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Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint.

Publication ,  Journal Article
Michiels, S; Potthoff, RF; George, SL
Published in: Stat Med
June 15, 2011

The recent revolution in genomics and the advent of targeted therapies have increased interest in biomarker-defined subgroups of patients who respond to therapy or exhibit specific toxicities. Such biomarker-defined subgroups are also being investigated for non-targeted therapies (e.g. chemotherapy and statins). However, even when the targeting pathway has been identified, a broadly available test to identify the appropriate subgroup will rarely exist prior to the launch of the pivotal phase III trial. Our aim in this paper is to provide guidance for the analysis of a phase III clinical trial with a survival endpoint, in order to ascertain whether a therapy is more effective in the biomarker-positive patients as compared with biomarker-negative patients, when the trial is conducted on the entire population and when there are multiple candidate biomarkers. We studied treatment-by-biomarker interactions in a Weibull regression model. Different permutation procedures, using single-biomarker statistics and novel composite statistics, are proposed in order to control the family-wise error rate accounting for dependence structures among the biomarkers. A simulation study was performed to compare the operational characteristics of the permutation tests under different scenarios. The tests were applied to a phase III trial of adjuvant chemotherapy in early breast cancer, for which 10 biomarkers were measured in tumor samples from 798 patients. These permutation tests can be applied to retrospective biomarker studies and to prospective phase III trials of new drugs for which a few clues are known about the targeting pathway at the start of the trial.

Duke Scholars

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

June 15, 2011

Volume

30

Issue

13

Start / End Page

1502 / 1518

Location

England

Related Subject Headings

  • Survival Analysis
  • Statistics, Nonparametric
  • Statistics & Probability
  • Models, Statistical
  • Humans
  • Female
  • Endpoint Determination
  • Clinical Trials, Phase III as Topic
  • Breast Neoplasms
  • Biomarkers, Tumor
 

Citation

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MLA
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Michiels, S., Potthoff, R. F., & George, S. L. (2011). Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint. Stat Med, 30(13), 1502–1518. https://doi.org/10.1002/sim.4022
Michiels, Stefan, Richard F. Potthoff, and Stephen L. George. “Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint.Stat Med 30, no. 13 (June 15, 2011): 1502–18. https://doi.org/10.1002/sim.4022.
Michiels S, Potthoff RF, George SL. Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint. Stat Med. 2011 Jun 15;30(13):1502–18.
Michiels, Stefan, et al. “Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint.Stat Med, vol. 30, no. 13, June 2011, pp. 1502–18. Pubmed, doi:10.1002/sim.4022.
Michiels S, Potthoff RF, George SL. Multiple testing of treatment-effect-modifying biomarkers in a randomized clinical trial with a survival endpoint. Stat Med. 2011 Jun 15;30(13):1502–1518.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

June 15, 2011

Volume

30

Issue

13

Start / End Page

1502 / 1518

Location

England

Related Subject Headings

  • Survival Analysis
  • Statistics, Nonparametric
  • Statistics & Probability
  • Models, Statistical
  • Humans
  • Female
  • Endpoint Determination
  • Clinical Trials, Phase III as Topic
  • Breast Neoplasms
  • Biomarkers, Tumor