Sequential monitoring of survival data with the Wilcoxon statistic.
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.
Lan
K K
KK
Department of Statistics, George Washington University, Rockville, Maryland 20852, USA.
Rosenberger
W F
WF
Lachin
J M
JM
D001699:Biometry; D002316:Cardiotonic Agents / Q000627:therapeutic use*; D002986:Clinical Trials as Topic / Q000379:methods*; D005500:Follow-Up Studies; D006333:Heart Failure / Q000188:drug therapy* / Q000401:mortality; D006801:Humans; D015993:Life Tables; D015233:Models, Statistical; D011719:Pyrazines; D011804:Quinolines / Q000627:therapeutic use*; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design; D016019:Survival Analysis; D013997:Time Factors
D002316:Cardiotonic Agents; D011719:Pyrazines; D011804:Quinolines; C041667:vesnarinone