Conditional power and predictive power based on right censored data with supplementary auxiliary information.

Abstract:

:Conditional power and predictive power provide estimates of the probability of success at the end of the trial based on the information from the interim analysis. The observed value of the time to event endpoint at the interim analysis could be biased for the true treatment effect due to early censoring, leading to a biased estimate of conditional power and predictive power. In such cases, the estimates and inference for this right censored primary endpoint are enhanced by incorporating a fully observed auxiliary variable. We assume a bivariate normal distribution of the transformed primary variable and a correlated auxiliary variable. Simulation studies are conducted that not only shows enhanced conditional power and predictive power but also can provide the framework for a more efficient futility interim analysis in terms of an improved accuracy in estimator, a smaller inflation in type II error and an optimal timing for such analysis. We also illustrated the new approach by a real clinical trial example.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Sun L,Wan Y

doi

10.1002/sim.7673

subject

Has Abstract

pub_date

2018-08-15 00:00:00

pages

2690-2699

issue

18

eissn

0277-6715

issn

1097-0258

journal_volume

37

pub_type

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