with metabolic disorder (in Aisha who had convulsions and normal CSF and no blood culture evidence of sepsis), meningitis (in Mozim based on persistent vomiting, metabolic acidosis, convulsions and crying excessively), pneumonia with aspiration (in Nida with fast breathing and gasping respiration with a family history of sibling death following pneumonia), liver disorder with metabolic acidosis (in Karneez with fever followed by repeated seizures but no CSF examination), sepsis with metabolic acidosis (in Shaistha crying excessively and irritable for 3 days after vaccination, convulsions on the third day, put on ventilator till death on 9th day). It is paradoxical, these diagnoses were reached on the clinical symptoms and laboratory findings of MODS without specific blood culture evidence of sepsis or CSF evidence of meningitis, suggesting the criteria for making these diagnoses are not strict like the algorithm needed to arrive at a diagnosis of death caused by vaccine. No death was attributed to MODS due to ‘multisystem generalized reaction to one or more vaccine components’. The most obvious possibility is not even mentioned in the differential diagnosis.

5) The doctors in the Kashmir hospital who noted the sudden increase in cases of deaths in October (11 cases in one month against the previous rate of 1 case in 2 months) sent telephonic text messages to senior government officials in the central government and state government to appraise them of these events but the AEFI team comes down heavily on them for sending these messages "as if to report 'breaking news'". Apparently they were expected not to take notice of these deaths and continue with business as usual and perhaps not to alert anyone.

It seems that after the October spike in incidence of AEFI deaths, the brand of vaccine was changed and the numbers of death have come down but the Government AEFI report does not mention it. It appears that although all brands of the vaccine have been associated with AEFI deaths in different countries, some brands may be particularly lethal.

A good AEFI reporting system must have picked up all these linkages which the new algorithm makes studious efforts to avoid.

On 2014 Mar 13, Jacob Puliyel commented:

6500 PENTAVALENT-VACCINE AEFI-DEATHS IN INDIA EACH YEAR CANNOT BE ACCEPTABLE

I thank Dr Malik for endorsing the opinion that the AEFI guidelines need to be revised. Unfortunately neither Tozzi and colleagues, nor Bonhoeffer et al (Bonhoeffer J, 2009) have responded and we do not know if the authors agree with us.

Dr Malik’s comment points out that India lacks a strong system of AEFI surveillance and investigation. This is undisputable. The fact of this poor surveillance in some States is clearly illustrated by the data obtained under the Right to Information from the Government of India, published by the Center for Science and Environment in their magazine – Down to Earth. Goa - a State with good surveillance and a low infant mortality rate (IMR 10/1000 live births) reported 26 AEFI deaths per 100,000 infants vaccinated with the Pentavalent vaccine whereas Gujarat, with poorer health infrastructure and high IMR, reported only 0.4 deaths per 100,000 infants vaccinated (Gujarat IMR is 50/1000 live births). The correlation between reported AEFI rate and IMR is illustrated here (R2 = 0.458).

Clearly AEFI deaths (following Pentavalent vaccination) in States like Goa and Kerala is much higher than previously (with the older DPT vaccine). If the Goa 'AEFI-death-rate' (reliable data from the state with the lowest IMR and presumably the best health infrastructure and surveillance systems) is projected nationwide and 26 babies are to die among every 100,000 babies vaccinated, 6500 AEFI deaths can be anticipated when the year’s birth cohort of 25 million babies in India are vaccinated. This cannot be acceptable.

On 2014 Feb 21, Akash Malik commented:

In total agreement to my worthy colleagues, the AEFI guidelines do need a revision, but citing an example from India (pentavalent) for this is inappropriate, because India lacks a strong system of AEFI surveillance and investigation.

It has to be taken into account that deaths after pentavalent (2.0 per lakh 1st doses of pentavalent vaccine),is less than the expected number of deaths (3.56 deaths per lakh live births)in the state of Kerala (Best performing state in India in terms of IMR )and this rate of 2.0 per lakh 1st doses of pentavalent vaccine is still less than the expected number of adverse events due to DPT alone.

It is important not only to report and highlight numbers, but also to correctly analyse them.

On 2014 Feb 20, Jacob Puliyel commented:

Tozzi and colleagues state that their article describes the new tool for causality assessment of AEFI as set out in the User Manual for the Revised WHO Classification

1) However this manual it seems has been developed without adequate care and without thinking through the consequences of the changes.

a) One pointer to this is how the manual cites an example of vaccines being wrongly blamed for events unrelated to its administration (Page 13). It says that vaccines were wrongly blamed for deaths resulting from consumption of the Cassia occidentalis beans causing a syndrome of acute hepato-myoencephalopathy. However the article they quote describes Japanese B encephalitis being blamed for the deaths – not the vaccine Panwar RS, 2008

b) Dr Madhavi put the new classification to a simple test. She tested how the system would have responded if the revised AEFI classification been in place in 1999. She suggests that the intusussceptions following use of RotaShield would have been classified as ‘inconsistent with causal association’ because:

i) other qualifying factors like previous similar reaction (re-challenge equivalent) were not available

ii) nor was biological plausibility demonstrated at that time

iii) and background rate, other exposures etc were not ruled out.

Under this category ‘inconsistent with causal association’ it would never activate the analysis reserved for ‘indeterminate’ reactions – “Information on AEFIs that are classified as indeterminate should be pooled and analyzed by time and place, in order to understand if the AEFI represents a new signal of an unrecognized event. Should this be the case, a more comprehensive epidemiological investigation should be performed.” Tozzi AE, 2013

These intusussceptions would have continued for years before the vaccine was pulled off the shelves.

2) In my previous comment I had pointed out that the experts investigating the Sri Lanka deaths from Pentavalent vaccine deleted the categories ‘Probable’ and ‘Possible’ from the Brighton classification and reported that although they found no alternate explanation for the deaths, the deaths were unlikely to be related to the vaccine. An apologist for the distorted Brighton Classification told me at that time that it was ‘experts’ who developed the Brighton Classification and it is alright for other experts to alter the classification. That was prescient. The new system makes a virtue of this ability to disregard the algorithm when it suits any expert. It says “Finally, instead of assigning a final category through an automatic classification process, the final outcome of the case investigation depends on the personal judgment of the assessor.” Tozzi AE, 2013

3) Post marketing surveillance is used to monitor the safety of a drug. Since drugs are approved on the basis of clinical trials which involve a relatively small numbers of people who have been selected for this purpose - meaning that they normally do not have other medical conditions which may exist in the general population - post marketing surveillance can further refine, or confirm or deny, the safety of a drug after it is used in the general population by large numbers of people who have a wide variety of medical conditions. (Abridged from Wikipedia)

The effort of the revised WHO Causality assessment of an AEFI is to deny adverse events noticed on post marketing surveillance, are caused by the vaccine (unless they had been observed in the original small clinical trials).

Events that occur 1 in 10,000, for example the intussusceptions with RotaShield will be noticed only in post marketing surveillance.

The AEFI in individuals was responsible for the ‘signal’. Evidence of causality in the individual provided evidence of causality in the population. The new system stands this logic on its head when it says on Page 5 that causality in the population must be known before causality in the individual can be ascribed.

“Causality assessment of AEFI should be performed at several different levels. The first is the population level, where it is necessary to test if there is a causal association between the use of a vaccine and a particular AEFI in the population. Secondly, at the level of the individual AEFI case report, one should review previous evidence and make a logical deduction to determine if an AEFI in a specific individual is causally related to the use of the vaccine. The third level of assessment is in the context of the investigation of signals.”

I am not stating that there is something sacrosanct about the original Brighton Classification but one has to evaluate the two schemes (Brighton vs CIOMS) from the point of view of patient safety to see which scheme would react to rare RotaShield-like-reactions first. The causality scheme that insists on calling all reactions as ‘indeterminate’ or ‘inconsistent/coincidental’ just because they were not noticed in the original small clinical trials, undermines the very raison d'être of post marketing surveillance. Patient safety (meaning protecting patients) rather than vaccine safety (protecting vaccines) is what is important.

On 2014 Feb 15, Y. Madhavi commented:

The above responses have raised very pertinent and highly contentious issues regarding CIOMS/WHO tool for the causality assessment of AEFI presented in Tozzi et al paper. This tool has negative implications in resource poor settings with poor surveillance systems and inadequate infrastructure.

Tozzi et al’s model claim to establish the causality between vaccine and AEFI referring to the general and cause-specific definitions of CIOMS (2012), (pages 39-40). However, it is not that simple nor is it really helpful. For instance, intussusception is a known adverse event with rota virus vaccine. But intussusception can also happen without Rotavirus vaccination. Suppose, if it happens in the week after immunization, it is possible that it is caused either by vaccine or it could be that the child was to get it any way and vaccination was coincidence. Yet the CIOMS scheme will classify this as 2A Consistent causal association to immunization [http://www.who.int/vaccine safety/initiative/tools/vaccinfosheets/en/index.html].

On the other hand had the CIOMS scheme been in use since1999, it is interesting to speculate how these intussusceptions would have been classified given that there was no known causal association. The fact that the event could take place independently of vaccination and no clear biologically plausible explanation linking it to the vaccine, it would be classified as 1A or 4C ‘Inconsistent causal association to immunization’ or ‘C. Coincidental’ [http://www.who.int/vaccine safety/initiative/tools/vaccinfosheets/en/index.html].

Reactions classified as ‘Indeterminate’ may at some point be evaluated if similar events are reported to identify a signal of a new potential causal association. Reactions classified as ‘Inconsistent causal association to immunization’ are not even reviewed later.

Dr. Puliyel is correct in suggesting that, a child who develops high fever within 2 hours, has convulsions, then lapsed into a coma and dies within 10 hours following immunization will be classified as ‘unclassifiable’ because ‘encephalitis’ as cause of the event cannot be ruled out.

Tozzi et al, argue that in the case of ‘events with a consistent temporal relationship but with insufficient evidence for the vaccine as a cause according to well designed epidemiologic studies… further studies are encouraged if other similar events are identified......’. This can be used to defer discontinuation of the vaccine despite adverse effect. Moreover, the requirement for ‘other similar events’ is vague, as it does not specify how many events are needed to suspend vaccination.

In a recent controversy on AEFI causality report on pentavalent vaccine in India, deaths following vaccination were attributed to sudden infant deaths (SIDS) without doing proper investigation. In the causality assessment of 15/2/13, the AEFI committee reported eight infant deaths as SIDS. However, in a new causality report, which is now available with the health ministry, only one death due to SIDS, three deaths with causal association with immunisation and seven deaths as 'unclassifiable' including those previously reported as SIDS [http://www.pharmabiz.com/NewsDetails.aspx?aid=79591&sid=1]. It is interesting that where sufficient information was previously available to arrive at the ‘diagnosis by exclusion’ of SIDS the information was later considered insufficient enough to merit the new classification as ‘unclassifiable’. “The final classification should be based on the personal judgment of the assessor”, according to Tozzi et al, (page no 5043, under 3.3 Algorithm), and this will result in numerous similar discrepancies in the classification directly related to the number of people whose ‘personal judgment’ is sought.

In India, there have been around 21 deaths and 83 adverse events reported following pentavalent vaccination which was introduced in a few states last year. Rather than halting the vaccination till its safety is proven, India extended its vaccination to the rest of the states under international pressure.

If the sole purpose of CIOMS/WHO tool of causality for AEFI is to ensure vaccine safety in the population, the pentavalent vaccination would have been halted in India, as it was done in countries like USA (rotavirus vaccine), till the vaccine safety is established.

The main emphasis of Causality assessment of AEFI approach seems to be to cite either the lack of strong evidence for causal association or the presence of strong evidence against causal association, to classify an adverse event as “Not an AEFI”.

On 2014 Feb 05, Brandon Horn commented:

Drs. Puliyel and King,

Thank you for the insightful observations. Just wanted to add that antibody response time is quite variable. Theoretically, we would see adverse events also happening weeks to months after introduction to an antigen. Varicella for example produces symptoms typically 10-21 days after exposure. Antibody detection for HIV occurs between 3 and 6 months. Therefore, we could expect some serious adverse events, for example related to autoimmune disease, to show signs up to 6 months+ post-inoculation. This is one of the reason it is so hard to study vaccine adverse events in the United States, because the vaccine schedule makes any pediatric autoimmune disease temporally associated with a vaccination. Animal studies have indicated that this indeed can occur.

On 2014 Feb 05, Paul King commented:

In general, as a scientist who studies vaccine safety, effectiveness, and cost-effectiveness issues, I support Dr. Puliyel's observations and suggestions.

Moreover, the use of the term "coincidental" should be limited to those instances where a full autopsy, including appropriate tissue section examinations fails to find any potential causal or contributory factor that may be related to a preceding vaccination. In science, while it is a reality that the relationship between a specific vaccination and a subsequent serious adverse event MAY be "coincidental", proof is required that all of the other scientifically plausible linkages between the vaccination and the AEFI have been properly considered and ruled out by scientifically sound and appropriate medical evidence BEFORE that AEFI should be labeled as "a coincidence".

Furthermore, intervening events between the vaccination and the adverse reaction reported should NOT preclude the possibility of the vaccines' given being a possible or probable causal factor UNLESS the intervening event completely accounts for "100%" of the symptoms and findings that may be attributable to the suspected vaccination/vaccinations.

In addition, when an adverse events occur after vaccination/vaccinations, such events should still be classified as "possibly" or "probably" associated with the suspected vaccine when other probable or possible causal factors are identified UNLESS the other factor(s) completely preclude the vaccine from being a causal factor.

Finally, when looking at a possible adverse event and a suspect antecedent vaccination set, one should consider ALL of the case's antecedent and concomitantly administered vaccines in light of the their possible contributions to the adverse outcome observed before attempting to assign a possible or probable linkage between a given vaccine and and the adverse-event observed.

Thus, UNLESS there is definitive proof that some intervening non-vaccine event caused the adverse outcome that was reported, an Adverse-Event Following Inoculation (AEFI) should always remain an AEFI [Note: As an example, a child's death is reported 2 weeks after as the child received an AEFI but the causal event is found to be that an appliance (e.g., a television) was knocked off onto the child while the child was sleeping -- causing the child's death. Only in such instances, should an initial AEFI could be reclassified as a not an AEFI.

In addition, whenever a "new" vaccination program is introduced, since the goal is to ensure the vaccine being introduced is "safe" and there is no real-world experience in the population as to what serious adverse events may occur or their rate of occurrence in that population, AEFIs that are serious should be presumed to be linked to the "new" vaccination program in question UNLESS there is definitive evidence that only other factors were causal -- especially in instances of deaths shortly after inoculation.

Furthermore, since most serious adverse events occur shortly after inoculation, the term "AEFI" should be redefined as "Adverse-Event Following INOCULATION" because the vaccine has not had time to generate any effective level of disease protection in the inoculee and, in some instances, the children having the adverse reaction do not develop any level of disease protection -- especially in those instances where the adverse-event is "death" shortly after inoculation.

