Characterizing expected benefits of biomarkers in treatment selection.

TitleCharacterizing expected benefits of biomarkers in treatment selection.
Publication TypeJournal Article
Year of Publication2015
AuthorsHuang, Ying, Eric B. Laber, and Holly Janes
JournalBiostatistics
Volume16
Issue2
Pagination383-99
Date Published2015 Apr
ISSN1468-4357
KeywordsBiomarkers, Clinical Decision-Making, Diabetes Mellitus, Glycated Hemoglobin A, Humans, Models, Statistical, Randomized Controlled Trials as Topic
Abstract

Biomarkers associated with heterogeneity in subject responses to treatment hold potential for treatment selection. In practice, the decision regarding whether to adopt a treatment-selection marker depends on the effect of using the marker on the rate of targeted disease and on the cost associated with treatment. We propose an expected benefit measure that incorporates both effects to quantify a marker's treatment-selection capacity. This measure builds upon an existing decision-theoretic framework, but is expanded to account for the fact that optimal treatment absent marker information varies with the cost of treatment. In addition, we establish upper and lower bounds on the expected benefit for a perfect treatment-selection rule which provides the basis for a standardized expected benefit measure. We develop model-based estimators for these measures in a randomized trial setting and evaluate their asymptotic properties. An adaptive bootstrap confidence interval is proposed for inference in the presence of non-regularity. Alternative estimators robust to risk model misspecification are also investigated. We illustrate our methods using the Diabetes Control and Complications Trial where we evaluate the expected benefit of baseline hemoglobin A1C in selecting diabetes treatment.

DOI10.1093/biostatistics/kxu039
Alternate JournalBiostatistics
Original PublicationCharacterizing expected benefits of biomarkers in treatment selection.
PubMed ID25190512
PubMed Central IDPMC4786637
Grant ListR01 GM106177-01 / GM / NIGMS NIH HHS / United States
R01 GM106177 / GM / NIGMS NIH HHS / United States
U24 CA086368 / CA / NCI NIH HHS / United States
R01 GM054438 / GM / NIGMS NIH HHS / United States
R01 CA152089 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
P01 CA053996 / CA / NCI NIH HHS / United States
U01 CA086368 / CA / NCI NIH HHS / United States
Project: