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Statistical Consideration for Event-Free Survival With Cure Rate in Acute Myeloid Leukemia Studies
Yuichiro Kaneko1, Kentaro Takeda1, Shufang Liu2
1Clinical Operations, Quantitative Sciences and China Development, Astellas Pharma Global Development Inc., Northbrook, Illinois, USA.
Abstract:
In many acute myeloid leukemia (AML) studies, event-free survival (EFS) has been accepted as a primary efficacy endpoint. In those studies, the patients who do not achieve complete remission (CR) in the induction period are regarded as induction treatment failure (ITF). The recent FDA guidance on AML (2022) has clearly specified ITF as the event at Day 1 of randomization, considering the variability of length of individual induction treatment periods among studies. Xu et al. (2021) suggested decomposing the log-rank test statistic into the ITF portion, and the Non-ITF portion that is defined as the patients who achieved CR, and assumed proportional hazards for the Non-ITF portion. However, especially in the newly diagnosed AML study, there is some indication of the cured patients who achieve CR during the induction period. As a result, Non-zero ITF rates and cured patients invalidate the proportional hazards assumption and therefore, the conventional power calculation based on the number of events may be problematic in this setting. Our research follows the same decomposition of the log-rank test statistic as Xu et al. (2021) and suggests a new sample size calculation method accounting for the presence of both ITF and cured patients. The result shows that the analytically calculated power of log-rank test based on our proposal was very similar to the empirical power based on simulations in various finite sample settings and was also useful to protect from overestimation and underestimation of the required sample size in the presence of cure fraction.
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