Clearly, if the choice is between the Brighton criteria and those being proposed in the WHO "tool", obviously the Brighton criteria should be retained and the scientifically challenged criteria proposed by the WHO should be rejected.

On 2014 Feb 04, Jacob Puliyel commented:

DEATHS IN DEVELOPING COUNTRIES WILL COUNT FOR LESS

Tozzi et al describe causality assessment for AEFI using criteria from the CIOMS/WHO working group on pharmacovigilence . AEFI is any untoward medical occurrence following immunization. A causal relationship is not implied. The Brighton collaboration classified reactions as very likely/certain; probable; possible; unlikely; unrelated; unclassifiable, based on temporal criteria and evidence of alternate etiological explanation. Deaths soon after immunization without an alternate explanation were classified as ‘probably related to vaccine’.

THE NEED FOR A NEW CLASSIFICATION

With use of Pentavalent vaccine (Diphtheria, Tetanus, Pertussis, Hib and Hepatitis B) in developing countries, there have been many AEFI deaths. WHO experts investigated these deaths in Sri Lanka. They could find no alternate explanation for 3 deaths. The experts write in the report that they deleted the categories ‘probable’ and ‘possible’ from the Brighton classification and after that, although they could not attribute deaths to another cause, they were declared unlikely to be related to the vaccine. The association to vaccine should have been classified as ‘probable’. The BMJ published a letter about this Saxena KB, 2010

1. The CIOMS/WHO report came after the BMJ letter. The committee, composed of 40 members (19 were vaccine-industry representatives), proposed changes to how AEFI are investigated and reported. The 194-page document has serious implications for developing countries.

2. Case definitions for different adverse events were developed. Illogically, the inclusion criteria for the proposed case definitions are too strict to be of scientific value in most countries. For example, to diagnose ‘encephalitis’ one needs the child with fever and encephalopathy to live at least 24 hours after AEFI onset, and have a CSF examination, an EEG or neuro-imaging and one of these investigations must be positive, to reach a level 2 diagnosis (page 73).

3. Presume that a healthy child is vaccinated. Suppose she develops high fever within 2 hours, has convulsions, then lapsed into a coma and dies within 10 hours. (Variations of this scenario have been enacted repeatedly with Pentavalent vaccine). Using CIOMS/WHO definitions, as the encephalopathy lasted less than 24 hours, it cannot be classified as encephalitis. In many countries, the facilities for a lumbar puncture may be unavailable, much less those for an EEG and CT/MRI. Under the report’s scheme, this would be labeled, “Insufficient information to distinguish both acute encephalitis and ADEM; Case unable to be definitely classified”.

4. Further, on page 170 (i) (in very small print), the report says, “Such a case must be classified as 'Not an AEFI'”. This last step, which classifies an “AEFI” as “Not an AEFI”, is patently unscientific, illogical and Orwellian.

5. The scenario described could well have been caused by ‘multisystem generalized reaction to one or more vaccine components’ (page 50). The encephalopathy, fever and convulsions could follow systemic inflammatory response but CIOSM does not have case definition for this, and inability to exclude causes of encephalopathy, is sufficient to classify the reaction as ‘not an AEFI’.

6. The risk is not merely theoretical. In March 2013 WHO investigated 12 deaths in Viet Nam from the same Pentavalent vaccine. The Viet Nam report stated, “no fatal AEFI has ever been associated with this vaccine”. The 2008 WHO experts had earlier classified the Sri Lanka deaths as AEFI unlikely to be related to vaccine. The Viet Nam report stating ‘no fatal AEFI has ever been associated with this vaccine’ suggests the Sri Lanka AEFI is now reclassified as “Not an AEFI”.

7. Tossi et al suggest that ‘events with a consistent temporal relationship but with insufficient evidence for vaccine as a cause, according to well designated epidemiological studies – in such cases, further studies are encouraged if other similar events are identified’. There have been 54 deaths temporally related to the vaccine in India. Instead of taking them as a group the new system looks at ‘individual adverse events’ and then labels them as ‘not an AEFI’ making way for many more deaths.

8. Tossi and colleagues report different clinical scenarios (Supplementary material). The scenario in Asia is also worth considering. Pentavalent vaccine is selectively promoted in developing countries with poor surveillance systems. Eighty three deaths following Pentavalent inoculation have been reported from Asian countries Puliyel J, 2013. There is no plausible alternate explanation. Most deaths occurred after the first vaccine dose, fewer after the second, and hardly any after the third. This pattern argues against the deaths being random events. Yet, the WHO to maintains that a cause and effect relationship has not been established.

9. This contrasts with what happened in 1998 when RotaShield was approved in the US. When intussusceptions were reported to the Vaccine Adverse Event Reporting System (VAERS) and only 12 children were affected the vaccine was withdrawn. No one needed to be ‘certain’.

10. A public health expert in India, Dr Y Jain has filed a public interest petition in the Supreme Court asking for these deaths to be investigated. The petition states that in the first six months, when the 40,000 doses were administered to children in the southern state of Kerala, at least five children died. Extrapolated to the 25 million babies born in India each year, 3,125 deaths can be expected from the vaccine each year. Using the best evidence from the Minz study Minz S, 2008 the incidence of Haemophilus influenzae type b meningitis in India is 7/100,000 children under 5. Using the Unicef rapid method to estimate Hib Pneumonia 350 deaths from Hib disease will be prevented over 5 years by vaccinating one birth cohort of 25 million. 3125 deaths from AEFI cannot be acceptable to prevent 350 Hib deaths.

11. The Infant Mortality Rate (IMR) in Kerala is 14. Seven of these deaths occur in the first month. The other seven deaths occur in the remaining 11 months of the infant’s first year. Pentavalent vaccine is administered six weeks after birth to babies who have survived neonatal life. Of the first five deaths from the vaccine, four occurred within 24 to 48 hours of the first dose of this vaccine. The death rate of babies in the first days after vaccination works out to be two to four times higher than Kerala’s post neonatal IMR.

12. The first 14 deaths in Kerala were investigated by AEFI experts. They reported 6 children had co-morbid conditions and the other 8 died of sudden infant death syndrome (SIDS). This SIDS rate on day after vaccination is higher than the all-cause IMR.

13. Under the new scheme, fatal AEFI in developing countries will be falsely recorded as ‘Not an AEFI’, simply because some time or test criterion was not met. Death is the worst AEFI possible. Continued use of the CIOMS/WHO scheme will result in missing an important opportunity to pick up signals that could save lives. This is dangerous. Perhaps we need to get back to the Brighton Classification.

On 2014 Mar 06, Christopher Southan commented:

Both the target and drug lists from this publication have been instanciated at http://www.guidetopharmacology.org/lists.jsp#drug

On 2013 Sep 26, Markus Meissner commented:

Dr Clare Harding (Meissner group):

This study by Farrell and Gubbels continues this group’s work in understanding the unusual method of cell division in Toxoplasma gondii, specifically the role of the kinetochore, a complex of proteins used to attach the centromere to the spindle fibres in mitosis. In Toxoplasma, unlike in mammalian systems, there is now convincing evidence that chromosomes remain attached to the spindle core throughout the cell cycle. This suggests that the kinetochore could be dispensable in Toxoplasma replication. The authors demonstrate that two conserved kinetochore proteins, TgNuf2 and TgNdc80, remain associated with the spindle core throughout the cell cycle in Toxoplasma. Although ablation of microtubules resulted in a partial disruption of kinetochore clustering, microtubules were not absolutely required for this localisation. Interestingly, conditional knock-down of TgNuf2 resulted in a complete inability of the parasites to grow. As predicted from other organisms, a reduction of TgNuf2 resulted in chromosome miss-segregation.<br> Knock-down of TgNuf2 resulted in simultaneous depletion of TgNdc80. This suggests these proteins form a stable dimer, which has been demonstrated using human proteins however remains to be confirmed in Toxoplasma. However, depletion of both proteins complicates the picture with regards to the phenotype observed. The authors were unable to identify any other components of the kinetochore through homology to other organisms and several key components of these pathways appear to be missing in Toxoplasma. In order to fully understand the role of the kinetochore in Toxoplasma cell division, more components of the kinetochore need to be identified, potentially using a pull-down approach. The identification of a putative novel nuclear localisation signal (NLS) for apicomplexan parasites is potentially interesting and the authors have demonstrated that this sequence is important for the localisation of TgNuf2. However, as the authors mention, it is possible that this domain is required for the structural integrity of the protein; hopefully future studies will address this issue in more depth.<br> Overall, this is a very interesting paper which significantly adds to our knowledge of the molecular mechanisms of cell division in this apicomplexan parasite.

On 2014 Mar 01, David Mage commented:

The author is correct that infant asphyxia of overlaying by a co-sleeper has an equal risk for both males and females Williams FL, 2001. However, he is incorrect that the ratio of male to female infant deaths by SIDS is usually 2:1. When all SIDS studies are combined the male fraction goes to 0.61 corresponding to a male:female ratio of 3:2, not 2:1 Mage DT, 2004, Mage DT, 2014.

On 2014 Nov 17, Denis Lebel commented:

The administration process is a complex one. The authors of this paper did a very good job of identifying drug administration sub-steps. This paper should be read by anyone planning the implementation of a computerized medication administration record.

On 2013 Oct 30, Edurne Zabaleta-del-Olmo commented:

It is an interesting review article which highlights the barriers to collaborative work between nurses and physicians practitioners in primary care health. The most common barrier is the lack of awareness by physicians of the scope of nursing practice. Working in partnership is essential so it is necessary to build the strategies intended to promote it. Congratulations to the authors.

On 2014 Mar 11, Harsha Radhakrishnan commented:

For someone like me with a limited understanding of how MRI works, this is an amazing paper.

On 2013 Oct 05, Daniel J Simons commented:

The paper implies that game training allows adults to perform as well as 20 year olds when multitasking. What it actually shows is that after training on the game, older adults perform as well as younger adults who are playing that same game for the first time. It does not show that training allows the older adults can multitask as well as the younger subjects in any other context. For example, the training did not lead to differential improvements on an a dual-task outcome measure.

The study had a small sample size (about 15/condition), and the analysis did not correct for multiple tests, meaning that it is not clear whether training led to any reliable improvements on the outcome measures.

The paper also did not control for expectations in the training and control group, meaning that any differential improvements upon re-testing could be due to differential placebo effects.

I have posted an extensive post-publication review of the paper here: http://blog.dansimons.com/2013/09/19-questions-about-video-games.html

On 2015 Feb 12, Tamás Ferenci commented:

EDIT (2015 Feb 13): I removed my comment for reasons of elegance, as Dr. Miller's original comment - to which I was solely replying - was also removed.

On 2015 Feb 12, Clifford Miller commented:

None

On 2015 Feb 11, Tamás Ferenci commented:

Dear Dr. Puliyel,

re: the TOKEN study. You quote Table 31, which (a) pertains not to the hexavalent vaccine, but rather hexa- and pentavalent combined (I'll return to the significance of this shortly), and (b) presents the results of the unweighted analysis.

Let us first examine what weighting means. It is possible to compensate for the preferential enrollment of those who were recently vaccinated (which is not only a theoretical possibility, rather, its existence has been empirically demonstrated in the study), by a method called inverse-probability weighting, thus providing better estimates. Not only I'm saying this, but the authors of the study themselves (p. 13):

The results obtained from these weighted analyses are regarded as more valid and are therefore presented in this summary. For reasons of completeness, the unweighted analyses are reported in the full study report in addition to the weighted risks estimated.

So, you were quoting the less valid results, which were only presented for the sake of completeness. Let us now go to your other source, Table 36. It is at least a weighted analysis, but the first problem still lingers: it is again not pertaining to hexavalent vaccine, but hexa- and pentavalent combined. The problem is, that the results are dominated by the effect of pentavalent vaccine (cf. Table 41), which is on the one hand not the issue discussed here, and on the other hand, it was also the more error-prone part of the study, given the fact that only 14 pentavalently vaccinated subjects were included (as compared to the almost hundred hexavalently vaccinated). For objectivity, I once again quote the authors of the study (p. 14):

In addition, response rate was especially high for parents whose deceased child was recently vaccinated with a pentavalent vaccine. This self-selection and the very low number of cases substantially limits interpretation of these findings.

Now let's move on to the issue that is actually discussed for this article, the hexavalent vaccine. Table 27 presents the results with the weighted analysis in the 1st and 2nd life-year combined: there is no increased risk neither with Model 1, nor with Model 2 (just to refer to your remark...), Table 28 shows the results for 1st year alone: there is no increased risk neither with Model 1, nor with Model 2. Tables 29 and 30 presents the results of the stratified analyses, none of which shows increased risk.

I also note that there was a case-control part in addition to the SCCS, which found no increased risk in any of the investigated scenarios.

re: reporting bias. I believe we have discussed everything here, just one very minor addition, which cropped up when I was browsing the comments. At another point, Dr. Miller is quite strongly arguing that 90% (!!!) of the adverse events, even serious adverse events, he specifically added (and used in the calculations for SIDS), don't get reported. Now 90% is not reported or these events are "investigated thoroughly" and thus "ascertainment bias is not likely to play a major role"...? You should decide..

On 2015 Feb 06, Jacob Puliyel commented:

None

On 2015 Feb 05, Tamás Ferenci commented:

Dear Dr. Puliyel,

Thanks for your response. Let me have a few comment on it.

If the reporting is so bad the clusters aren't real, then the data can't/shouldn't be used to defend its safety.

Or to question it... Actually, I very much do hope that it is not used, at least in itself, to "defend" its safety: like I already discussed, this data simply can't be used for such purposes, the sole application is to warrant the performing of active safety studies (which have been done).

3A data is self-reported. It is no crime if a parent does not report to the doctor that their child developed leg pain a few days after being administered Infanrix.

For the record, 3A includes only serious adverse events, ranging from ITP through haematochezia to anaphylaxis, and yes, it even includes deaths. While I agree that reports made by parents can not be compared to reports made by physicians, comparing such adverse events to "leg pain" is not too fair, either.

Forensic experts are unlikely to ‘forget’ to mention immunization, simply because it was not given on the day of death but on the previous day.

By this, we get back to the first half of the 1st remark in my original comment (which you have not addressed). Under the circumstances you described, we could very well argue that such "professional forensic experts" are also unlikely to forget a vaccination a week ago as well, yet, it can be easily demonstrated that in reality this needs to be the case, see my original comment.

But it is difficult to argue convincingly that higher under-reporting is likely on the day just after a vaccine is administered, compared to the day of vaccination.

Actually, we don't need to: Day 1 is not significantly different from Day 0, Day 2 is the same as Day 1, so the first point where the number of reports truly drops is at the third day.

Tables 31 and 36 show significantly increased risk of unexplained sudden unexpected death in the first 3 days after hexa- or pentavalent vaccination (1st and 2nd year of life).

