Literature DB >> 7548701

Sequential monitoring of survival data with the Wilcoxon statistic.

K K Lan1, W F Rosenberger, J M Lachin.   

Abstract

When a spending function is used in sequential data monitoring of a clinical trial, it is important to know the information fraction at the times of interim analysis. In a maximum duration designed study, the information fraction is unknown when data are monitored, and it has to be estimated. The modified Wilcoxon statistic developed by Peto and Peto and modified by Prentice is often used to compare two survival curves in a clinical trial. We give guidelines for estimating the information fraction in a maximum duration trial when this statistic is employed. When there is a relatively low event rate or the survival time is approximately exponential, the information fraction for the Peto-Peto-Prentice Wilcoxon statistic is very close to that of the popular logrank statistic. In other cases, it would be helpful to estimate the information fraction as a function of elapsed calendar time. We discuss both group sequential and continuous monitoring.

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Year:  1995        PMID: 7548701

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  3 in total

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2.  Flexibly Monitoring Group Sequential Survival Trials When Testing is Based Upon a Weighted Log-Rank Statistic.

Authors:  Sean S Brummel; Daniel L Gillen
Journal:  Seq Anal       Date:  2014-01-30       Impact factor: 0.927

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Journal:  CNS Drugs       Date:  2013-12       Impact factor: 5.749

  3 in total

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