20 Matching Annotations
  1. Apr 2024
    1. Ibrutinib

      Can you add a combined BTKi group column in this table? Since you matched on the BTKi group vs VenO, that will prob better show the matching variables are similar.

    2. 273 (100%)

      273 here but we should have 275 VenO patients.

      Also, at the bottom of the table it says 13% had missing all dose info, but this point says 273 had 400 mg dose at some point in time.

    3. Acalabrutinib, N = 921

      Confirm that pts are exact matched in age category, gender and race. Seems the acalabrutinib arm is different than Ibr and VenO

  2. Feb 2024
  3. Jan 2024
    1. 11 Exploring rwTTD and Gaps between LOTs

      Table 1 has 300 Acala and 1777 Ibrutinib patients. Where did these patients come from?

    2. Unknown

      Instead of "unknown", "Not calculated" with a footnote that 2L start not reported (or other).

    1. Inference: BTKI Median TTNTD 45.2 Months with a LCL of 38.6 and NA UCL. VenG does not reach Median but has an LCL of 40.4 and NA UCL

      This is outdated? Based on tab 3.3, this should be 48.0 mo for BTKi

  4. Nov 2023
    1. Characteristic

      can you please include the other clinical/demographic variables: payer, region, cytogenetics ? Also can you add the 2nd line therapies for the 2 groups?

  5. Oct 2023
    1. Acalabrutinib

      surprised there are no ibrutinib patients in the "nibs group". Can you pls check this?

    2. Unknown

      relabel to "No 2nd line therapy"

    3. Two to One Match

      On 3.2, the p-values and # at risk are different from the last run. Also the HR.

      Let's also revisit the # at risk from our last convo

    4. Every Received Cytogenetic Test

      should this be "Received any cytogenetic test"?

    1. 2961

      Should this be 268?

    2. -177 (-177, -177)

      how do I interpret a negative number here?

    3. Median TTNTD 48 Months

      Is the p-value of 0.0098 on the KM curve testing the TTNTD?

    4. Characteristic

      Can you confirm what was exact matched-- age category, gender and race? In an outdated slide, I had also noted that the model included practice type, payer category, SES although not exact matched

    5. 855

      can you include unknown/missing in the percentage?