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Testing of evaluation bias for progression free survival endpoint in oncology clinical trials
Author(s) -
Sun Yan,
Wu Wenting,
Sargent Daniel
Publication year - 2016
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6963
Subject(s) - sample size determination , progression free survival , clinical trial , clinical endpoint , computer science , type i and type ii errors , audit , medicine , index (typography) , oncology , medical physics , statistics , overall survival , mathematics , accounting , business , world wide web
Progression‐free survival is an increasingly popular end point in oncology clinical trials. A complete blinded independent central review (BICR) is often required by regulators in an attempt to reduce the bias in progression‐free survival (PFS) assessment. In this paper, we propose a new methodology that uses a sample‐based BICR as an audit tool to decide whether a complete BICR is needed. More specifically, we propose a new index, the differential risk, to measure the reading discordance pattern, and develop a corresponding hypothesis testing procedure to decide whether the bias in local evaluation is acceptable. Simulation results demonstrate that our new index is sensitive to the change of discordance pattern; type I error is well controlled in the hypothesis testing procedure, and the calculated sample size provides the desired power. Copyright © 2016 John Wiley & Sons, Ltd.