While I am not specifically familiar with the TOKEN study, it is immediately clear that you only cited half of the results: those tables also reveal that while there is indeed a period of increased risk on day 0-3, but this is followed by a period (day 4-7) of decreased risk, the net effect of which is an unchanged risk...

So it appears that active studies have confirmed that there are two vaccines which cause 'sudden deaths'.

OK, so we have a range of studies cited by Dr. Franco (none of which you have addressed), all having negative result, a SINGLE study which you cited, whose results are summarized by its own authors as "[t]he main study analysis showed no increased risk of sudden death within one week after hexavalent vaccination [...] multivariate case-control analysis [...] was in accordance with this finding and did not suggest a risk increase within one week after hexavalent vaccination", and you described this situation as "active studies have confirmed that there are two vaccines which cause 'sudden deaths'". Well...

On 2015 Feb 04, Jacob Puliyel commented:

I thank Ferenci and Miller for their responses. I will address the three points made by Dr Ferenci

1) The data I have quoted (from Table 36) was made available by the manufacturers GSK, to defend the safety record of Infanrix Hexa to the regulatory authority (- the EMA). The data suggests a cluster on and following the day of vaccination. If the reporting is so bad the clusters aren't real, then the data can't/shouldn't be used to defend its safety. If the reporting is good, then the clusters are real too, and the vaccine looks unsafe.

2) Dr Ferenci writes “ ..it is immediately obvious from 3A appendices (pp. 301-522, pp. 857-1064) that no matter which disease-group we look at, the vast majority of spontaneous reports with known time are definitely coming from the first few days!”

The sources for the the reports in the 3A appendices are different. 3A data is self-reported. It is no crime if a parent does not report to the doctor that their child developed leg pain a few days after being administered Infanrix.

But SIDS deaths are different and have to be reported mandatorily to those like coroners who must determine the cause of death. They are investigated by professional forensic experts. SIDS are ‘deaths under suspicious circumstances’ - unexplained death that could be infanticide unless proved otherwise. Forensic experts are unlikely to ‘forget’ to mention immunization, simply because it was not given on the day of death but on the previous day. Reporting bias is less likely to be an issue with such forensic reports. Under-reporting on all days will of course still occur for all the reasons it occurs for other serious adverse events. But it is difficult to argue convincingly that higher under-reporting is likely on the day just after a vaccine is administered, compared to the day of vaccination.

3) Finally, Dr Ferenci says that active vaccine safety studies are better than passively acquired data. For well designed, managed and executed studies I wholeheartedly agree with him.

The TOKEN study aimed to assess comprehensively a possible causal relationship between vaccination and unexplained sudden unexpected death of children between their 2nd and 24th month of life. The study was supported and sponsored by the Paul-Ehrlich-Institute (PEI) and the Federal Ministry of Health (Bundesministerium für Gesundheit). Unfortunately this large study with a wealth of data has not been published in an indexed peer reviewed journal as yet. It is available here: http://www.rki.de/DE/Content/Gesundheitsmonitoring/Studien/Weitere_Studien/TOKEN_Studie/Studyreport.pdf?__blob=publicationFile

Parents of children who had died of SIDS were requested to participate in the study. 37.6% (254 cases) could be included in the study, where parental consent was obtained. Tables 31 and 36 show significantly increased risk of unexplained sudden unexpected death in the first 3 days after hexa- or pentavalent vaccination (1st and 2nd year of life).

So it appears that active studies have confirmed that there are two vaccines which cause 'sudden deaths'. I am grateful that the Italian Court has allowed public scrutiny of GSK's PSUR reports held as confidential by the EMA.

Jacob Puliyel

On 2015 Feb 08, Clifford Miller commented:

There is a matter to add to my above comments concerning the Observed/Expected analysis provided by GSK to the European Medicines Agency [EMA] and to my exchanges with Dr Ferenci here: http://www.ncbi.nlm.nih.gov/pubmed/24004825#cm24004825_8920

Where death and vaccination occurred on the same day, unlike any death occurring after the day of vaccination, only half the children who would have been expected to die by chance alone would have been vaccinated.

As vaccination appointments can take place at any time during the daytime, one has to adjust for the expected number of deaths by chance where the child died without being vaccinated.

Neither GSK nor the EMA appear to have considered that point judging by the information in GSK's PSUR's 15 and 16.

SIDS cases are often found in the early hours of the morning and can also die in their sleep at any time during daytime.

This would mean that half the number deaths expected by chance on Day 0 would have been of vaccinated children. So only half the number of spontaneous reports would be expected.

Spontaneous reports of adverse events cannot be relied upon to state the exact times of death nor of vaccination. The detailed narrative accounts of cases in GSK's PSURs 15 and 16 support this. So it seems unlikely that Day 0 means a period of 24 hours commencing from the time of vaccination but merely means the calendar day starting from and ending at midnight.

On such a basis, if all deaths occurred on the first dose the number expected by chance to die regardless of vaccination would be 162 and not GSK's 54. The data suggests one must weight the expected deaths as it seems more deaths were on the day of the first dose - namely on the same day as vaccination. So one would expect by chance alone a lower number than 162 deaths, but a higher number than 54.

Adjusting for underreporting running at 90% in a country, the UK, with better reporting rates than most other countries this brings us to expect no more than 16 spontaneous reports of sudden deaths to occur by chance on the day of first vaccination if all 162 deaths expected by chance were vaccinated.

But if only half the number of children who might be expected by chance to die are vaccinated [81] then one expects no more than 8 spontaneous reports of deaths associated with contemporaneous vaccination to be by chance compared to the 16 actual reports.

What is remarkable about that is 16 deaths were observed. This is in close correspondence within the same order of magnitude with a crude estimation of the number of spontaneous reports one might expect by chance to coincide with vaccination [ie. 8].

In addition, the healthy vaccinee effect being greatest on the first day of vaccination [1] indicates a low likelihood these are spurious mere coincidences. And as Dr Puliyel has observed, sudden deaths of children are investigated as potential cases of infanticide, unlike other kinds of deaths. And ~90% of the spontaneous reports were by medical professionals.

So one has a greater degree of confidence such reports are more reliable and that the reports are of children who died because they were vaccinated and not because it is mere coincidence. The numbers do not support the latter conclusion.

As noted previously, the proper comparison is not what GSK submitted to the EMA but between the number of spontaneous reports to be "Expected" by chance and those "Observed".

I note Dr Puliyel asked for peer review of his observations. I too ask the authors of this paper to do the same for those I have set out.

[1] https://www.ruor.uottawa.ca/bitstream/10393/31774/1/Hawken_Steven_2014_thesis.pdf

EDITED FOR GREATER CLARITY @ 14:30 GMT 8th Feb 2015

On 2015 Feb 05, Clifford Miller commented:

Whichever way one looks at this problem, the reports of sudden death do not look like they should be considered in any way coincidental.

Ignoring the observed clustering of reports on the day of and days following vaccination, if the GSK figure of 54 is not the number of deaths to be expected on any day but the number of deaths to be expected to coincide with any one of the three vaccinations in a 180 day vaccination period: 1) without correcting for underreporting; 2) assuming the rate of sudden death GSK used is applicable for the periods concerned; 3) the healthy vaccinee correction of 0.8 is applicable; and 4) this is not confounded by co-administration the same day with any other vaccine, then one would expect 54 deaths to coincide with the day of vaccination over the course of three vaccines.

It is not however the correct calculation for the number of deaths to be expected to be reported. And that is what GSK and the EMA should have compared.

Ignoring 2), 3) and 4), underreporting of serious adverse events to safety regulators is high. Correcting for underreporting using the rate observed in a country with good rates of reporting, then GSK's 54 figure becomes 5.4 expected reports [90% underreporting of serious adverse events] compared to 16 reports of observed actual deaths:

"Compared to other countries the number of spontaneous reports submitted in the UK is relatively high and reporting rates in relation to prescription volumes are also among the best in Europe.2 It is estimated, however, that only 10 per cent of serious reactions and between 2 and 4 per cent of non-serious reactions are reported.2 Such a high level of under-reporting will necessarily lead to bias in the data collected via the Yellow Card Scheme." BMA Board of Science Reporting adverse drug reactions A guide for healthcare professionals May 2006

Even if we assume a highly conservative figure for underreporting namely that 2/3 of serious adverse events are not reported, the GSK figure becomes 18 compared to the observed 16.

And the healthy vaccinee correction may be optimistic. A 2014 thesis published by the University of Ottawa shows that on the day of vaccination serious ill health in children is 1/3rd of that on any other day, so one would expect spurious reports of merely coincidental ill-health to be 1/3rd of those on any other day including being lower than on the day following vaccination:

https://www.ruor.uottawa.ca/bitstream/10393/31774/1/Hawken_Steven_2014_thesis.pdf

The position is confounded by Infanrix Hexa being co-administered with two other vaccines on the same day - so it is not the only vaccine to be considered. According to Wyeth's [now Pfizer] PSUR 4 for Prevenar 13 the rate of reported neurological complications is highest when co-administered with Infanrix Hexa, lowest when administered alone and when administered with any other vaccine the figure lies between the two. [1]

[1] Prevenar 13 : PSUR 04 – Response to RSI MA numbers: EU/1/09/590/001-006

On 2015 Feb 04, Clifford Miller commented:

My reply to Dr Ferenci [2015 Feb 03 2:20 p.m.] now appears beneath his comment [2015 Feb 02 09:30 a.m.]. The EMA's failure to notice GSK's error in calculating the number of sudden deaths per day predicted to be expected by chance as three times too high [54] instead of what it should be [18] is addressed. The population to a reasonable approximation for these purposes is not 54.7 million doses but 54.7m doses / 3 administered per child.

On 2015 Feb 03, Clifford Miller commented:

None

On 2015 Feb 06, Clifford Miller commented:

Dear Dr Ferenci,

Thank you. I am not repeating what you said. My comments are in the context of my overall comments to which I made express reference here:

http://www.ncbi.nlm.nih.gov/pubmed/24004825#cm24004825_8956

Perhaps you might like to summarise your responses to all the observations made in the context in which they were made. By such means we can see what is common ground.

On 2015 Feb 05, Tamás Ferenci commented:

Dear Dr. Clifford,

I believe you are practically repeating, almost literally, what I said in my very first reply. Let me quote myself:

[S]trictly speaking "all of which can result in an SIDS" is only true if these events are independent, which might not be the case, but assuming that such event can only and exclusively occur after the first vaccination (and the probability at the further vaccinations is zero, conditional on surviving the first), which would give rise to your calculation, is no less irrealistic in my opinion.

Thus, my conclusion is unchanged: Nevertheless, I agree with you that this issue would have worthed at least a discussion in the PSUR, it'd have been elegant to discuss it, but at this point, I don't see that it is "plain wrong", as suggested by your comment.

Let me also add that even if you are correct that most deaths happened after the first dose, this is still not a conclusive evidence per se: SIDS has a decreasing age-specific incidence curve at this age range, so higher dose repetition numbers coincide with higher age which is in turn associated with lower risk itself. I.e. these two are confounded.

On 2015 Feb 05, Clifford Miller commented:

Dear Dr Ferenci,

Thank you. If one assumes an equal probability of death per dose then exposure is more relevant. If death is more likely on the first dose then the population is more relevant.

See also my comment above: http://www.ncbi.nlm.nih.gov/pubmed/24004825#cm24004825_8956

GSK's 54 expected deaths figure is based on an equal likelihood on each exposure. This ignores the likelihood of death on the first dose. The data GSK provided to the EMA appears misleading. The figure for deaths expected by chance should be much much closer to 18 than to 54.

GSK's individual case report data in PSUR's 15 and 16 shows the following distribution of deaths for those reports which included the information:

7 @ 2 months, 8 @ 3 months, 1 @ 4 months, 2 @ 5 months, 1 @ 6 months 1 @ 11 months.

Some of the deaths aged 3 months may be first dose vaccinations given at 2 months or could also be late first doses at three months. The age at vaccination is not given.

The interval between vaccination and death for these deaths was between 0 and up to 14 days [with one at 24 days].

The EMA SPC dosage schedule for these ages states:

The primary vaccination schedule consists of three doses of 0.5 ml (such as 2, 3, 4 months; 3, 4, 5 months; 2, 4, 6 months) or two doses (such as 3, 5 months). There should be an interval of at least 1 month between doses.

The Expanded Program on Immunisation schedule (at 6, 10, 14 weeks of age) may only be used if a dose of hepatitis B vaccine has been given at birth.

On 2015 Feb 05, Tamás Ferenci commented:

Dear Dr. Miller,

cited in your comment 54 million as the population figure when the maximum upper limit is 18 million to a good approximation.

Like I have discussed in my comment, the question is not the size of population, but the exposure. These are different concepts; this was just the main point of my discussion.

On 2015 Feb 04, Clifford Miller commented:

Dr Ferenci,

Thank you for your response.

GSK and the EMA appear to have made the issue of an Observed/Expected analysis central to the matter. That appears the main point - what to a reasonable approximation is the Expected figure to compare to the Observed 16 real spontaneous reports of real deaths of real children occurring on Day 0 [the day of vaccination].

The correction required to the approach used by GSK is to use a realistic figure to a good approximation for the maximum population.

At the moment the position with that correction appears to be 18[E]:16[O] to a good approximation for these purposes [albeit without yet making a correction for underreporting].

I put the issue of the population to you because your comment states you are a senior lecturer in biostatistics and because of course you chose to comment on the matter and cited in your comment 54 million as the population figure when the maximum upper limit is 18 million to a good approximation.

As for your other points, in the light of the foregoing, in my view it is the GSK O/E analysis which needs to be addressed - all else at this time being surplusage.

It is of course open to any of the authors or others who have commented who also used the figure of 54 million as representing the size of the population to comment.

On 2015 Feb 04, Tamás Ferenci commented:

Dear Dr. Miller,

Thanks for your remark.

Let me note, however (as you submitted your comment as a reply to mine), that my 2nd comment and the second half of my 1st comment is in no way dependent on the size of the background population, so they remain completely intact, even if your criticism is correct. The first half of my first comment indeed depends on the background size, but - as I have pointed out - the discrepancy is in excess to two magnitudes, so a factor of 3, even if you are correct, doesn't affect qualitatively my conclusion.

As a side note, I also can't completely agree with your logic. You are correct that this way, the same child is counted several times in the background population, but don't forget that the same child - save for those who die, but their number is of course negligible even compared to 18 million - is also exposed several times! (All of which can result in an SIDS and those results are counted together in Table 36.) Well, strictly speaking "all of which can result in an SIDS" is only true if these events are independent, which might not be the case, but assuming that such event can only and exclusively occur after the first vaccination (and the probability at the further vaccinations is zero, conditional on surviving the first), which would give rise to your calculation, is no less irrealistic in my opinion.

