Literature DB >> 28838813

On study designs and hypotheses for clinical trials with predictive biomarkers.

Weichung J Shih1, Yong Lin2.   

Abstract

Recent interest in conducting clinical trials with predictive biomarkers has generated research in comparing relative efficiency of different trial designs. We find these comparisons of efficiency mostly misleading since they are based on different hypotheses. In this paper, we discuss several commonly used trial designs and consider the hypotheses that each design is capable to address. We first consider the ideal situation of no classification errors, then the more realistic situation where marker assay's sensitivity, specificity and the rule of classification are imperfect. We pay special attention to the differences between treatment utility versus absolute treatment effect, and marker by treatment interaction versus marker utility.
Copyright © 2017 Elsevier Inc. All rights reserved.

Keywords:  Efficiency; Hypothesis; Precision medicine; Randomization; Stratification

Mesh:

Substances:

Year:  2017        PMID: 28838813     DOI: 10.1016/j.cct.2017.08.014

Source DB:  PubMed          Journal:  Contemp Clin Trials        ISSN: 1551-7144            Impact factor:   2.226


  2 in total

1.  Relative efficiency of precision medicine designs for clinical trials with predictive biomarkers.

Authors:  Weichung Joe Shih; Yong Lin
Journal:  Stat Med       Date:  2017-12-04       Impact factor: 2.373

2.  Two-stage enrichment clinical trial design with adjustment for misclassification in predictive biomarkers.

Authors:  Yong Lin; Weichung J Shih; Shou-En Lu
Journal:  Stat Med       Date:  2019-10-17       Impact factor: 2.373

  2 in total

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