Adaptive Designs for Two Candidate Primary Time-to-Event Endpoints

TY - JOUR

T1 - Adaptive Designs for Two Candidate Primary Time-to-Event Endpoints

AU - Rauch, Geraldine

AU - Schüler, S

AU - Wirths, M

AU - Englert, S

AU - Kieser, M

N1 - Copyright © 2016 John Wiley & Sons, Ltd.

PY - 2016/6/2

Y1 - 2016/6/2

N2 - In clinical trials, the choice of an adequate primary endpoint is often difficult. Besides its clinical relevance,the endpoint must be measurabl ewithin reasonable time and must allow differentiating between the treatments.Often, the most relevant endpoint is ‘’time-to-death,” but if the overall survival prognosis is good, only a few deaths are observed during the study duration. A possible solution is to use surrogate endpoints instead. However, various examples from the literature demonstrate that surrogates do not always perform as intended. Sometimes, the surrogate effect is smaller than for the original endpoint, or the latter shows a higher effect than anticipated so using the surrogate is not reasonable. In this work, different adaptive design strategies for two candidate endpoints are proposed to solve these problems. The idea is to base the efficacy proof on the significance of at least one endpoint. At an interim analysis, both candidates are evaluated. If it is not possible to stop the study early, the sample size is recalculated based on the more promising endpoint. The new methods are illustrated by a clinical study example and compared in terms of power and sample size using Monte Carlo simulations. The software code is provided as supplementary material.

AB - In clinical trials, the choice of an adequate primary endpoint is often difficult. Besides its clinical relevance,the endpoint must be measurabl ewithin reasonable time and must allow differentiating between the treatments.Often, the most relevant endpoint is ‘’time-to-death,” but if the overall survival prognosis is good, only a few deaths are observed during the study duration. A possible solution is to use surrogate endpoints instead. However, various examples from the literature demonstrate that surrogates do not always perform as intended. Sometimes, the surrogate effect is smaller than for the original endpoint, or the latter shows a higher effect than anticipated so using the surrogate is not reasonable. In this work, different adaptive design strategies for two candidate endpoints are proposed to solve these problems. The idea is to base the efficacy proof on the significance of at least one endpoint. At an interim analysis, both candidates are evaluated. If it is not possible to stop the study early, the sample size is recalculated based on the more promising endpoint. The new methods are illustrated by a clinical study example and compared in terms of power and sample size using Monte Carlo simulations. The software code is provided as supplementary material.

U2 - 10.1080/19466315.2016.1143391

DO - 10.1080/19466315.2016.1143391

M3 - SCORING: Journal article

C2 - 28028823

VL - 8

SP - 207

EP - 216

JO - STAT BIOPHARM RES

JF - STAT BIOPHARM RES

SN - 1946-6315

IS - 2

ER -