Nevertheless, I agree with you that this issue would have worthed at least a discussion in the PSUR, it'd have been elegant to discuss it, but at this point, I don't see that it is "plain wrong", as suggested by your comment.

On 2015 Feb 03, Clifford Miller commented:

Dr Ferenci,

The number of daily sudden deaths to be expected by chance is just in excess of 18 and not the number GSK reported to the EMA. One must not equate the number of doses sold [54.7 million] with the size of the population. The maximum vaccinated population is 18 million.

This means the number of sudden deaths predicted by chance using GSK's proposed annual rate of .454 per 1000 and healthy vaccinee factor of 0.8 is 18.

To that you must compare the number reported in spontaneous reports. That number according to GSK is 16 dead children, [and that is without correcting for underreporting].

Of the number of doses sold GSK estimate the number used for Year 1 is 54.7 million. Each child historically was to receive three doses according to the EMA Schedule. The authors of this paper suggest a 4 dose schedule is being adopted so 18 million is an upper boundary and that ignores over-vaccination, spoils and other wastage.

It is therefore a little troubling that the report to the regulator was so far in error and that the EMA appears to have failed to have noticed.

On 2015 Feb 02, Tamás Ferenci commented:

Dr. Puliyel’s comment raises important questions about the time clustering of adverse events observed in passive vaccine safety data, i.e. the pattern of temporal association of adverse events with vaccination – which is the only thing that can be investigated using such data –, however his approach neglects an important aspect thus leading to unfounded conclusions in my opinion.

The major issue was raised by Dr. Franco, but let me add two further remarks.

1) While it is obviously clear for everyone that we will never be able to surely tell the exact role of reporting bias (and thus the real effect of the vaccine on SIDS, if there is any), there are two points that worth mentioning in my opinion, which were not raised by Dr. Franco:

• The fact that Dr. Puliyel’s calculation is flawed can be simply demonstrated using his own data. Let’s have a look at the method where he calculated excess deaths using “the second 10-day-window-period as the baseline SIDS rate”. Using the data from the <1 year old, his method would result in 2 deaths in 10 days, which means 73 deaths in a year (assuming linear rate within the first life-year, as in the PSUR), which means – using a background population of the size of 54.7 million – an SIDS rate of 0.00133 per 1000 which is two magnitudes (!) smaller than what is actually reported in the literature. As SIDS rate simply can’t be that low, we can conclude that Dr. Puliyel’s assertion on ascertainment bias “not playing a major role” is definitely wrong.
• In his second comment, Dr. Puliyel referred to the fact that there is a substantial drop even after the first three days. Although at first glance it is tempting to agree with Dr. Puliyel that “[i]t is difficult to imagine that reporting bias is responsible for this big a change, in so short a time”, actual data shows otherwise. While I have not compiled a comprehensive statistics, it is immediately obvious from 3A appendices (pp. 301-522, pp. 857-1064) that no matter which disease-group we look at, the vast majority of spontaneous reports with known time are definitely coming from the first few days! And these can be used for comparison, because 3A also only includes – by definition – serious events. Now either the vaccine is causing everything from “Blood and lymphatic system disorders” to “Vascular disorders” (which is perhaps not something that Dr. Puliyel suggests…) or there is in fact a dramatic drop in reporting rate just after a few days.

2) Finally, let me note that I have a feeling that Dr. Puliyel misunderstands the applicability of passive data. Due to the inherent bias outlined above, such data simply can not be used alone to make conclusions on causality. Rather, their aim – among others – is to detect “suspicious” cases, which can be then specifically investigated with appropriately designed active vaccine safety methods, which are capable – as opposed to what we can do from passive data – to draw causal conclusions. There is no point in claiming that by applying “better” methods, we detected causality from passive data, because this is simply impossible, the only thing that can be meaningfully asked for if we detect something suspicious (using any method, including Dr. Puliyel’s) is to perform an active study. But these have been conducted (as pointed out by Dr. Franco)! Now Dr. Puliyel either accepts their results, or questions their methodology (which is a separate issue), the only thing he can’t do is to question the results of an active study based on passive data.

Conflict of interest: None.

Tamás Ferenci PhD

Senior lecturer (biostatistics), Óbuda University, Budapest, Hungary

John von Neumann Faculty of Informatics, Physiological Controls Group

On 2015 Jan 22, Jacob Puliyel commented:

I thank the authors for their response to my comment.

I was presuming that in the countries from where this data was gathered, sudden infant death or SIDS is considered 'unnatural death'. If that is so, these deaths will have been investigated by a competent forensic team and the immunization records will have been examined to check if the infant was up to date with its vaccinations or whether there was an element of neglect. Reporting bias (based on parents perception that vaccine was the trigger for events that lead to the death of their child) would have little or no role under these circumstances.

The authors quote from the 'Guidelines for good pharmacovigilance practices'; that events that are expected, common and mild, or occur late after vaccination, are less likely to be reported. That is not applicable here, as SIDS is completely unexpected and a catastrophic event.

Further, the analysis in Table 2 of the linked article http://jacob.puliyel.com/paper.php?id=345 (Please download pdf version) shows that there were 42 deaths in the first 3 days and only 16 in the next 3 days. It is difficult to imagine that reporting bias is responsible for this big a change, in so short a time.

We will need to find a more plausible explanation. Otherwise we have to accept that the deaths were caused by the vaccine and the diagnosis of SIDS was wrong.

Jacob Puliyel

On 2015 Jan 21, Elisabetta Franco commented:

Dr Puliyel’s analysis uses the period of 10-19 days post-vaccination as a control for the period of 0-9 days post-vaccination to determine whether there is an excess of Sudden Infant Deaths (SIDS) in the first ten days following administration of Infanrix-hexa. The opinion of all the Authors is that the suggested imbalance in reported SIDS between 0-9 days and 10-19 days periods represents a well recognised bias in spontaneous report reporting, where the shorter the time that has elapsed between the vaccination procedure and the event, the more likely it is to be perceived as a trigger and subsequently be reported. Conversely, events that are expected, common and mild, or occur late after vaccination, are less likely to be reported [1]. Many studies have demonstrated an absence of causal association between vaccination and SIDS [2,3]. Post marketing data are shared on a regular basis with regulatory authorities worldwide [1,4], who support this position [2,3].

1. Guideline on good pharmacovigilance practices (GVP) Product- or Population-Specific Considerations I: Vaccines for prophylaxis against infectious diseases (9 December 2013) (OE analyses section) http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2013/12/WC500157839.pdf [Accessed on 13JAN2015])
2. World Health Organization http://www.who.int/features/qa/84/en/
3. Center for Disease Control and prevention, Atlanta, USA http://www.cdc.gov/vaccinesafety/Concerns/sids.html
4. ENCePP Guide on Methodological Standards in Pharmacoepidemiology, http://www.encepp.eu/standards_and_guidances/methodologicalGuide9_2.shtml

On 2015 Jan 19, Jacob Puliyel commented:

Apropos the earlier posting there are a couple of other facts that we must consider when looking at the incidence of sudden unexplained deaths immediately following vaccination with Infanrix.

a) The safety assessment document has used the number of doses of vaccine distributed as the denominator. The report acknowledges that all the doses of the vaccine distributed, need not have been utilized.

There can be another argument against using this denominator. As each child is given up to 5 doses (https://www.gsksource.com/gskprm/htdocs/documents/INFANRIX.PDF) and they could die after any one of the doses (and you can die only once), perhaps it would be more appropriate to look at the number of deaths against the number of babies vaccinated (rather than the number of units of vaccine distributed). The appropriate denominator would be about one fifth the denominator used in the report.

b) Appendix 5A in the document sent to the regulator gives the International Event Report in 13 fatal cases. It can be seen in this sample that there were more deaths after the first dose than after the second and more after the second than after the third dose. This is a pattern seen with adverse events following immunization (AEFI) that are causatively related.

c) In May 2005, Zinka and colleagues have reported six cases of sudden infant deaths caused by another hexavalent vaccine (similar to Infanrix), called Hexavac Zinka B, 2006. Marketing authorization in the European Union was withdrawn in August 2005 (Doc.Ref.EMEA/207369/2005).

d) The CIOMS /WHO have revised the widely used Brighton Protocol for assessment of AEFI. The new scheme facilitates misclassification of vaccine related deaths as [Not an AEFI] and this has been discussed on PubMed Commons earlier. (http://www.ncbi.nlm.nih.gov/pubmed/19061929 ) (http://www.ncbi.nlm.nih.gov/pubmed/23452584 ) (http://www.ncbi.nlm.nih.gov/pubmed/24021304 ).

e) In some ways the deaths with Infanrix is similar to deaths seen with the use in Asia of Pentavalent vaccine against 5 disease ( DPT, hepatitis B, Hib) Puliyel J, 2013. Some of these deaths have been investigated by the WHO using this revised method and the vaccine had been declared safe. http://www.who.int/vaccine_safety/committee/topics/hpv/GACVSstatement_pentavalent_June2013.pdf

f) The deaths are completely unnecessary as the vaccines could have been given separately, and separately they have a long track record of safety. One hopes that the findings will result in an honest assessment of the harms being done by these new combined vaccines.

Conclusion

As mentioned earlier there is nothing sacrosanct about the original Brighton Classification (http://www.who.int/vaccine_safety/publications/AEFI_aide_memoire.pdf) but one has to evaluate the two schemes (Brighton vs CIOMS) from the point of view of patient safety to see which scheme would react to rare vaccine related adverse reaction signals early. “The causality scheme that insists on calling all reactions as ‘indeterminate’ or ‘inconsistent/coincidental’ just because they were not noticed in the original small clinical trials, undermines the very raison d'être of post marketing surveillance. Patient safety (meaning protecting patients) rather than vaccine safety (protecting vaccines) should be more important.”

On 2015 Jan 13, Jacob Puliyel commented:

Baldo and colleagues quote 2 references to suggest that in Germany, a population-based evaluation demonstrated a possible safety signal for DTPa-HBV-IPV-Hib-SP but failed to show an imbalance between observed and expected SUD cases for DTPa-HBV-IPV/Hib von Kries R, 2005 von Kries R, 2006. However this seems to be contradicted by the data that was submitted by the manufacturer to the regulatory authority and the analysis below.

The GlaxoSmithKline Biological Clinical Safety and Pharmacovigilance’s confidential report to the Regulatory Authority on Infanrix hexa (combined Diptheria Tetanus and Acelluar Pertusis, Hepatitis B, inactivated Poliomyelitis and Haemophilus influenza type B vaccine for the period 23 October 2009 to 22 October 2011 (the 15th and 16th Periodic Safety Update Report (PSUR)) has been made available to the public by the Italian Court of Justice Nicola Di Leo and is now available on the internet (http://autismoevaccini.files.wordpress.com/2012/12/vaccin-dc3a9cc3a8s.pdf)

Section 9.3.1.1 on pages 246-249 documents an evaluation of whether the number of ‘sudden deaths’ reported, exceeded the number one could expect to occur by coincidence - that is from the natural background incidence of sudden death. The background incidence of 0.454/1000 live births in the first year and 0.062/1000 live births is used, with a healthy vaccine correlation factor of 0.8 applied. Table 36 on page 249 tabulates the number of sudden death that would be expected to occur by chance within a range of days post vaccination.

Table 1 Cumulative number of observed and expected cases of Sudden Death following Infanrix hexa in children in their first or second year of life

This is available here: http://jacob.puliyel.com/paper.php?id=345 (Please download pdf version)

( Source: Table 36 The GlaxoSmithKline Biological Clinical Safety and Pharmacovigilance report to Regulatory Authority )

According to this analysis, the number of sudden death cases reported after vaccination with Infantrix hexa is below the number of cases expected in children in the first year of life. It is equal or below the number of cases expected in children in the 2nd year of life.

However if one analyses the data looking at deaths in first 10 days after administration of vaccine and compares it to the deaths in the next 10 days, it is clear that 97% of deaths (65 deaths) in the infants below 1 year, occur in the first 10 days and 3% (2 deaths) occur in the next 10 days. Had the deaths been coincidental SIDS deaths unrelated to vaccination, the numbers of deaths in the two 10 day periods should have been the same.

Similarly in children older than 1 year, 87.5% deaths (7 deaths) occurred in the first 10 days and 12.5% (1 death) occurred in the next 10 days.

If we consider the number of deaths in the second 10-day-window-period as the baseline SIDS rate in these healthy children coming for immunization, we can see that there was an excess of 63 (65 – 2 = 63) deaths in the first year and excess of 6 deaths (7 – 1 = 6) among those vaccinated between 1 and 2 years.

In the reporting period, one must conclude that Infanrix hexa vaccine could have been responsible for at least 69 deaths.These are all deaths within a small window period (of 3 weeks) after a catastrophic event which has been investigated thoroughly (forensic investigation of sudden unexpected deaths - SIDS/SUDS), therefor ascertainment bias is unlikely to have played a major role.

Table 2 The daily increment in Sudden Death following Infanrix hexa in children ' is tabulated and made available here: http://jacob.puliyel.com/paper.php?id=345 (Please download pdf version)

The decelerating incremental-deaths further supports the contention that there is a clear relationship of ‘sudden death’ to the vaccination episode. 42 deaths had taken place in the first three days after vaccination, 16 deaths in the next 3 days between day 3 and day 5, 3 deaths between day 6 and day 8, 2 deaths between day 9 and day 11, and there were only 2 deaths in all of the remaining 10 days. The fact that rate of deaths decreases rapidly and continuously as time elapses after immunization, makes it clear that the deaths are related to the vaccination episode.

This is being posted on PubMed Commons to put it up for open review by the scientific community, on account of its urgency, as this is a matter that involves the lives of children and there is a continuing risk to children.

As the authors of this article are best qualified to peer review this submission, I am inviting each of the authors castrom@wustl.edu paolo.bonanni@unifi.it mclaudia@fei.edu.br giovanni.gabutti@unife.it franco@med.uniroma2.it fem75838@gsk.com r.prato@unifg.it fvitale@igiene.unipa.it to review it and to post their review on PubMed Commons.

Jacob Puliyel MD MRCP M Phil

puliyel@gmail.com

On 2013 Nov 04, Allison Stelling commented:

This was a good read. The authors do a good job going over the present body of literature about using Raman and IR for medical diagnostics. I particularly liked the fact that they defined "sensitivity" and "specificity" in their Introduction, and kept the statistics and processing algorithms reasonably straightforward in their analysis. I also admire the fact that they used two different spectral methods (florescence and Raman spectroscopy) to investigate the tissue; combining the two increases the likelihood of accurate and reliable diagnostic results.

I wonder, though, if it would be more effective to individualize the diagnosis even further- that is, take a background spectra on a "healthy" section, and take a huge number of acquisitions. The disease phenotype might pop out in the difference spectra as the instrument scans over the tissue area. (More likely, many things will. But, you might be able to train it on the disease's signature, and detect it within the subtraction spectra.) This could possibly avert the issue of training sets with misclassified (misdiagnosed) spectra in the training set for "healthy" (or vice versa). With tumors, there can be quite of lot of inter-individual variance within different tumor classifications and subtypes. Raman could really help with more tailored, individualized diagnostics.

