An alternative method to analyse the Biomarker-strategy design

Kunz, Cornelia Ursula and Jaki, Thomas Friedrich and Stallard, Nigel (2018) An alternative method to analyse the Biomarker-strategy design. Statistics in Medicine, 37 (30). pp. 4636-4651. ISSN 0277-6715

[img]
Preview
PDF (Kunz_BMstrategy_submitted)
Kunz_BMstrategy_submitted.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (152kB)

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 novel 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. Application of the novel method is illustrated using a real data example.

Item Type:
Journal Article
Journal or Publication Title:
Statistics in Medicine
Additional Information:
This is an Accepted Manuscript of an article published by Taylor & Francis in Statistics in Medicine. 2018, available online:http://wwww.tandfonline.com/10.1002/sim.7940
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
126479
Deposited By:
Deposited On:
20 Jul 2018 14:10
Refereed?:
Yes
Published?:
Published
Last Modified:
18 Sep 2020 04:19