Sample Size Estimation in Bioequivalence? [Surveys]

posted by Helmut Homepage – Vienna, Austria, 2020-05-21 00:39 (1422 d 13:17 ago) – Posting: # 21455
Views: 22,701

Dear all,

on the occasion of recent discussions about software used for sample size estimation in BE I created a


with ten questions.

Attendance is anonymous and limited to one participation per device (i.e., same IP-address). If your institution has only one IP (like Novartis redirecting its 120,000+ employees to a single one in Basel…), sorry.
The survey should take about three minutes to complete.

The questions are:
  1. How do you estimate the sample size?
    ○ Sample size tables
    ○ Software
    ○ Both
  2. Which software do you use?
    ☐ Commercial (off-the-shelf, e.g., SAS Proc Plan, NQuery Advisor, PASS, StudySize, …)
    ☐ Open source (e.g., R-packages like PowerTOST, bear, …)
    ☐ Free (e.g., FARTSSIE, EFG, …)
    ☐ Web-based
    ☐ In-house (e.g., own SAS-macros, R, C, Excel-template, …)
    ☐ Optional: Please give the software you use most (incl. version, year of release)
  3. How often do you update the software you use most?
    ○ Never
    ○ Occasionally
    ○ Regularly
    ○ I don’t want to disclose this information
  4. Is the software you use most validated?
    ☐ IQ (Installation Qualification acc. to procedures provided by the vendor)
    ☐ OQ Type 1 (Operational Qualification acc. to procedures provided by the vendor)
    ☐ OQ Type 2 (Operational Qualification acc. to own pre-specified procedures)
    ☐ PQ (Performance Qualification)
    ☐ Comparison with sample size tables
    ☐ Cross-validated with other software
    ☐ Partly (i.e., only some of the procedures)
    ☐ No
    ☐ I don’t want to disclose this information
    ☐ Other approach (please specify)
  5. Were you ever asked by a regulatory agency about software validation?
    ☐ Yes
    ☐ No
    ☐ I don’t want to disclose this information
    ☐ Optional: If you answered “Yes”, please give the year
  6. Do you repeat the estimation in-house if provided by an external entity (CRO, sponsor, consultant)?
    ☐ Always
    ☐ Regularly
    ☐ Sometimes
    ☐ Never
  7. Do you perform a Sensitivity Analysis in order to assess the impact on power if in the study values (e.g., T/R-ratio, CV, number of dropouts) will deviate from assumptions?
    ○ Never
    ○ Sometimes
    ○ Always
    ○ I don’t know what a Sensitivity Analysis is
    ○ I don’t want to disclose this information
  8. Do you increase the estimated sample size according to the expected dropout rate?
    ○ Yes (formula: n’ = n × (100 + dropout-rate in %) / 100)
    ○ Yes (formula: n’ = n / (100 – dropout-rate in %) × 100)
    ○ Yes (as provided by the software; I don’t know the formula)
    ○ Yes (chosen by management)
    ○ No (since the impact on power is limited)
  9. Please give general problems that you faced in sample size estimation.
    ☐ Estimated sample size was substantially smaller/larger than expected
    (compared to PARs / other studies)

    ☐ Result of re-assessment differed from the estimate given (by CRO, sponsor, consultant)
    ☐ Software, version, setup not given (by CRO, sponsor, consultant)
    ☐ Other (please give a short description)
  10. Did you face problems with the software you use most?
    ☐ Planned design not available
    ☐ Only one design-variant provided (although alternatives exist)
    ☐ Methods based on simulations not reproducible (e.g., for reference-scaling)
    ☐ Operation is complicated
    ☐ User manual insufficient
    (too short/verbose, methods not/poorly documented, lacking/outdated references, …)

    ☐ No
    ☐ Other (please specify)
Feel free to participate. It could help all of us to understand the current landscape. If you close the browser in the middle of the survey, you can come back later – from the same device – to complete it.
If sample size estimation is not your cup of tea, consider inviting a responsible colleague.

I will post results mid June.

In the meantime I suggest [image] this one.

Edit: 101 respondents as of 2020-10-23. Average time taken 3:30 minutes. THX!

Dif-tor heh smusma 🖖🏼 Довге життя Україна! [image]
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

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