Design and analysis of clinical trials in the presence of delayed treatment effect

Stat Med. 2016 May 20;35(11):1774-9. doi: 10.1002/sim.6889. Epub 2016 Feb 2.

Abstract

In clinical trials with survival endpoint, it is common to observe an overlap between two Kaplan-Meier curves of treatment and control groups during the early stage of the trials, indicating a potential delayed treatment effect. Formulas have been derived for the asymptotic power of the log-rank test in the presence of delayed treatment effect and its accompanying sample size calculation. In this paper, we first reformulate the alternative hypothesis with the delayed treatment effect in a rescaled time domain, which can yield a simplified sample size formula for the log-rank test in this context. We further propose an intersection-union test to examine the efficacy of treatment with delayed effect and show it to be more powerful than the log-rank test. Simulation studies are conducted to demonstrate the proposed methods.

Keywords: lagged treatment effect; log-rank test; power calculation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Clinical Trials as Topic*
  • Computer Simulation
  • Endpoint Determination
  • Epidemiologic Research Design*
  • Humans
  • Models, Statistical*
  • Survival Analysis
  • Time Factors
  • Treatment Outcome