Identifying optimal biomarker combinations for treatment selection through randomized controlled trials.

ABSTRACT:

Background/aims

Biomarkers associated with treatment-effect heterogeneity can be used to make treatment recommendations that optimize individual clinical outcomes. To accomplish this, statistical methods are needed to generate marker-based treatment-selection rules that can most effectively reduce the population burden due to disease and treatment. Compared to the standard approach of risk modeling to derive treatment-selection rules, a more robust approach is to directly minimize an unbiased estimate of total disease and treatment burden among a pre-specified class of rules. This problem is one of minimizing a weighted sum of 0-1 loss function, which is computationally challenging to solve due to the nonsmoothness of 0-1 loss. Huang and Fong, among others, proposed a method that u

SUBMITTER: Huang Y 

PROVIDER: S-EPMC4506270 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature