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Updated: Mar 22, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Testing of evaluation bias for progression free survival endpoint in oncology clinical trials
Yan Sun1, Wenting Wu2, Daniel Sargent3
1University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL, 60607, U.S.A.
Abstract:
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.
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