On 2014 Jan 27, William Hollingworth commented:

I'd like to reinforce Dr Coyne's point about the advantages of PubMed Commons over the much slower, traditional method of communication still used by journals like the Journal of Clinical Oncology.

5th September 2013: Our online paper and the accompanying editorial were published on the JCO website. The editorial, which we had not previously seen, was quite critical and contained several points that we wanted to respond to.

10th Sept 2013: We submitted our letter of response to JCO. After a couple of enquiries, I was told that our letter couldn't be published for several months.

17th Dec 2013: Our letter was accepted.

14th Jan 2014: Proofs, conflict of interest, authorship statement for the letter received and returned.

I'm still not sure when our letter will appear in the journal or on its website.

The 4+ month delay clearly stifles debate and favours the editorialist (who has immediate right of reply) over the authors (who have to wait). Next time I'll respond through PubMed Commons.

On 2013 Nov 14, James C Coyne commented:

This is an exceptionally transparent report of a clinical trial that was intended to improve cancer patients' level of distress by introducing routine screening. The results were that screen patients did not have lower levels of distress and did not appreciably increase their use of specialized psychosocial and mental health services. Cost data suggest that it took about $28 to screen one patient, the screening was not cost-effective.

This kind of data is sorely needed to evaluate implementation of screening versus other possible uses of the same resources. Unfortunately, when this article came out in Journal of Clincal Oncology, it was accompanied by a negative editorial commentary. Apparently the authors of the study had no forewarning or opportunity to respond. Moreover, this article is behind a pay wall, but the attack on it in the same journal is freely available.

Here's the attack on it Carlson LE, 2013 and here's a link to my blog post <http://blogs.plos.org/mindthebrain/2013/11/08/wheres-the-evidence-that-screening-for-distress-benefits-cancer-patients/

discussing all the implications of such a use use of invited commentaries by advocacy groups to discredit negative findings would contradict their claims of benefit from accepting their practice recommendations. It's good that we have PubMed Commons so that such invited commentaries do not become the last word in evaluating studies.

On 2013 Nov 14, James C Coyne commented:

Although not identified as such in PubMed, this article is an invited commentary on another article Hollingworth W, 2013.

The targeted article involved a reasonably conducted randomized trial that found that implementing routine screening for distress failed to reduce the distress of cancer patients and only minimally increased referrals to specialty psychosocial and mental health services. The article also concluded that screening was not cost-effective.

There is a paucity of such data available, even though crucial to evaluating the value of implementing screening versus alternative uses of resources. See http://blogs.plos.org/mindthebrain/2013/11/08/wheres-the-evidence-that-screening-for-distress-benefits-cancer-patients/

The commentary is quite negative, unfairly so, especially because the authors of the targeted article were not forewarned or given a chance to respond. The author of the commentary is a key proponent of routine screening for distress and took the occasion of an invited commentary to trash negative findings from a relatively well done study.

The commentary represents a post publication enforcement of the confirmatory bias generally required for screening articles to be published. The targeted article nonetheless got through peer review, but obviously the author of the invited commentary was forewarned and given an opportunity to neutralize its impact.

Eight of the 16 citations are to the author or a close collaborator’s work. Many do not present relevant data was seem relevant at all. I would consider some of them gratuitous self citations. And others seem to represent simply advocacy pieces, that are not evidence based.

Although this commentary appears in a paywalled journal, it can be freely accessed, whereas the targeted article is securely behind a paywall. This substantially adds to the unfairness of this commentary. You can readily access the commentary from PubMed, but cannot directly access the article that it harshly criticizes.

I have commented more extensively on this invited commentary and the target article in a PLOS Mind the Brain blog post < http://blogs.plos.org/mindthebrain/2013/11/13/2127/> The publishing of this invited commentary demonstrates a failure of prepublication peer review of the kind that post publication comments in PubMed Commons can remedy.

On 2015 Oct 05, Siddharudha Shivalli commented:

I read this article with a great interest. Authors’ efforts are praiseworthy. It highlights the key factors associated with the risk of malaria in the study area and provides evidence for fine tuning of malaria control activities. However, following issues need to be addressed.

The prevalence of malaria should have been reported with 95% confidence intervals (n=83/1084, 7.7%; 95% CI: 6.2-9.4). Authors have mentioned in the abstract that the multivariate logistic regression analysis was used to compare the factors associated with malaria in pregnant women. However, the same is missing in ‘Data analysis’ part of methods. Moreover, authors mention that after adjusting for possible confounders, the use of insecticide spray (p<0.001) and young maternal age (p = 0.020) were the main factors associated with a reduced and an increased risk of malaria infection among pregnant women in Lagos, respectively [Table 5]. It is advisable to explicitly mention all the confounders used in the regression model to avoid ambiguity. Although the study sample was large (n=1084), a word about R2 (explaining the variance in the risk of malaria) of the applied regression model would have been more affirmative. Although bed net, ITN and Insecticide sprays are the major preventive measures, others like avoiding water logging and clean surroundings, proper covering of stored water, screening of the houses with wire mesh, clothes covering maximum body surface etc. are overlooked in this study.

None the less, I must congratulate the authors for investigating an important public health problem in the study area.

Competing interests

The author declares that there is no conflict of interest about this publication.

On 2013 Nov 30, GianCarlo Panzica commented:

A previous study in the same rat model, demonstrated that also the nNOS system is altered in Tfm males, suggesting that also this system is depending by androgens for its full differentiation Martini M, 2008.

On 2014 Jan 02, Tom Kindlon commented:

Two letters were published in reply to this:

Two letters were published in reply to this piece. One is mentioned above, "What's the problem with sharing research committee's discussions?"

Then there is also my letter: BMJ. 2013 Sep 25;347:f5731. doi: 10.1136/bmj.f5731. "People want to learn as much as possible from the PACE trial for chronic fatigue syndrome" Kindlon T. Kindlon T, 2013

This second letter isn't free online. But it's just a slightly shortened version of an e-letter which can be read for free at: http://www.bmj.com/content/347/bmj.f5355/rr/659900 .

Following a response from the PACE Trial authors, I justified and expanded on my points in these two e-letters: (i) "Author's response: Criticisms of the PACE Trial were justified" http://www.bmj.com/content/347/bmj.f5963/rr/667107 (ii) "PACE trial: Simply giving a reason why an outcome measure was changed is not necessarily sufficient" http://www.bmj.com/content/347/bmj.f5963/rr/670755

On 2013 Oct 29, John Cannell commented:

Both isoforms of tryptophan hydroxylase are directly regulated by calcitriol and both isoforms have a vitamin D response element on their genes. Vitamin D down-regulates the peripheral hydroxylase and up-regulates the central tryptophan hydroxylase.

Wang, T. T. et al. Large-scale in silico and microarray-based identification of direct 1,25-dihydroxyvitamin D3 target genes. Mol Endocrinol 19, 2685-2695, doi:10.1210/me.2005-0106 (2005) Wang TT, 2005

Autistic children with vitamin D deficiency have high peripheral serotonin and low central serotonin and thus low central melatonin as they do not have the central serotonin necessary to make melatonin.

Thus the vitamin D theory of autism (vitamin D deficiency is the environmental risk factor for this highly heritable disorder) is consistent with the authors weak findings. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with autism. Two of the studies below (Mostafa et al and Gong et al) also found autism severity, as rated on standard autism rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with autism severity.

Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

Furthermore, the vitamin D theory of autism explains many of the epidemiological facts of autism.

Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day.

Cannell JJ. Autism, will vitamin D treat core symptoms? Medical Hypotheses. 2013 Aug;81(2):195-8. Cannell JJ, 2013

Some autism researchers seem cognizant of the entire body of autism research. For example, a group of well-known European autism researchers, including Professor Christopher Gillberg of the Gillberg Neuropsychiatric Institute, have recently called for the need for “urgent research” into vitamin D and autism.

Kočovská E, Fernell E, Billstedt E, Minnis H, Gillberg C. Vitamin D and autism: clinical review. Res Dev Disabil. 2012 Sep-Oct;33(5):1541-50. doi: 10.1016/j.ridd.2012.02.015. Epub 2012 Apr 21.Kočovská E, 2012

However, these scientists appear to be in the minority. Until all autism researchers become cognizant of the wider body of autism research, we will continue to wonder how to prevent - and perhaps even treat - this modern day plague.

John J Cannell, MD Vitamin D Council http://www.vitamindcouncil.org

On 2014 Jan 08, Brett Snodgrass commented:

Dear Authors,

Thank you for the excellent article.

Please provide your kind attention to the distinction between the Thebesian veins and the vessels of Wearn.

http://bit.ly/JTWearn

http://bit.ly/vasaThebesii

For additional commentary, please see

https://twitter.com/BrettSnodgrass1/status/417440058648428544

Comments and suggestions are welcome.

Thank you very much.

On 2013 Oct 31, John Cannell commented:

The authors reported that immune system dysregulation is common in autism spectrum disorder (ASD). Vitamin D deficiency produces very similar immune dysregulation.

Prietl B, 2013

Kamen DL, 2010

Yang CY, 2013

Baeke F, 2010

Thus the vitamin D theory of ASD (vitamin D deficiency being the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with ASD. Two of the studies below (Mostafa et al and Gong et al) also found ASD severity, as rated on standard ASD rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with ASD severity.

Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

Eyles DW, Burne TH, McGrath JJ. Vitamin D, effects on brain development, adult brain function and the links between low levels of vitamin D and neuropsychiatric disease. Front Neuroendocrinol. 2013 Jan;34(1):47-64. doi: 10.1016/j.yfrne.2012.07.001. Epub 2012 Jul 11. Review. Eyles DW, 2013

Furthermore, the vitamin D theory of autism explains most of the epidemiological facts of ASD.

Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day and few toddlers or pregnant women get any sunshine due to the sun scare. As vitamin D fortified milk consumption and sun exposure has declined, so have toddlers and pregnant women’s vitamin D levels. The dramatic increase in the incidence of ASD occurred during the same time vitamin D levels were falling in toddlers and pregnant women.

Cannell JJ. Autism, will vitamin D treat core symptoms? Medical Hypotheses. 2013 Aug;81(2):195-8. Cannell JJ, 2013

Some autism researchers seem cognizant of the entire body of autism research. For example, a group of well-known European ASD researchers, including Professor Christopher Gillberg of the Gillberg Neuropsychiatric Institute, have recently called for the need for “urgent research” into the vitamin D deficiency theory of ASD.

Kočovská E, Fernell E, Billstedt E, Minnis H, Gillberg C. Vitamin D and autism: clinical review. Res Dev Disabil. 2012 Sep-Oct;33(5):1541-50. doi: 10.1016/j.ridd.2012.02.015. Epub 2012 Apr 21.Kočovská E, 2012

Until all autism researchers become cognizant of the wider body of scientific research, we will continue to wonder how to prevent - and perhaps even treat - this modern day plague.

John J Cannell, MD

Vitamin D Council

http://www.vitamindcouncil.org

On 2017 Oct 11, Bhaskar Chandra Mohan Ramisetty commented:

Does not seem like there is any useful information from this paper. The authors are apparently bold enough to correct their work!!! Good job. Nasty Prophages and the Dynamics of Antibiotic-Tolerant Persister Cells. https://www.biorxiv.org/content/early/2017/10/09/200477.1

On 2016 Feb 29, Bhaskar Chandra Mohan Ramisetty commented:

http://biorxiv.org/content/early/2015/07/02/021162 http://journal.frontiersin.org/article/10.3389/fmicb.2016.01882/full

A biorxiv article with contradictory results. Regulation of yefM/yoeB TA system is independent of inorganic polyphosphate as well as ppGpp.

On 2014 Feb 19, james brophy commented:

Prompt revascularization of the culprit lesion with percutaneous coronary interventions (PCI) is a cornerstone in the treatment of acute myocardial infarction (STEMI). Numerous previous studies have suggested that simultaneous additional interventions of other non-culprit is at best unnecessary and at worst potentially dangerous. However this study that compared simultaneous ‘preventive angioplasty’ of non-infarct-related coronary arteries with ≥50% stenosis with primary PCI alone (with optimal medical treatment) found the composite endpoint of cardiac death, nonfatal myocardial infarction, or refractory angina was reduced by a staggering 65% (HR=0.35; 95% CI: 0.21-0.58, p<0.001). Is this result believable?

First, despite a very slow recruitment period of several years, the trial was prematurely stopped. Premature trial discontinuations for benefits are well known to overestimate treatment effects. This is especially problematic in this small unblinded study with only 16 excess 'hard' events and no formal statistical stopping rule described in their study protocol. The strongly positive results in prematurely stopped small trials are often not confirmed in bigger follow-up studies underlining the important role of chance that arises with repeated looks at the data. Moreover it has been shown that these small prematurely stopped trials have an increased likelihood of being published in high profile journals reinforcing this tendency to early stopping, as in the present case. Second, can medical treatment really be considered optimal in the control group when, despite STEMI and multi-vessel disease patients were discharged in less than 2 days without ischemic testing, the current standard of care (if additional angioplasty has not been performed during the original hospitalization). It seems only 1/3 of patients ever got any ischemic testing and this occurred only several weeks after the acute event, perhaps to late to influence potentially avoidable outcomes. Consequently was the “preventive” up front PCI group not being compared to an inferior "straw man" comparator? Third given the unblinded nature, could not the knowledge of untreated lesions have encouraged a detection bias in the search for clinical outcomes.

In an accompanying editorial, it was proposed that these additional interventions helped to pacify the inflamed coronary vasculature. However this argument seems specious as the coronary vasculature is diffusely and not locally inflamed. The biases discussed above seem a more likely explanation for this large and unexpected effect size.

On 2013 Sep 26, Carl Heneghan commented:

We wrote about all sorts of sports intervention in the BMJ last year and bare foot running was one of the interventions we looked. The evidence underpinning sports performance products: a systematic assessment.

Heneghan C, Howick J, O'Neill B, Gill PJ, Lasserson DS, Cohen D, Davis R, Ward A, Smith A, Jones G, Thompson M. BMJ Open. 2012 Jul 18;2(4). doi:pii: e001702. 10.1136/bmjopen-2012-001702. Print 2012. PMID: 22815461

Seems whilst there is lots of biomechanical evidence, as pointed out in the article, there is no actual clinical performance evidence that could aid the decision as to whether to use these shoes.

