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Analysis of randomized comparative clinical trial data for personalized treatment selections.


ABSTRACT: Suppose that under the conventional randomized clinical trial setting, a new therapy is compared with a standard treatment. In this article, we propose a systematic, 2-stage estimation procedure for the subject-level treatment differences for future patient's disease management and treatment selections. To construct this procedure, we first utilize a parametric or semiparametric method to estimate individual-level treatment differences, and use these estimates to create an index scoring system for grouping patients. We then consistently estimate the average treatment difference for each subgroup of subjects via a nonparametric function estimation method. Furthermore, pointwise and simultaneous interval estimates are constructed to make inferences about such subgroup-specific treatment differences. The new proposal is illustrated with the data from a clinical trial for evaluating the efficacy and toxicity of a 3-drug combination versus a standard 2-drug combination for treating HIV-1-infected patients.

SUBMITTER: Cai T 

PROVIDER: S-EPMC3062150 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Analysis of randomized comparative clinical trial data for personalized treatment selections.

Cai Tianxi T   Tian Lu L   Wong Peggy H PH   Wei L J LJ  

Biostatistics (Oxford, England) 20100928 2


Suppose that under the conventional randomized clinical trial setting, a new therapy is compared with a standard treatment. In this article, we propose a systematic, 2-stage estimation procedure for the subject-level treatment differences for future patient's disease management and treatment selections. To construct this procedure, we first utilize a parametric or semiparametric method to estimate individual-level treatment differences, and use these estimates to create an index scoring system f  ...[more]

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