Abstract
Companion diagnostic tests play an important role in precision medicine. With the advancement of new technologies, multiple companion diagnostic tests can be rapidly developed in multiple platforms and use different samples to select patients for new treatments. Analytically validated assays must be clinically evaluated before they can be implemented in patient management. The status quo design for validating candidate assays is to employ one candidate assay to select patients for new drug clinical trial and then further evaluate the 2nd candidate assay in a bridging study. We propose a new enrollment strategy that employs two assays to select patients. We then develop a bivariate Bayesian approach that enables the totality of data to be used in evaluating whether these assays can be used independently or in a composite procedure in selecting right patients for new treatment. We demonstrate through simulations that when proper priors are available, the Bayesian approach is superior to classical methods in terms of statistical power.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Richard M. Simon
Richard Simon holds a doctor of science degree in Applied Mathematics and Computer Science from Washington University in St. Louis, Missouri. He was formerly chief of the Biometric Research Branch at the National Cancer Institute in Bethesda, Maryland.
Songbai Wang
Songbai Wang holds a medical degree from Tongji Medical university (Wuhan, China) and a MSPH degree in biostatistics from University of South Florida (Tampa, Florida). his career includes employment at China-Japan Friendship Hospital (Beijing, China), University of Michigan Comprehensive Cancer Center (Ann Arbor, Michigan), Parexel International Corporation (San Diego, California), Gen-Probe Incorporated (San Diego, California) and Johnson & Johnson (New Jersey, USA and Beerse, Belgium). Dr. Wang is currently scientific director of Statistics and Advanced Analytics at Janssen Pharmaceutical Research and Development (Raritan, New Jersey).