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Sizing clinical trials when comparing bivariate time‐to‐event outcomes
Author(s) -
Sugimoto Tomoyuki,
Hamasaki Toshimitsu,
Evans Scott R.,
Sozu Takashi
Publication year - 2017
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7225
Subject(s) - censoring (clinical trials) , bivariate analysis , sample size determination , statistics , event (particle physics) , log rank test , econometrics , clinical trial , computer science , medicine , proportional hazards model , mathematics , physics , quantum mechanics
Clinical trials with multiple primary time‐to‐event outcomes are common. Use of multiple endpoints creates challenges in the evaluation of power and the calculation of sample size during trial design particularly for time‐to‐event outcomes. We present methods for calculating the power and sample size for randomized superiority clinical trials with two correlated time‐to‐event outcomes. We do this for independent and dependent censoring for three censoring scenarios: (i) the two events are non‐fatal; (ii) one event is fatal (semi‐competing risk); and (iii) both are fatal (competing risk). We derive the bivariate log‐rank test in all three censoring scenarios and investigate the behavior of power and the required sample sizes. Separate evaluations are conducted for two inferential goals, evaluation of whether the test intervention is superior to the control on: (1) all of the endpoints (multiple co‐primary) or (2) at least one endpoint (multiple primary). Copyright © 2017 John Wiley & Sons, Ltd.