The Cross-Validated Adaptive Signature Design

• Published in: Clinical cancer research Vol. 16; no. 2; pp. 691 - 698
• Main Authors: Freidlin, Boris, Jiang, Wenyu, Simon, Richard
• Format: Journal Article
• Language: English
• Published: United States American Association for Cancer Research 15-01-2010
• Subjects: Adaptation, Physiological - drug effects; Antineoplastic Agents - pharmacology; Antineoplastic Agents - therapeutic use; Biomarkers, Pharmacological - analysis; Breast Neoplasms - diagnosis; Breast Neoplasms - drug therapy; Breast Neoplasms - genetics; clinical trial; Clinical Trials, Phase III as Topic - methods; Computer Simulation; cross-validation; Decision Support Techniques; Drug Design; Drug Resistance, Neoplasm - genetics; Female; Gene Expression Profiling; genomic classifier; Humans; Microarray; Neoadjuvant Therapy; Patient Selection; Randomized Controlled Trials as Topic; Research Design; sensitive subpopulation; Validation Studies as Topic
• ISSN: 1078-0432; 1557-3265
• DOI: 10.1158/1078-0432.CCR-09-1357

Purpose: Many anticancer therapies benefit only a subset of treated patients and may be overlooked by the traditional broad eligibility
approach to design phase III clinical trials. New biotechnologies such as microarrays can be used to identify the patients
that are most likely to benefit from anticancer therapies. However, due to the high-dimensional nature of the genomic data,
developing a reliable classifier by the time the definitive phase III trail is designed may not be feasible.
Experimental Design: Previously, Freidlin and Simon ( Clinical Cancer Research , 2005) introduced the adaptive signature design that combines a prospective development of a sensitive patient classifier
and a properly powered test for overall effect in a single pivotal trial. In this article, we propose a cross-validation extension
of the adaptive signature design that optimizes the efficiency of both the classifier development and the validation components
of the design.
Results: The new design is evaluated through simulations and is applied to data from a randomized breast cancer trial.
Conclusion: The cross-validation approach is shown to considerably improve the performance of the adaptive signature design. We also
describe approaches to the estimation of the treatment effect for the identified sensitive subpopulation. Clin Cancer Res;
16(2); 691–8