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Activity Number: 436 - SPEED: Tests, Trials, Biomarkers, and Other Topics in Biometrics
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 3:05 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #332570
Title: Practical Determining the Late Effect Parameter in Fleming-Harrington Test When a Delayed Treatment Effect Is Predicted
Author(s): Yuichiro Kaneko* and Satoshi Morita
Companies: Astellas Pharma and Kyoto University
Keywords: Fleming-Harrington test; delayed effect; weighted log-rank statistics

In many clinical trials, immuno-oncologic agents showed a delayed effect, thus leading to a violation of the proportional hazard assumption when comparing with the other drugs. To address this problem, it may be useful to use the weighted log-rank statistics. Fleming-Harrington test is categorized in the weighted log-rank statistics, and which has two parameters, i.e. the parameter p and q. When setting p>0 and q=0, it weights the early events heavily. In the delayed effect situation, it is reasonable to weight the later events by setting p=0 and q>0. However, it is difficult to choose an appropriate value of parameter q, for example, by discussing with clinicians, because parameter q is not directly clinically interpretable. On the other hand, Zucker and Lakatos (1990) discussed two weighted log-rank types of statistics assuming the prototypical lag model (i.e. 'linear' and 'threshold' lag models) where a delayed effect is expected. The 'linear' and 'threshold' lag includes clinically interpretable parameter. We propose a practical procedure to determine parameter q in Fleming-Harrington test in relation to these lag models, using the Pitman's asymptotic relative efficiency.

Authors who are presenting talks have a * after their name.

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