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An alternative method to analyse the biomarker-strategy design

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Kunz, Cornelia Ursula, Jaki, Thomas and Stallard, Nigel (2018) An alternative method to analyse the biomarker-strategy design. Statistics in Medicine, 37 (30). pp. 4636-4651. doi:10.1002/sim.7940

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Official URL: http://dx.doi.org/10.1002/sim.7940

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Abstract

Recent developments in genomics and proteomics enable the discovery of biomarkers that allow identification of subgroups of patients responding well to a treatment. One currently used clinical trial design incorporating a predictive biomarker is the so-called biomarker strategy design (or marker-based strategy design). Conventionally, the results from this design are analysed by comparing the mean of the biomarker-led arm with the mean of the randomised arm. Several problems regarding the analysis of the data obtained from this design have been identified in the literature. In this paper, we show how these problems can be resolved if the sample sizes in the subgroups fulfil the specified orthogonality
condition.We also propose a different analysis strategy that allows definition of test statistics for the biomarker-by-treatment interaction effect as well as for the classical treatment effect and the biomarker effect. We derive equations for the sample size calculation for the case of perfect and imperfect biomarker assays. We also show that the often used 1:1 randomisation does not necessarily lead to the smallest sample size. In addition, we provide point estimators and confidence intervals for the treatment effects in the subgroups. Application of our method is illustrated using a real data example.

Item Type: Journal Article
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine > Warwick Medical School > Health Sciences
Faculty of Medicine > Warwick Medical School > Health Sciences > Statistics and Epidemiology
Faculty of Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Biochemical markers -- Diagnostic use, Clinical trials -- Design, Personalized medicine
Journal or Publication Title: Statistics in Medicine
Publisher: John Wiley & Sons Ltd.
ISSN: 0277-6715
Official Date: 30 December 2018
Dates:
DateEvent
30 December 2018Published
9 September 2018Available
20 July 2018Accepted
Volume: 37
Number: 30
Page Range: pp. 4636-4651
DOI: 10.1002/sim.7940
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
NIHR-SRF-2015-08-001[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
MR/M014525/1[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/M005755/1[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
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