Subgroup detection and sample size calculation with proportional hazards regression for survival data.

TitleSubgroup detection and sample size calculation with proportional hazards regression for survival data.
Publication TypeJournal Article
Year of Publication2017
AuthorsKang, Suhyun, Wenbin Lu, and Rui Song
JournalStat Med
Volume36
Issue29
Pagination4646-4659
Date Published2017 Dec 20
ISSN1097-0258
KeywordsAcquired Immunodeficiency Syndrome, Algorithms, Clinical Trials as Topic, Computer Simulation, Control Groups, Humans, Propensity Score, Proportional Hazards Models, Regression Analysis, Sample Size, Statistics, Nonparametric, Survival Analysis
Abstract

In this paper, we propose a testing procedure for detecting and estimating the subgroup with an enhanced treatment effect in survival data analysis. Here, we consider a new proportional hazard model that includes a nonparametric component for the covariate effect in the control group and a subgroup-treatment-interaction effect defined by a change plane. We develop a score-type test for detecting the existence of the subgroup, which is doubly robust against misspecification of the baseline effect model or the propensity score but not both under mild assumptions for censoring. When the null hypothesis of no subgroup is rejected, the change-plane parameters that define the subgroup can be estimated on the basis of supremum of the normalized score statistic. The asymptotic distributions of the proposed test statistic under the null and local alternative hypotheses are established. On the basis of established asymptotic distributions, we further propose a sample size calculation formula for detecting a given subgroup effect and derive a numerical algorithm for implementing the sample size calculation in clinical trial designs. The performance of the proposed approach is evaluated by simulation studies. An application to an AIDS clinical trial data is also given for illustration.

DOI10.1002/sim.7441
Alternate JournalStat Med
Original PublicationSubgroup detection and sample size calculation with proportional hazards regression for survival data.
PubMed ID28791726
PubMed Central IDPMC5698151
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States