25 Matching Annotations
  1. Last 7 days
    1. 2l34IbrutinibAnastrozole,IbrutinibAcalabrutinibAcalabrutinib,Anastrozole2l

      Add notation here that If 2l then LOT2Linename == LOTENDS

  2. Apr 2024
    1. LL order details (13%, N=36 now represented in the table)

      Updated to reflect 13% not N=13

    2. osing Information on Venentoclax Patients

      Arliene and Sophia: We only have 273 of our patients with a record in the Medication orders table. Not everyone is represented.

  3. Dec 2023
    1. OD, N = 19,987,1801 OS, N = 19,940,3591

      No need to break eyes.

    2. 5 Table 3 - Procedures Medication and Drug Tables

      Only keep visits that match from Eye table. Check this.

    3. N = 3,616,7511

      Robert confirm if this is visits or patients

  4. Nov 2023
    1. N of Patient Eyes (1 or 2 Treated)

      David, here is the context. We have 83% of patients being treated for both eyes. That will mean that the N of injections probably appears higher since we aren't breaking them down into injections by specific eye.

  5. Oct 2023
    1. Race/Ethnicity (Raw)

      Possible project for Sophia? D&I - looking at disparities in ttt

    2. VenG vs. Nibs - Tables & Curves - Two to One Match

      Removed the 1:1 match - consolidated tables to be based on each matching pair.

    3. 2 Table 1 Characteristics

      Overall Cohort - Moved everything descriptive of overall cohort to this first section

    4. Our final sample size for the CLL FlatIron data set is 5,108 CLL patients fitting our inclusion and exclusion criteria.

      Final sample size for our study

  6. Sep 2023
    1. Dry AMD 43 (23%)

      Is this an artifact of how they are recording the DX.

    2. Showing 1 to 2 of 2 entries

      Add in a count of the N of Study Patients and N of Sample Patients

    3. Missing 0 (0%)

      Missing added as a future proof option for future data uploads.

    4. OU 0 (0%) Not Recorded 0 (0%)

      When we filter out records for condition == ALL we lose all Not Recorded and OU records in the Eye table.

    1. Unspecified

      Patients with a race value, but it is not useful for analysis. I am considering this missing if we have unspecified. Do you want me to keep it like that?

    2.     Medicare Cost 497 (0.9%) 1,005 (1.8%)     Medicare Risk 3,136 (5.4%) 4,952 (9.0%)

      Slightly higher Medicare Cost and Risk patients in the Race/Ethnicity grouping. Possibly due to the older age

    3. 46 (36, 55) 50 (42, 58)

      Fairly significant difference here. Not missing is older in comparison.

    1. Months Enrollment Coverage 19 (12, 28) 24.3 (17.2, 29.4

      Hmm this seems strange. Can you explain how this was calculated?

    2. Age at Enspryng Initiation 47 (32, 55) 47 (30, 52)

      Makes sense to me. Looks to be similar across cohorts

    3. Ultimately, after consulting with my TI colleagues and reviewing what we need to do for variable follow-up, I believe that for ease of interpretability that we should use the 6 months CE pre patients only for this analysis.

      Can you clarify?