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Randomized reverse marker strategy design for prospective biomarker validation
Author(s) -
Eng Kevin H.
Publication year - 2014
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6146
Subject(s) - context (archaeology) , computer science , parametric statistics , biomarker , research design , machine learning , medicine , medical physics , statistics , mathematics , paleontology , biochemistry , chemistry , biology
We describe a novel study design for validating marker‐based treatment strategies meant to select among possible therapeutic options using a biologic marker. Studying existing designs in realistic scenarios, we demonstrate that this design is more than four times more efficient for testing the interaction between a marker and its intended treatment. Our analysis employs a simple parametric framework that uncovers systematic biases in currently proposed designs and suggests how they may be accommodated or enumerated. In the context of markers for choosing a treatment for recurrent ovarian cancer, our proposal requires sample sizes on the order of recently completed phases II and III studies making validation studies for this clinical decision scenario viable. © 2014 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.