Trial Designs for Personalizing Cancer Care: A Systematic Review and Classification

Clin Cancer Res. 2013 Sep 1;19(17):4578-88. doi: 10.1158/1078-0432.CCR-12-3722. Epub 2013 Jun 20.

Abstract

There is an increasing interest in the evaluation of prognostic and predictive biomarkers for personalizing cancer care. The literature on the trial designs for evaluation of these markers is diverse and there is no consensus in the classification or nomenclature. We set this study to review the literature systematically, to identify the proposed trial designs, and to develop a classification scheme. We searched MEDLINE, EMBASE, Cochrane Methodology Register, and MathSciNet up to January 2013 for articles describing these trial designs. In each eligible article, we identified the trial designs presented and extracted the term used for labeling the design, components of patient flow (marker status of eligible participants, intervention, and comparator), study questions, and analysis plan. Our search strategy resulted in 88 eligible articles, wherein 315 labels had been used by authors in presenting trial designs; 134 of these were unique. By analyzing patient flow components, we could classify the 134 unique design labels into four basic patient flow categories, which we labeled with the most frequently used term: single-arm, enrichment, randomize-all, and biomarker-strategy designs. A fifth category consists of combinations of the other four patient flow categories. Our review showed that a considerable number of labels has been proposed for trial designs evaluating prognostic and predictive biomarkers which, based on patient flow elements, can be classified into five basic categories. The classification system proposed here could help clinicians and researchers in designing and interpreting trials evaluating predictive biomarkers, and could reduce confusion in labeling and reporting.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Clinical Trials as Topic
  • Humans
  • Neoplasms / drug therapy*
  • Neoplasms / genetics
  • Neoplasms / pathology
  • Precision Medicine*
  • Research Design*