On 2017 Oct 18, Eric Lock commented:

None

On 2017 Oct 18, Eric Lock commented:

The software URL is yet again broken. Instead see

http://ericfrazerlock.com/Software.html , or https://github.com/lockEF/bayesCC

On 2015 Sep 03, Kenneth Daily commented:

Software URL broken - currently is:

http://www.tc.umn.edu/~elock/Software.html

On 2014 Jan 17, Amanda Capes-Davis commented:

A note regarding the tissue studied here: KB is not an epidermoid carcinoma cell line. The KB cell line is known to be cross-contaminated and is actually HeLa, a cervical adenocarcinoma cell line. For a database of cross-contaminated or otherwise misidentified cell lines, see http://iclac.org/databases/cross-contaminations/.

On 2013 Dec 30, Ben A Inglis commented:

It seems to me that although the intent was to assess connectivity induced by reading a novel, in the absence of a control task there is no way to know whether the changes were due to the specific act of reading or due simply to the subjects' being engaged in a structured task over the study period. Surely, to be confident that the changes are due to reading, a second group of subjects should have been exposed to a control task that was as similar as possible to the novel reading. For example, control subjects could have been instructed to watch a dramatic TV mini-series, with each evening's exercise lasting approximately the same time as the reading. (Questioning of control subjects could have verified that the task was completed as instructed, in precisely the same manner as the test subjects had their reading task assessed.) An even better control would have been to use the same story but change the medium. For instance, the test subjects might have read the story while the control subjects listened to it on an audio book. Perhaps there is even need for a second control group; subjects are set a task to attend to each night, but there is no plot to follow. In sum, without assessing directly the effects of a structured attention task over the study period there is no way to be sure that reading per se is causing the connectivity changes.

On 2015 Jan 30, Peter Gøtzsche commented:

This meta-analysis was fatally flawed

Based on FDA trial data, Arif Khan et al. report that antipsychotic drugs lower total mortality in schizophrenia by more than 50% and that the drugs also lower suicides (1). These results agree very poorly with the fact that people with schizophrenia live about 20 years less than other people while almost all of them receive antipsychotics; that many experience excessive weight gains and diabetes because of the antipsychotics, which shorten their life substantially; and that a meta-analysis of old people found that double as many died when they got antipsychotics than when they got placebo (2).

It is difficult to understand how Khan, who has been principal investigator of more than 340 clinical trials sponsored by more than 65 pharmaceutical companies and 30 contract research organizations (1), can publish a meta-analysis that is so intensely misleading as this one (1). The fatal flaw in their analysis is that the authors used person-years instead of using persons. As pointed out in a letter to the editor, a person-year is not just a person-year (3). The average duration of placebo exposure was very short, only 33 days, as compared to 132 days on drug (1). Khan et al. seem to have included not only the double-blind phases of the trials but also safety extension studies (in which patients only receive active drug of course). Such analyses are notoriously unreliable, as those who continue on active drug are those who tolerate it. We need to look at deaths in relation to number of randomised patients, and then we can see that antipsychotics kill people, which we knew beforehand. The relative risk is 1.65, i.e. a 65% increase in total mortality on drug compared with placebo, and for suicides, the relative risk is 2.83.

Conflicts of interest: none.

1 Khan A, Faucett J, Morrison S, et al. Comparative mortality risk in adult patients with schizophrenia, depression, bipolar disorder, anxiety disorders, and attention-deficit/hyperactivity disorder participating in psychopharmacology clinical trials. JAMA Psychiatry 2013;70:1091-9.

2 Schneider LS, Dagerman KS, Insel P. Risk of death with atypical antipsychotic drug treatment for dementia: meta-analysis of randomized placebo-controlled trials. JAMA 2005;294:934–43.

3 Nordentoft M, Laursen TM. Was Risk of Suicide Underestimated? JAMA Psychiatry 2014;71:716.

On 2014 Oct 26, Nicholas Rosenlicht commented:

In evaluating the results of this trial it is important to note that the published results do not correspond to the primary outcomes specified in the trial’s original and updated registrations on ClinicalTrials.gov. The four primary outcome measures initially registered (10/7/2008) were: MADRS at 40 minutes, 120 minutes, 24 hours, and 7 days. These were expanded on 1/12/11 to include the MADRS at 240 minutes, 48 hours, 72 hours, biweekly for up to 4 weeks, and early termination. After publication (1/30/14) all Primary Outcomes except MADRS at 24 hours were removed from the ClincalTrials.gov registration. These changes can be tracked at: http://clinicaltrials.gov/archive/NCT00768430 It would be important to understand why the authors changed the outcome measures several times during the trial. These changes are not mentioned in the publication. The finding that ketamine, a dissociative anesthetic that is abused for its euphoric and other mind-altering properties, transiently suppresses MADRS scores is not surprising. It would be much more important clinically to demonstrate significant effects on the outcome measures at 2 to 4 weeks. These were not presented.

On 2013 Nov 01, Natalie Clairoux commented:

The submitted version of the manuscript is freely available here: https://papyrus.bib.umontreal.ca/xmlui/handle/1866/9023

On 2014 Apr 10, Alexander Klabnik commented:

I recomend as a collaborator

On 2014 Feb 04, Jean-Jacques Letesson commented:

In the bacteria and plasmid section of this paper, the readers should be aware that it is impossible to grow B. melitensis in the minimal medium stated "B. melitensis 16 M was routinely cultured in rich medium Tryptic Soy Broth (TSB) or in minimal medium GEM7.0 (MgSO4.7H2O 0.2 g/L, Citric acid•H2O 2.0 g/L, K2HPO4 10.0 g/L, NaNH4HPO4.4H2O 3.5 g/L, Glucose 20 g/L, pH 7.0)" All Brucella strictly require biotin, panthotenate, thiamine and nicotinamide as additional factors. In addition 20g/L of glucose is almost ten times as much as normaly needed.

On 2014 Mar 16, Jonathan Eisen commented:

Two of the authors of this paper have written a guest post on my "Tree of Life" blog discussing some of the "Story behind the paper". See Story behind the paper guest post by Corey Nislow (w/ Metka Lenassi) on "Genomics w/o Borders"

On 2013 Nov 08, Seth Bordenstei commented:

The Story Behind "Mom Knows Best: The Universality of Maternal Microbial Transmission"

What types of microbes do mothers transmit to their newborns and how universal is maternal microbial transmission throughout animals?

http://symbionticism.blogspot.com/2013/08/the-story-behind-mom-knows-best.html

On 2014 Oct 06, Anders von Heijne commented:

Yes, the abductive mode of thinking that Peirce described is really very crucial in all forms of diagnostics. Depending on the problem at hand we clearly use different logical strategies. This is a must read, together with Lawson AE1, Daniel ES. Inferences of clinical diagnostic reasoning and diagnostic error.J Biomed Inform. 2011 Jun;44(3):402-12. Sadly this sort of analysis seldom appears in clinical speciality journals. If you are lucky you can find articles on Dual System theory and Bayesian theory, but without abduction there is no place to start using these techniques. We all need a dose of metacognitive musings from time to time.

On 2015 Sep 25, Amanda Capes-Davis commented:

Great to see a paper looking at reproducibility of cell culture systems, in this case for replication of HuNoVs, important for the study of acute gastroenteritis. The authors note in their Materials and Methods that two cell lines are used for viral growth, INT-407 and Caco-2, and correctly state that INT-407 has been cross-contaminated with HeLa. So it makes sense that INT-407 is not a good model for culture of HuNoVs. INT-407 was found to be cross-contaminated with HeLa in the 1960s and there are no known authentic stocks remaining for the original intestinal culture; INT-407 has been completely replaced by HeLa cells. HeLa may form microvilli as shown here, but HuNoV replication is likely to require additional tissue-specific factors that HeLa cannot supply.

Failure of Caco-2 is more puzzling, considering that the authors used a well-known intestinal (colorectal adenocarcinoma) cell line that was successful for the previous study, and obtained their stock of Caco-2 from the same source. However, it is worth noting that viral replication can vary across different strains or subclones e.g. Carson & Pirruccello, PMID 23408555. Caco-2 is well documented as a cell line that can change phenotype with passaging e.g. Briske-Anderson et al, PMID 9083258.

For a list of known misidentified cell lines, please refer to http://iclac.org/databases/cross-contaminations/. It is also important to authenticate cell line stocks before use. Setting up in vitro culture systems takes a great deal of time - testing can save a great deal of heartache!

On 2015 Dec 02, David Keller commented:

Extended-release niacin reduced Lp(a) but not CV risk, when added to statin therapy

The AIM-HIGH trial yielded a 21% reduction in Lp(a) levels when high dose niacin was added to statin therapy, but without the expected additional reduction in cardiovascular (CV) events. This is puzzling because it is known that CV risk is correlated to Lp(a) level. Niacin is known to lower Lp(a) levels, which was again demonstrated in this study.

The Coronary Drug Project, conducted in the pre-statin era, demonstrated that monotherapy with high-dose niacin reduced recurrent nonfatal myocardial infarctions, cerebrovascular events, and overall mortality at 15 years compared with placebo [1]. However, more recent studies of patients taking appropriate baseline statin therapy did not demonstrate additional reduced CV risk due to the improvement in lipids caused by the addition of niacin.

All of the patients in this study were on appropriate statin therapy at baseline. Again, we see that adding niacin to baseline statin therapy somehow fails to yield the additional outcome benefits expected from niacin's improvements in cholesterol and Lp(a) levels.

Given the evidence of outcome benefits with niacin monotherapy, but not with niacin added to a statin, it may be that statins somehow negate niacin's outcome benefits, despite preserving its improvement of the lipid profile. If so, then statin-intolerant patients remain candidates for niacin therapy, unless and until future clinical trials fail to reproduce the outcome benefits niacin demonstrated in the Coronary Drug Project.

Reference

1: Canner PL, Berge KG, Wenger NK, Stamler J, Friedman L, Prineas RJ, Friedewald W. Fifteen year mortality in Coronary Drug Project patients: long-term benefit with niacin. J Am Coll Cardiol. 1986 Dec;8(6):1245-55. PubMed PMID: 3782631.

On 2013 Oct 23, Albert Erives commented:

The background motivation of this paper is well written and informative. The "fine structure" of transcriptional enhancers underlying animal development is worthy of study and it is refreshing to see affirmation that there may be a range of simple to structured regulatory DNAs. From this report on Svb target enhancers, it will be important to follow-up on whether there are functional consequences to the range of architectures.

Also of interest is the following. The authors note that: "[t]hese findings highlight a paradoxical discrepancy between the enrichment of putative BSs accumulated in Svb downstream genes and the limited number of those acting as cis-regulatory elements. Is there a role for this evolutionary accumulation of Svb-like motifs in Svb targets?" This is an important question that is related to the broader issues of homotypic site clustering and related phenomenon mentioned in this paper's background. Though my lab's work is nicely integrated into the introduction, there is one additional key study of ours that is most relevant to these issues: "Dynamic evolution of precise regulatory encodings creates the clustered site signature of enhancers" (Crocker J, 2010). I suspect this one issue, and a difficulty in experimentally testing the function of every single sequence component of a homotypic site cluster, has facilitated the generally-assumed working model that each sequence component in a cluster or locus remains functional in the extant organisms from they have been isolated (I take issues with this model on several grounds). To some extent this is a question that preceded the more recent debate about "biochemical functionality" in the ENCODE data sets. This report is another step towards a more versatile, effective, and evolutionarily-grounded language of enhancer biology.

On 2014 Sep 15, Andrea Messori commented:

Bayesian models implemented under Winbugs: can they be considered the new standard for conducting a network meta-analysis?

When multiple agents are available to treat the same disease condition, network meta-analysis of randomized controlled trials (RCTs) has the purpose of synthesising the available evidence. In the application of this technique, both direct and indirect comparisons are made between individual treatments. Direct comparisons are those for which a “real” randomised study is available while indirect comparisons are those for which no real trial has been conducted.

Initial approaches for conducting network meta-analyses were designed to separately evaluate each indirect comparison; hence, there were as many separate analyses as the number of indirect comparisons [1,3]. More recently, the Bayesian approach for network meta-analysis has emerged as the new standard in this area [4-7]. This method relies on a sort of “all-in-one” modelling in which a single model incorporates the evidence available from all clinical trials and estimates, through a unified approach, all comparative results for both direct and indirect comparisons.

In network meta-analysis, the phases of literature search and data extraction do not differ from those commonly employed for standard meta-analysis [5,6]. As regards the type of end-points, network meta-analysis favours binary end-points [4] as opposed to continuous ones. Hence, irrespective of whether the analysis is aimed at evaluating effectiveness or safety, the starting material for conducting a network meta-analysis is given by the rates of end-point occurrence (i.e. numerator and denominator) for each arm of each RCT.

In present times, statistical modelling for network meta-analysis recognises its new standard in these Bayesian approaches based on an “all-in-one” model and implemented in the WINBUGS environment [4,7]. This approach has found a wide acceptance also because the methods and the software, developed by an authoritative institution (the NICE), are freely available [7]. The code for these estimations is available as fixed-effect model and random-effect model.

The Winbugs Bayesian model employs a random sequence of chains, called a Markov chain Monte Carlo simulation. Each chain must be run for a length of time sufficient to allow model convergence (burn-in) before estimating posterior probabilities. Typically, the random-effect logistic regression model is created according to the binary outcome of subjects reaching the end-point concerned. Randomization within each study is preserved by specifying each arm in each study separately, thus accounting for the effect of the comparator. Results are generally presented as odds ratio or log odds ratio. Heterogeneity among studies can be accounted by applying meta-regression techniques and by consequently generating an index of heterogeneity [4,7].

As regards the software, these analyses can be conducted by using the software package WinBUGS 1.4.3 (Cambridge, United Kingdom) in combination with the meta-analysis code developed by the National Institute for Health and Care Excellence[7]. Odds-ratio is the typical outcome measure of this software; however, odds-ratios can be converted into risk ratios or risk differences by application of standard equations [8,9]

Sobieraj and co-workers [10] have published an article that reviews all previously published studies that have adopted the Bayesian approach.

In conclusion, the present literature clearly indicates that Bayesian network meta-analysis can be considered the new standard in this field.

References

1. Lumley T. Network meta-analysis for indirect treatment comparisons. Stat Med 2002, 30; 21(16): 2313-24

2. Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol 1997;50(6):683–91

3. Wells GA, Sultan SA, Chen L, Khan M, Coyle D. Indirect treatment comparison [computer program]. Version 1.0. Ottawa: Canadian Agency for Drugs and Technologies in Health; 2009. Software available at:http://www.cadth.ca/preview/en/resources/itc-user-guide

4. Greco T, Landoni G, Biondi-Zoccai G, D'Ascenzo F, Zangrillo A. A Bayesian network meta-analysis for binary outcome: how to do it. Stat Methods Med Res. 2013 Oct 28.

5. Hoaglin DC, Hawkins N, Jansen JP,. et al. Conducting Indirect-Treatment-Comparison and Network-Meta-Analysis Studies: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices—Part 2. Value Health 2011;14:429-37.

6. Jansen JP, Fleurence R, Devine B, et al. Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: Part 1. Value Health 2011;14:417-28.

