Interim analyses of survival data in cancer clinical trials.
It is common practice to undertake interim analyses of accumulating survival data in a cancer clinical trial while patient entry and/or follow-up is still in progress. The purpose of making an interim analysis is to stop the trial if a convincing treatment difference can be demonstrated. The main problem with repeated significance tests is that the more often one analyses accumulating data, the greater the probability of eventually obtaining a significant result, p < 0.05 say, even when there is in reality no treatment difference. To allow for repeated testing one must therefore choose a more stringent nominal significance level as a criterion for stopping the trial. Repeated significance tests are normally applied at equally spaced intervals, and the maximum number of tests is decided in advance. This paper presents and compares the properties of two simple and commonly applied strategies for undertaking interim analyses of accumulating survival data.
Skovlund
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Norwegian Cancer Society and Section of Medical Statistics, University of Oslo. eva.skovlund@klinmed.uio.no
D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D005500:Follow-Up Studies; D006801:Humans; D009369:Neoplasms / Q000401:mortality*; D018579:Patient Selection; D018401:Sample Size; D013223:Statistics as Topic; D013269:Stochastic Processes; D016019:Survival Analysis