Futility Interim Analysis Based on Probability of Success Using a Surrogate Endpoint

Author:

Fougeray Ronan1,Vidot Loïck1,Ratta Marco2ORCID,Teng Zhaoyang3,Skanji Donia1,Saint‐Hilary Gaëlle24ORCID

Affiliation:

1. Institut de Recherches Internationales Servier (IRIS) Gif‐sur‐Yvette France

2. Politecnico di Torino Torino Italy

3. Servier Boston USA

4. Saryga Tournus France

Abstract

ABSTRACTIn clinical trials with time‐to‐event data, the evaluation of treatment efficacy can be a long and complex process, especially when considering long‐term primary endpoints. Using surrogate endpoints to correlate the primary endpoint has become a common practice to accelerate decision‐making. Moreover, the ethical need to minimize sample size and the practical need to optimize available resources have encouraged the scientific community to develop methodologies that leverage historical data. Relying on the general theory of group sequential design and using a Bayesian framework, the methodology described in this paper exploits a documented historical relationship between a clinical “final” endpoint and a surrogate endpoint to build an informative prior for the primary endpoint, using surrogate data from an early interim analysis of the clinical trial. The predictive probability of success of the trial is then used to define a futility‐stopping rule. The methodology demonstrates substantial enhancements in trial operating characteristics when there is a good agreement between current and historical data. Furthermore, incorporating a robust approach that combines the surrogate prior with a vague component mitigates the impact of the minor prior‐data conflicts while maintaining acceptable performance even in the presence of significant prior‐data conflicts. The proposed methodology was applied to design a Phase III clinical trial in metastatic colorectal cancer, with overall survival as the primary endpoint and progression‐free survival as the surrogate endpoint.

Funder

Incorporated Research Institutions for Seismology

Publisher

Wiley

Reference54 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3