title: Sizing clinical trials when comparing bivariate time-to-event outcomes.
abstract: 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.
authors.affiliation: Department of Mathematics and Computer Science, Kagoshima University Graduate School of Science and Technology, Kagoshima, Japan.
authors.forename: Tomoyuki
authors.initials: T
authors.lastname: Sugimoto
authors.affiliation: Department of Data Science, National Cerebral and Cardiovascular Center, Saita, Japan.
authors.forename: Toshimitsu
authors.identifier: 0000-0002-4928-1160
authors.initials: T
authors.lastname: Hamasaki
authors.affiliation: Department of Biostatistics and Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health, Boston, MA, U.S.A.
authors.forename: Scott R
authors.initials: SR
authors.lastname: Evans
authors.affiliation: Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Tokyo, Japan.
authors.forename: Takashi
authors.initials: T
authors.lastname: Sozu
mesh_terms: D003627:Data Interpretation, Statistical; D018450:Disease Progression; D023381:Endpoint Determination / Q000706:statistics & numerical data; D000074099:Equivalence Trials as Topic; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D018401:Sample Size; D016019:Survival Analysis; D016896:Treatment Outcome
keywords: dependent censoring; log-rank test; multiple endpoints; semi-competing risk; time-dependent association