Literature DB >> 24935478

Stratification and partial ascertainment of biomarker value in biomarker-driven clinical trials.

Richard Simon1.   

Abstract

This article examines the role of stratification of treatment assignment with regard to biomarker value in clinical trials that accept biomarker-positive and -negative patients but have a primary objective of evaluating treatment effect separately for the marker-positive subset. It also examines the issue of incomplete ascertainment of biomarker value and how this affects inference about treatment effect for the biomarker-positive subset of patients. I find that stratifying the randomization for the biomarker ensures that all patients will have tissue collected but is not necessary for the validity of inference for the biomarker-positive subset if there is complete ascertainment. If there is not complete ascertainment of biomarker values, it is important to establish that ascertainment is independent of treatment assignment. Having a large proportion of cases with biomarker ascertainment is not necessary for establishing internal validity of the treatment evaluation in biomarker-positive patients; independence of ascertainment and treatment is the important factor. Having a large proportion of cases with biomarker ascertainment makes it more likely that biomarker-positive patients with ascertainment are representative of the biomarker-positive patients in the clinical trial (with and without ascertainment), but since the patients in the clinical trial are a convenience sample of the population of patients potentially eligible for the trial, requiring a large proportion of cases with ascertainment does not facilitate generalizability of conclusions.

Entities:  

Keywords:  Ascertainment; Biomarker; Clinical trials; Stratification

Mesh:

Substances:

Year:  2014        PMID: 24935478      PMCID: PMC4130784          DOI: 10.1080/10543406.2014.931411

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  13 in total

1.  Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients.

Authors:  Boris Freidlin; Richard Simon
Journal:  Clin Cancer Res       Date:  2005-11-01       Impact factor: 12.531

2.  Use of archived specimens in evaluation of prognostic and predictive biomarkers.

Authors:  Richard M Simon; Soonmyung Paik; Daniel F Hayes
Journal:  J Natl Cancer Inst       Date:  2009-10-08       Impact factor: 13.506

3.  Randomized clinical trials. Perspectives on some recent ideas.

Authors:  D P Byar; R M Simon; W T Friedewald; J J Schlesselman; D L DeMets; J H Ellenberg; M H Gail; J H Ware
Journal:  N Engl J Med       Date:  1976-07-08       Impact factor: 91.245

4.  Statistical considerations in evaluating pharmacogenomics-based clinical effect for confirmatory trials.

Authors:  Sue-Jane Wang; Robert T O'Neill; Hm James Hung
Journal:  Clin Trials       Date:  2010-07-01       Impact factor: 2.486

5.  Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial.

Authors:  S J Pocock; R Simon
Journal:  Biometrics       Date:  1975-03       Impact factor: 2.571

6.  Using Randomization Tests to Preserve Type I Error With Response-Adaptive and Covariate-Adaptive Randomization.

Authors:  Richard Simon; Noah Robin Simon
Journal:  Stat Probab Lett       Date:  2011-07       Impact factor: 0.870

7.  Propensity score matching in randomized clinical trials.

Authors:  Zhenzhen Xu; John D Kalbfleisch
Journal:  Biometrics       Date:  2010-09       Impact factor: 2.571

8.  Adaptive clinical trial designs for simultaneous testing of matched diagnostics and therapeutics.

Authors:  Howard I Scher; Shelley Fuld Nasso; Eric H Rubin; Richard Simon
Journal:  Clin Cancer Res       Date:  2011-11-01       Impact factor: 12.531

9.  Randomized phase III clinical trial designs for targeted agents.

Authors:  Antje Hoering; Mike Leblanc; John J Crowley
Journal:  Clin Cancer Res       Date:  2008-07-15       Impact factor: 12.531

10.  Design and analysis of randomized clinical trials requiring prolonged observation of each patient. I. Introduction and design.

Authors:  R Peto; M C Pike; P Armitage; N E Breslow; D R Cox; S V Howard; N Mantel; K McPherson; J Peto; P G Smith
Journal:  Br J Cancer       Date:  1976-12       Impact factor: 7.640

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