7. NICE Clinical Guidelines, No. 92. National Clinical Guideline Centre – Acute and Chronic Conditions (UK). London: Royal College of Physicians (UK); 2010. Available at http://www.ncbi.nlm.nih.gov/books/NBK116530/ Accessed 14 August 2014

8. Zhang J, Yu KF. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998 Nov 18;280(19):1690-1.

9. ClinCalc Website. Odds-ratio to risk ratio. http://clincalc.com/Stats/ConvertOR.aspx

10. Sobieraj DM, Cappelleri JC, Baker WL, Phung OJ, White CM, Coleman CI. Methods used to conduct and report Bayesian mixed treatment comparisons published in the medical literature: a systematic review. BMJ Open. 2013 Jul 21;3(7). pii:e003111. doi: 10.1136/bmjopen-2013-003111. Print 2013.

On 2014 Feb 23, Pei-Hui Wang commented:

PubM.Comm. is a funny tool!

On 2016 Dec 16, Alessandro Rasman commented:

CAREFUL APPLICATION OF THE RECOMMENDED PROTOCOLS IMPROVE REPRODUCIBILITY AND PERMIT COMPARISON AMONG CCSVI STUDIES. Posted by zambo on 15 Aug 2013 at 00:12 GMT http://journals.plos.org/plosone/article/comment?id=10.1371/annotation/a1ae22d2-49a5-4c0b-9b9d-dbb08773216b https://drive.google.com/file/d/0B_Ed_wxZvab3OWg4Y242NWFEQ3M/view?usp=sharing

On 2013 Oct 23, Stephen Shea commented:

What is the basis for the statement that CO2 is odorless? Because it is to humans? This paper that the authors cite (http://www.ncbi.nlm.nih.gov/pubmed/17702944) quite convincingly demonstrated low concentration responses to CO2 in the olfactory sensory neurons and main olfactory bulb?. What reason is there to conclude that these are trigeminal in origin? Aren't these neurons the most likely source of the responses you see in cortex? I don't see how you can make your central claim without inactivation of trigeminal and olfactory sensory neurons.

On 2014 May 22, Jacob Puliyel commented:

Post-marketing surveillance cannot properly estimate risks

The authors must be congratulated for conducting a study whose scope was so vast. However it must be recognized that RCTs are the best method to look for risks and benefits. Post-marketing surveillance is relied on to detect rare adverse events. It has severe limitations in quantifying the magnitude of risks. The present study highlights the problem well.

1 The authors estimate the risk of intussusceptions (IS) in two window periods after immunization. Previously surveillance had found that the incidence of IS was significantly increased in the first 3 weeks and more after the first dose than after the second dose. But that does not imply the risk of IS is limited to this window period alone. Only long term RCTs can really identify the full risk of IS after immunization and can categorically confirm that there is no risk in other periods.

2 For estimating reduction of diarrhea the authors use the hospital discharge diagnosis coded rota virus (A08.0) or acute gastroenteritis excluding rota virus (A01-A09, K32 excluding A08.0) multiplied by proportion of the cases estimated to be rota virus.

I am not sure how coding is done in the National Morbidity Database of the Australian Institute of Health and Welfare, but in many countries, diarrhea where rota virus is identified is coded as rota virus diarrhea, even where other pathogenic organisms are identified alongside and rota virus may not be the cause of the episode of diarrhea. The new rota virus vaccine strain from India, the monovalent human-bovine (116E) rotavirus, was cultured from an asymptomatic neonate in India. http://www.ncbi.nlm.nih.gov/pubmed/24629994. Some strains of rota virus could be a harmless commensals. The harmless rota virus may be protecting the individual imparting natural immunity without need for vaccines. Just because an organism is identified in a child with diarrhea, it does not necessarily imply that the organism is the cause of the diarrhea.

Furthermore, there are obvious problems in assuming that a fixed proportion of all diarrhea which are 'not coded as rota virus,' are due to rota virus.

Given these drawbacks, the estimate of 6500 rota virus hospitalizations avoided in Australia may not be accurate.

The judgment on acceptability of the risk-benefit equation pivots on the trade off between the putative 6500 rota virus admissions avoided on the one hand and the 14 cases of IS caused by the vaccine on the other, and these figures may not be reliable in the first place.

3 In their conclusions in the Abstract the authors say the "balance of risks and benefits at population level was highly favorable – a finding likely to extend to other settings despite varying incidence of IS and potentially higher morbidity and mortality from gastroenteritis and IS." This conclusion is clearly debatable.

The morbidity and mortality from gastroenteritis may be high in developing countries, but the morbidity and mortality for IS is disproportionately higher. Most developing countries can manage dehydration but facilities for surgical and radiological management of IS may not be available in large areas, making the risk unacceptable in accordance with the principle of primum non nocere.

4 Another factor the authors do not consider in their conclusion (that the findings are likely to extend to other countries,) is the varying vaccine efficacy seen in different countries. While the efficacy is nearly 90% in Western countries it is barely 50% in the tropics. Although the authors do not refer to the study by Madhi et al http://www.ncbi.nlm.nih.gov/pubmed/20107214 it is often quoted in this context. Severe rota virus gastroenteritis (SRVGE) was more common in Malawi than South Africa (13.1 vs. 5.4) and even though efficacy was lower in Malawi (49.4% vs. 76.9%) more cases of SRVGE were prevented by vaccination (6.7 vs. 4.2) in Malawi. This is often given as the justification for using the vaccine (with such low efficacy) in poor tropical countries.

This does not apply to all nations in the tropics. Although the incidence of gastroenteritis is high in India, the incidence of rota virus diarrhea was even less than South Africa. The incidence SRVGE in the unvaccinated in India was 3.4% compared to 13.1 in Malawi and 5.4 in South Africa. The absolute risk reduction (ARR) by vaccination was tiny in India (1.7). This is much lower than the benefit in Malawi (6.7) and even South Africa (4.2). It raises questions about the need for the vaccine in countries like India using the ‘disease burden’ argument. http://www.ncbi.nlm.nih.gov/pubmed/24629994#cm24629994_3808. Clearly each country needs to evaluate local risks and benefits and a blanket recommendation for all countries for the vaccine is perhaps not appropriate.

5 In conclusion: This study clearly shows the problems of relying on post marketing surveillance to evaluate harms. After unusual adverse events have been identified during post marketing surveillance, (if they are serious in nature) the vaccine must be withdrawn and reassessed in RCTs of sufficient size.

6 The data from the small 2-year follow-up RCT of the Indian vaccine 116E (4500 children received the new rota virus vaccine) will help understand if the '3 week window' is adequate to identify all adverse events. This follow-up paper is awaited. The preliminary report is available http://www.ncbi.nlm.nih.gov/pubmed/24629994#cm24629994. From the initial data it appears that the incidence of IS may be higher with this vaccine and so it may be a good vaccine to study the ‘window period’ of increased risk of IS.

On 2014 Nov 14, Curtis Corum commented:

Stephen,

Interesting comment...

I am not as familiar with standard imaging reporting for PC. For PC it is the various Gleeson scores that are of final interest, but structured imaging reporting is not necessarily as far along as in breast?

In Breast the BI-RADS reporting is standard, and now includes qualitative/semi-quatnitative DCE and morphological MRI. Efforts to process emerging modalities such as quantitative DCE and DWI/ADC are still research topics... for example http://www.ncbi.nlm.nih.gov/pubmed/23504036 as far as I can tell.

For treatment monitoring in breast (and many others icluding PC?) there are the various RECIST etc. http://www.ncbi.nlm.nih.gov/pubmed/18316345 that are continuously being updated as volumetric and other information becomes more readily available.

will review more...

On 2014 Aug 27, Stephen Strum commented:

My comment is limited by obviously not having read the full text of the article. What I have found in reviewing data on Multi-Parametric MRI (MPM) in PC (prostate cancer) is a lack of objective reporting, aka "structured" reporting. Therefore, I wonder if BC (breast cancer) reporting is similar.

What is needed is consensus on reporting the important objective data e.g., for DWI, indicating the Apparent Diffusion Coefficient (ADC) and b values; for DCE, reporting Ktrans (transfer constant min-1) or signal intensity-time curves (SITCs), and of course dimensional measurements for T2WI (T2 weighted images).

Such an attempt at a structured report would not only be of great value to clinicians for evaluating initial response to neoadjuvant therapy but also for ongoing responses to any form of treatment.

On 2014 Mar 14, Jonathan Eisen commented:

The last author of the paper, Amy Pruden, wrote a post for the "microbiology of the Built Environment network" (microBEnet) blog about this paper. See Probiotics for Plumbing?

On 2014 Feb 20, Markus Meissner commented:

Thank you very much for your feedback and the constructive criticism regarding our paper. We agree with some of the criticism regarding the nature of the localisation of TgStx6. Based on the co-localisation data with proM2AP, VP1 and GRASP we were initially convinced that Stx6 is localising to early endosomes, similar to the situation in ophistokonts. However, EM and IEM analysis did not result in the identification of EE but rather it appears that Stx6 is localising to the TGN as mentioned in the manuscript. However, we do not rule out that EEs exist and propose it as a hypothesis that apicomplexans have a more plant-like configuration.

With respect to other co-localisations with Rab5 or GalNac, we had some technical problems with these assays. As described in Kremer et al., 2013 overexpression of Rab5A (and Rab5C) leads to significant defects in the secretory system and therefore colocalisation analysis of parasites (over-) expressing both markers turned out to be not reliable. However, we agree that colocalisation with GalNac on transgenic parasites expressing endogenously tagged Stx6 would add additional information and should be performed in the future.

As you point out there is currently much confusion in the field if we can call something endosomal or endosomal-like. As one anonymous reviewer put it:” The authors are very generous in their use of the tern “endosome” in an organism where no form of endocytosis has even been seen. It might be better to define the process studied here as post-golgi membrane trafficking. “ We believe that unless one is very familiar with the terminology surrounding vesicular trafficking in Toxoplasma, the literature is very confusing. Therefore it might be the time where we have to agree on a common nomenclature based on the localisation of known markers, so that everyone has a clearer idea of the endomembrane system.

On 2014 Feb 19, Vernon B Carruthers, PhD commented:

Our group reviewed this paper for journal club recently. The group appreciated the novelty and importance of the study in defining new players in the elaborate vesicular transport system of the parasite. The main point raised was the unclear basis for stating that the study provided no "conclusive evidence for early endosomes in the parasite" and that the parasite likely harbors a fused TGN-EE similar to plants. The study did not attempt to look for early endosomes. It is widely acknowledged that there is limited published evidence that T. gondii can internalize exogenous material into its endocytic system. Nonetheless, Rab5, which is a classic marker for early endosomes has been used in several studies to define a mid-apical compartment that is associated with other markers of endosome-like compartments. Likewise, a previously characterized marker for the TGN, UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase or GalNac for short, was not tested. Comparing the localization of TgStx6 with these markers would help clarify the issue of a merged or separate TGN-EE in T. gondii.

On 2015 Sep 04, Casey M Bergman commented:

Orignally posted at PubPeer: https://pubpeer.com/publications/B37A9BD035CAEA3EEE79C48DDB0378

This paper provides a nice example of natural selection operating on a new gene duplicate at the Resistance to dieldrin (Rdl) locus in in D. melanogaster. Starting with an amino acid variant that is known to confer resistence to the insecticide dieldrin, the authors query whole genome sequences in the Drosophila Genetic Reference Panel (DGRP) [1] and find four strains that contain the resistance mutation. In three of the four strains, the resistance mutation is found unexpectedly in a heterozygous condition. The DGRP strains are highly inbred but are known to contain regions of residual heterozygosity scattered throughout the genome that could arise from incomplete inbreeding or segmental duplication.

By genotyping the offspring of "heterozygous" stocks, the authors find that 100% of progeny retain the heterozygous state, consistent with a segmental duplication. Analysis of the depth of sequence coverage in "heterozygous" strains confirms a 2-fold increase in the depth of coverage for a ~110 kb region containing Rdl and several other genes. The segmental duplication is flanked by two Roo transposable elements, suggesting it arose by ectopic recombination between repetitive sequences. The outcome of the duplication is that one duplicate contains the resitance allele and the other duplicate contains the susceptibility allele. Both copies are expressed. Transgenic analysis confirmed that the cause of the resistence allele is due to a single amino acid change in the Rdl gene only.

This paper shows how a newly arising allele with partial dominance can achieve a state of "permanant heterozygosis" by segmental duplication, conferring immediate adaptive advantage via the new allele while also retaining ancestral function via the old allele. This result nicely confirms a theoretical model developed by Spofford (1969) [2] (not cited in the current work) to explain selective forces that would govern the fixation of a new, polymorphic segmental gene duplicate. This work also shows that the "residual heterozygosity" in the DGRP lines may be more than just background noise from the vagaries of inbreeding, and may in fact point to many other functional segmental duplications in these lines.

[1] Mackay, Trudy FC, et al. "The Drosophila melanogaster genetic reference panel." Nature 482.7384 (2012): 173-178. http://www.nature.com/nature/journal/v482/n7384/full/nature10811.htm

[2] Spofford, Janice B. "Heterosis and the evolution of duplications." American Naturalist (1969): 407-432. http://www.jstor.org/stable/2458991

On 2013 Oct 31, John Cannell commented:

I congratulate the authors on a fine study. I wonder if they are aware that Mostafa et al found that an anti neural antibody found in autism had a -.86 correlation coefficient with 25(OH)D levels? If not it goes to show that scientists become experts in their own niche but apparently do not keep up with relevant science in other fields.

Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

Thus the vitamin D theory of ASD (vitamin D deficiency being the environmental risk factor for this highly heritable disorder) is consistent with the authors work. Three recent studies, using community controls, have found 25(OH)D levels are significantly lower in children with ASD. Two of the studies below (Mostafa et al and Gong et al) also found ASD severity, as rated on standard ASD rating scales, is inversely correlated with 25(OH)D levels. Mostafa et al found an R value of -.86 for the association of serum 25(OH)D with ASD severity.

Gong ZL, Luo CM, Wang L, Shen L, Wei F, Tong RJ, Liu Y. Serum 25-hydroxyvitamin D levels in Chinese children with autism spectrum disorders. Neuroreport. 2013 Oct 1. Gong ZL, 2014

Meguid NA, Hashish AF, Anwar M, Sidhom G. Reduced serum levels of 25-hydroxy and 1,25-dihydroxy vitamin D in Egyptian children with autism. J Altern Complement Med. 2010 Jun;16(6):641-5. Meguid NA, 2010

Mostafa GA, Al-Ayadhi LY.Reduced serum concentrations of 25-hydroxy vitamin D in children with autism: relation to autoimmunity. J Neuroinflammation. 2012 Aug 17;9:201. Mostafa GA, 2012

There is a plethora of basic science explaining why low gestational or early childhood 25(OH)D levels would adversely effect brain development.

