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 Medjournal_title
Statistics in medicineauthors
Sun L,Wan Ydoi
10.1002/sim.7673subject
Has Abstractpub_date
2018-08-15 00:00:00pages
2690-2699issue
18eissn
0277-6715issn
1097-0258journal_volume
37pub_type
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