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Design and Analysis of Group Sequential Clinical Trials with Multiple Primary Endpoints
Author(s) -
Kosorok Michael R.,
Yuanjun Shi,
DeMets David L.
Publication year - 2004
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2004.00146.x
Subject(s) - clinical endpoint , early stopping , clinical trial , type i and type ii errors , medicine , treatment and control groups , clinical study design , statistics , computer science , mathematics , artificial intelligence , artificial neural network
Summary. In many phase III clinical trials, it is desirable to separately assess the treatment effect on two or more primary endpoints. Consider the MERIT‐HF study, where two endpoints of primary interest were time to death and the earliest of time to first hospitalization or death (The International Steering Committee on Behalf of the MERIT‐HF Study Group, 1997, American Journal of Cardiology 80 [9B], 54J–58J). It is possible that treatment has no effect on death but a beneficial effect on first hospitalization time, or it has a detrimental effect on death but no effect on hospitalization. A good clinical trial design should permit early stopping as soon as the treatment effect on both endpoints becomes clear. Previous work in this area has not resolved how to stop the study early when one or more endpoints have no treatment effect or how to assess and control the many possible error rates for concluding wrong hypotheses. In this article, we develop a general methodology for group sequential clinical trials with multiple primary endpoints. This method uses a global alpha‐spending function to control the overall type I error and a multiple decision rule to control error rates for concluding wrong alternative hypotheses. The method is demonstrated with two simulated examples based on the MERIT‐HF study.