DeLuca GC, Kimball SM, Kolasinski J, Ramagopalan SV, Ebers GC. Review: the role of vitamin D in nervous system health and disease. Neuropathol Appl Neurobiol. 2013 Aug;39(5):458-84. doi: 10.1111/nan.12020. DeLuca GC, 2013

Eyles DW, Feron F, Cui X, Kesby JP, Harms LH, Ko P, McGrath JJ, Burne TH. Developmental vitamin D deficiency causes abnormal brain development. Psychoneuroendocrinology. 2009 Dec;34 Suppl 1:S247-57. doi: 10.1016/j.psyneuen.2009.04.015. Epub . Review. Eyles DW, 2009

Furthermore, the vitamin D theory of autism explains most of the epidemiological facts of ASD.

Cannell JJ. On the aetiology of autism. Acta Paediatr. 2010 Aug;99(8):1128-30. Cannell JJ, 2010

Cannell JJ. Autism and vitamin D. Med Hypotheses. 2008;70(4):750-9. Cannell JJ, 2008

70% of American toddlers do not take the American Pediatric Association's recommended vitamin D supplement of 400 IU/day. As milk consumption has fallen, so have toddler’s vitamin D levels.

Cannell JJ. Autism, will vitamin D treat core symptoms? Medical Hypotheses. 2013 Aug;81(2):195-8. Cannell JJ, 2013

Some autism researchers seem cognizant of the entire body of autism research. For example, a group of well-known European autism researchers, including Professor Christopher Gillberg of the Gillberg Neuropsychiatric Institute, have recently called for the need for “urgent research” into the vitamin D deficiency theory of ASD.

Kočovská E, Fernell E, Billstedt E, Minnis H, Gillberg C. Vitamin D and autism: clinical review. Res Dev Disabil. 2012 Sep-Oct;33(5):1541-50. doi: 10.1016/j.ridd.2012.02.015. Epub 2012 Apr 21.Kočovská E, 2012

However, these scientists appear to be in the minority. Until all autism researchers become cognizant of the wider body of scientific research, we will continue to wonder how to prevent - and perhaps even treat - this modern day plague.

John J Cannell, MD

Vitamin D Council

http://www.vitamindcouncil.org

On 2014 Sep 26, George Ntoumenopoulos commented:

The ability to determine the need for and deliver physiotherapy for patients managed on VV-ECMO is challenging, both from the acute respiratory and rehabilitative perspective. The cannulae type, location (e.g. femoral and/or jugular veins) and stability of delivery of VV-ECMO may impact on the clinicians opinions (physiotherapy and medical staff) about physiotherapy care. Deep sedation levels during ECMO may limit the ability the deliver physiotherapy and we need to explore this further. The use of ultra-low tidal volume delivery during mechanical ventilation for lung protective ventilation may also mask the detection of problems such as secretion retention, with standard methods such as"sawtooth" patterning on expiratory flow waveforms. We need to further investigate the role of physiotherapy (both acute respiratory and rehabilitative) in this complex patient group.

On 2014 Oct 15, Gerd Heusch commented:

The skepticism of Dr. Berthelsen is well taken. However, contrary to his expectation, the results of our study with its primary endpoint troponin release have already been replicated, see Candilio L, 2015.

On 2014 Oct 13, Preben Berthelsen commented:

This study was registered with ClinicalTrials (NCT01406678). According to the registration, the authors planned to include 500 patients in a randomised study of remote ischaemic preconditioning (RIP) in isoflurane anaesthetised patients. No interim statistical analyses were planned. The study was, however, stopped early after the inclusion of 162 patients in the RIP-group and 167 patients in the group where no RIP was used. (Only 121 and 137 patients could be included in a per protocol analysis).

It is an indispensable rule not to break the randomisation code before all patients have completed the investigation. The authors have not followed this imperative. They have kept running track of the results as can be seen from the admission on page 598 of this paper “After use in some patients, however, we became aware of apparent interference of propofol with remote ischaemic preconditioning and discontinued its use in the remainder of the study”. So at least theoretically, it has been possible for the authors to analyse the data continuously and therefore stop the investigation – when a statistical difference was demonstrated – and before the stipulated number of patients had been reached.

A re-calculation of the power of the study using the 17% difference in 72h-troponin AUCs and a SD of 200 (standardised difference 0.27) shows that there is less than a 50% chance that another study would replicate the authors’ findings. It is my opinion that the result of this investigation must be viewed with some scepticism. Preben G. Berthelsen MD. Charlottenlund, Denmark.

On 2014 May 21, Amanda Capes-Davis commented:

INT 407 is a widely used cell line. However, many scientists are unaware that it is NOT an intestinal cell line. INT 407 is cross-contaminated by HeLa, which comes from cervical carcinoma. For a list of known cross-contaminated cell lines, see http://iclac.org/databases/cross-contaminations/.

On 2013 Oct 26, Lorene M Nelson commented:

This article provides an excellent summary of the state of knowledge regarding the role of pesticides in the etiology of Parkinson’s disease, and nicely highlights the challenges faced by environmental epidemiologists in identifying specific pesticide chemicals that are associated with PD. I agree with Dr. Kamel that it has been difficult to make substantial progress in identifying specific pesticide chemicals that increase PD risk except in unique circumstances, such as the two recent high-quality cohort studies that she cites. Another notable example is the retrospective (case-control) study conducted in central California by Dr. Ritz (UCLA investigator) whose group has produced findings implicating workplace and ambient pesticide exposure in PD [Wang A, 2011; also cited by Dr. Kamel], well-water consumption Gatto NM, 2009, specific pesticide combinations Costello S, 2009, and gene-pesticide exposure interactions Manthripragada AD, 2010.

On 2014 Nov 17, Raphael Levy commented:

This article belongs to the “stripy nanoparticles” series. The evidence behind the structure and special properties of these nanoparticles has been challenged by Cesbron Y, 2012. The publication in 2012 of Cesbron Y, 2012 took three years and has been followed by post-publication peer review of the various existing and new stripy articles on my blog, PubPeer, etc.

A detailed analysis of this body of work is published today in PloS One by Stirling et al; from the abstract: “through a combination of an exhaustive re-analysis of the original data with new experimental measurements of a simple control sample comprising entirely unfunctionalised particles, we conclusively show that all of the STM evidence for striped nanoparticles published to date can instead be explained by a combination of well-known instrumental artefacts, strong observer bias, and/or improper data acquisition/analysis protocols.”

On 2014 Jun 30, Karel Koberna commented:

The method described in the article of Cappella et al. was patented by us in 2012 and at the end of the same year published in great detail in our article “Atomic Scissors: A New Method of Tracking the 5-Bromo-2′-Deoxyuridine-Labeled DNA In Situ” PLoS (7(12): e52584). This fact is not evident as the paper of Cappella et al. contains incorrect reference to our original paper. We asked editor of Cytometry A to correct this error so we believe that it will be corrected soon.

On 2013 Dec 02, Kenneth N Litwak commented:

This study, by Ruff et al, attempted to demonstrate negative effects of excess sugar consumption on mouse survival, competitive ability, and reproduction, as a means of demonstrating the utility of Organismal Performance Assays (OPAs) in quantifying toxicities. However, there are multiple methodological issues in the article affecting its value.<br> 1. In the discussion, the authors state that the diet was “analogous to human subjects consuming a healthy diet plus the equivalent of ~3 cans of soda per day”. This statement does not correctly reflect the study diet vs. control diet, as the two diets were isocaloric. Adding 3 cans of soda to the diet would add additional calories to a diet, not replace a source of carbohydrates.<br> 2. The authors correctly noted that this experiment would have ideally maintained the different groups on their original diets for duration of the study; however, all mice were given the F/G diet once they entered the OPA enclosures at 26 weeks of age and for the next 7 – 8 months. This change in diet is a major confounding point of the entire experiment. It might be reasonably assumed that initial outcomes in the OPA enclosures would be due to different diets, but the authors do not provide any data to support this premise, for initial or long-term outcomes.<br> 3. Mouse pups were only counted every six week to determine reproductive success (Methods). The long duration between counts would likely result in an under-count of reproductive success, as cannibalism and early pup death would be difficult to determine. Further, the duration between counts was sufficient to allow multiple litters to be born to founder mice and to F1 mice.<br> 4. The confounding effects of the OPA enclosures and their locations (Supplementary Figure S3) are potentially significant. Each enclosure was immediately adjacent to others. However, some enclosures were only bounded by two enclosures, while some were bounded on three sides by other enclosures. Stress associated with territorial boundaries has been repeatedly documented in mice. Due to the small size of this study, the potential space interaction could have had significant effects on the outcomes.

On 2017 Jul 08, David Keller commented:

Why Physicians Favored Lipitor Over Simvastatin

In their commentary on generic drug use, Alldredge and Kayser state the following:

"In 2011, fewer prescriptions for generic simvastatin were written than for Lipitor (atorvastatin calcium; Pfizer Inc) despite a significant cost differential and no apparent clinical differences in efficacy and safety." [1]

That statement is an unfair criticism of physicians and conflicts with the expressed views of the Food and Drug Administration (FDA). On June 8, 2011, the FDA issued a safety warning concerning simvastatin [2] in which physicians were advised to discontinue the use of simvastatin, 80 mg (except in patients who had already been taking it safely for over 1 year).

For patients taking amlodipine, the FDA warned against prescribing more than 20 mg of simvastatin, and for patients taking diltiazem or verapamil, the dose of simvastatin was limited to 10 mg. These safety warnings were based on reports of adverse events including serious myopathy caused by simvastatin, 80 mg, and by lower doses of simvastatin when combined with widely prescribed calcium channel blockers.

As a result, physicians were left with a maximum safe simvastatin dose of 40 mg, which lowers low-density lipoprotein cholesterol level by approximately 40%, whereas atorvastatin, 80 mg, lowers low-density lipoprotein cholesterol level by approximately 55%.[3] The FDA has not deemed it necessary to issue similar safety restrictions on the use of atorvastatin, which may explain why physicians favored Lipitor over generic simvastatin in 2011.

References

1: Alldredge BK, Kayser SR. Bending the curve toward increased use of generic drugs. JAMA Intern Med. 2013;173(3):233-234. PubMed Article

2: FDA Drug Safety Communication: new restrictions, contraindications, and dose limitations for Zocor (simvastatin) to reduce the risk of muscle injury. www.fda.gov/Drugs/DrugSafety/ucm256581.htm. Accessed February 21, 2013.

3: Law MR, Wald NJ, Rudnicka AR. Quantifying effect of statins on low density lipoprotein cholesterol, ischaemic heart disease, and stroke: systematic review and meta-analysis. BMJ. 2003;326(7404):1423. PubMed Article

Author's note: the format of the above letter is scrambled and difficult to read, as published online at the following URL:

https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/1726968

Due to the difficulty of getting the published version corrected, I have posted the corrected version above.

On 2014 Jan 15, Satoko Hattori commented:

"ImageLD" and "ImageEP", image analysis application softwares used in this article, are now freely available from http://www.mouse-phenotype.org/software.html.

On 2013 Nov 14, Gareth Highnam commented:

Awesome study, are cancerous areas changed to a uniform density across ethnicities? Or does density of cancerous areas also have an ethnic component? All factors for an optimized detection model, I suppose. [CoI - RH is my favourite published uncle :) ]

On 2013 Nov 20, Jamie Horder commented:

It would be wrong to say that reverse coded items are rarely not unconfusing!

On 2013 Nov 17, James C Coyne commented:

Formal Correction: This article has been formally corrected to address the following errors.

As a result of an error by PLOS ONE, an incorrect version of the article was typeset. Below is a link to a version of the article based on the correct manuscript.

http://www.plosone.org/annotation/listThread.action?root=71757

On 2013 Nov 05, Pedro Mendes commented:

This yeast metabolic reconstruction improves on the work described in Herrgård MJ, 2008, Dobson PD, 2010, and Heavner BD, 2012. The data set is available at http://yeast.sf.net/

On 2017 Jun 10, Casey Greene commented:

We used this method in our own preprint. Our preprint is available on bioRxiv: https://doi.org/10.1101/147645

For the convenience of the research community, we have made our implementation available as an open source python package. It is currently maintained on GitHub (https://github.com/kathyxchen/crosstalk-correction) and distributed via PyPI (pip install crosstalk-correction). We hope that others will also find this useful.

On 2014 Jul 12, Jorge H Ramírez commented:

The overall quality of this randomized clinical trial is poor:

• Limited time of follow-up (12 weeks) to determine the safety and effectiveness of an active pharmacological principle or a fixed-dose combination (i.e., solifenacin plus tamsulosin).

• The study evaluates surrogate instead of definitive outcomes.

• No description of allocation concealment mechanisms.

• No description of methods used to generate the random sequence used in the randomization of patients to each study arms

• The article does not describe methods for the implementation of the random sequence.

• No appropriate description of blindings in the study.

• No intention-to-treat analysis

• Cardiovascular adverse events were not appropriately described in this article.

• Haemodynamic variables were not included as primary or secondary outcomes in this study.

Tamsulosin is a nonuroselective alpha blocker associated with severe hypotension in men.(1,2) Moreover, over three quarters of the studies with tamsulosin in humans are unpublished.(3)

A recent publication entitled "Solifenacin/tamsulosin FDC squeezes out competitors."(4) supports that this combination is cost-effective only based in the pharmacoeconomic analysis of this study (Neptune trial. van Kerrebroeck and colleagues. Eur Urol 2013).

I have the following open-question for anyone reading this comment:

What would happen with pharmacoeconomic evaluations involving solifenacin/tamsulosin in the treatment of lower urinary tract symptoms after considering the risk of severe hypotension and the results of unpublished studies?

Finally, I personally think that the title "Solifenacin/tamsulosin FDC squeezes out competitors." resembles more a pharmaceutical marketing campaign (a misleading one) than a serious paper reporting the results of a pharmacoeconomic analysis.

References

1. Bird Steven T, Delaney Joseph A C, Brophy James M, Etminan Mahyar, Skeldon Sean C, Hartzema Abraham G et al. Tamsulosin treatment for benign prostatic hyperplasia and risk of severe hypotension in men aged 40-85 years in the United States: risk window analyses using between and within patient methodology BMJ 2013; 347:f6320 http://www.bmj.com/content/347/bmj.f6320

2. Ramirez Jorge. Severe hypotension associated with α blocker tamsulosin BMJ 2013; 347:f6492 http://www.bmj.com/content/347/bmj.f6492

3. Ramirez, Jorge H (2014): Expression of concern about tamsulosin: over three quarters of human studies are unpublished. figshare. http://dx.doi.org/10.6084/m9.figshare.1094338 URL:http://figshare.com/articles/Expression_of_concern_about_tamsulosin_over_three_quarters_of_human_studies_are_unpublished/1094338

4. Nazir, J. Solifenacin/tamsulosin FDC squeezes out competitors." PharmacoEconomics & Outcomes News 706 (2014): 10-5.