医学
医学物理学
背景(考古学)
临床试验
缺少数据
桥接(联网)
病理
计算机科学
机器学习
计算机网络
生物
古生物学
作者
Jonathan Denne,Gene Pennello,Luping Zhao,Shao-Chun Chang,Sandra K. Althouse
标识
DOI:10.1080/19466315.2013.852618
摘要
AbstractIn the United States, regulatory approval of a therapy that is tailored to a subpopulation may require the coapproval of a companion in vitro diagnostic (IVD) tool for identifying that subpopulation. Unfortunately, for many reasons, development of the companion IVD may lag such that it is unavailable during a pivotal clinical trial of the therapy. Instead, a laboratory-developed test (LDT) may be used on clinical trial specimens to identify the subpopulation on whom to evaluate the therapy. However, remaining specimen material is saved so that when the companion IVD is ready for market, the specimens can be retested, in an effort to "bridge" from the LDT to the IVD. Unfortunately, retest results can be missing or invalid because some subjects lack remaining specimen material or because what remains is unevaluable (e.g., due to insufficient specimen material, inadequate specimen quality). We frame the bridging analysis problem as one of estimating drug efficacy in the IVD-defined subpopulation. We develop a closed-form approach, as well as approaches based on multiple imputation and bootstrapping to address the missing data problem. We discuss this in the context of a case study involving a recent submission and approval in the United States of a drug and IVD in oncology.Key Words: AgreementCompanion diagnosticConcordanceOncologyPharmacogenomicsPredictive biomarker AcknowledgmentsThe authors thank Donna Roscoe and Jingjing Ye for their reviews and helpful comments, which improved this article.
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