A Targeted Simulation-Extrapolation Method for Evaluating Biomarkers Based on New Technologies in Precision Medicine

• Activity Number: 109 - Innovative Approaches in Biomarkers Discovery and Subgroup Analyses
• Type: Contributed
• Date/Time: Monday, August 8, 2022 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Dong Wang* and Sue-Jane Wang and Joshua Xu and Samir Lababidi
• Companies: National Center for Toxicological Research/FDA and FDA and National Center for Toxicological Research/FDA and Office of Chief Scientist/FDA
• Keywords: biomarker; measurement error; misclassification; next generation sequencing; SIMEX

Abstract

New technologies for novel biomarkers have transformed the field of precision medicine. However, in applications such as liquid biopsy for early tumor detection, the misclassification rates of next generation sequencing and other technologies have become an unavoidable feature of biomarker development. In this article, we describe an approach based on an extended version of simulation extrapolation (SIMEX) to project the performance of biomarkers measured with varying misclassification rates due to different technological or application settings when experimental results are only available from one specific setting. Through simulation studies for logistic regression and proportional hazards models, we show that our proposed method can be used to project the biomarker performance with good precision when switching from one to another technology or application setting. Similar to the original SIMEX model, the proposed method can be implemented with existing software in a straightforward manner. A data analysis example is also presented using a lung cancer data set and performance metrics for two gene panel based biomarkers.