Review
. 2005 Mar;23(9).
doi: 10.1200/JCO.2005.01.112.

Clinical trial designs for predictive marker validation in cancer treatment trials

Daniel J Sargent 1 Barbara A Conley  Carmen Allegra  Laurence Collette  
Affiliations
  • PMID: 15774793
  •     136 citations

Abstract

Current staging and risk-stratification methods in oncology, while helpful, fail to adequately predict malignancy aggressiveness and/or response to specific treatment. Increased knowledge of cancer biology is generating promising marker candidates for more accurate diagnosis, prognosis assessment, and therapeutic targeting. To apply these exciting results to maximize patient benefit, a disciplined application of well-designed clinical trials for assessing the utility of markers should be used. In this article, we first review the major issues to consider when designing a clinical trial assessing the usefulness of a predictive marker. We then present two classes of clinical trial designs: the Marker by Treatment Interaction Design and the Marker-Based Strategy Design. In the first design, we assume that the marker splits the population into groups in which the efficacy of a particular treatment will differ. This design can be viewed as a classical randomized clinical trial with upfront stratification for the marker. In the second design, after the marker status is known, each patient is randomly assigned either to have therapy determined by their marker status or to receive therapy independent of marker status. The predictive value of the marker is assessed by comparing the outcome of all patients in the marker-based arm to that of all of the patients in the non-marker-based arm. We present detailed sample size calculations for a specific clinical scenario. We discuss the advantages and disadvantages of the two trial designs and their appropriateness to specific clinical situations to assist investigators seeking to design rigorous, marker-based clinical trials.

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Biometrics, 2016 Oct 25; 73(2). PMID: 27775814    Free PMC article.
Biomarker-Guided Non-Adaptive Trial Designs in Phase II and Phase III: A Methodological Review.
Miranta Antoniou, Ruwanthi Kolamunnage-Dona, Andrea L Jorgensen.
J Pers Med, 2017 Jan 27; 7(1). PMID: 28125057    Free PMC article.
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Beyond Correlations, Sensitivities, and Specificities: A Roadmap for Demonstrating Utility of Advanced Imaging in Oncology Treatment and Clinical Trial Design.
Erich P Huang, Frank I Lin, Lalitha K Shankar.
Acad Radiol, 2017 May 01; 24(8). PMID: 28456570    Free PMC article.
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Inter-alpha Inhibitor H4 as a Potential Biomarker Predicting the Treatment Outcomes in Patients with Hepatocellular Carcinoma.
Eun-Jung Lee, Seung-Hyun Yang, +6 authors, Jinsil Seong.
Cancer Res Treat, 2017 Jul 21; 50(3). PMID: 28724284    Free PMC article.
On Enrichment Strategies for Biomarker Stratified Clinical Trials.
Xiaofei Wang, Jingzhu Zhou, Ting Wang, Stephen L George.
J Biopharm Stat, 2017 Sep 22; 28(2). PMID: 28933670    Free PMC article.
Case-only approach to identifying markers predicting treatment effects on the relative risk scale.
James Y Dai, C Jason Liang, +2 authors, Holly Janes.
Biometrics, 2017 Sep 30; 74(2). PMID: 28960244    Free PMC article.
Chemosensitivity-directed therapy compared to dacarbazine in chemo-naive advanced metastatic melanoma: a multicenter randomized phase-3 DeCOG trial.
Selma Ugurel, Carmen Loquai, +18 authors, Jürgen C Becker.
Oncotarget, 2017 Nov 05; 8(44). PMID: 29100289    Free PMC article.
Relative efficiency of precision medicine designs for clinical trials with predictive biomarkers.
Weichung Joe Shih, Yong Lin.
Stat Med, 2017 Dec 06; 37(5). PMID: 29205435    Free PMC article.
Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting.
Vahé Asvatourian, Clélia Coutzac, +3 authors, Emilie Lanoy.
BMC Med Res Methodol, 2018 Jul 05; 18(1). PMID: 29969993    Free PMC article.
Auxiliary variable-enriched biomarker-stratified design.
Ting Wang, Xiaofei Wang, +2 authors, Stephen L George.
Stat Med, 2018 Sep 18; 37(30). PMID: 30221368    Free PMC article.
IHC Color Histograms for Unsupervised Ki67 Proliferation Index Calculation.
Rokshana S Geread, Peter Morreale, +4 authors, April Khademi.
Front Bioeng Biotechnol, 2019 Oct 22; 7. PMID: 31632956    Free PMC article.
Noncoding RNAs and Liquid Biopsy in Lung Cancer: A Literature Review.
Antonia Haranguș, Ioana Berindan-Neagoe, +2 authors, Mărioara Șimon.
Diagnostics (Basel), 2019 Dec 11; 9(4). PMID: 31818027    Free PMC article.
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An alternative method to analyse the biomarker-strategy design.
Cornelia Ursula Kunz, Thomas Jaki, Nigel Stallard.
Stat Med, 2018 Sep 28; 37(30). PMID: 30260533    Free PMC article.
Natural agents inhibit colon cancer cell proliferation and alter microbial diversity in mice.
Lulu Farhana, Sarah Sarkar, +5 authors, Adhip P N Majumdar.
PLoS One, 2020 Mar 21; 15(3). PMID: 32196510    Free PMC article.
Designing precision medicine trials to yield a greater population impact.
Ying-Qi Zhao, Michael L LeBlanc.
Biometrics, 2019 Oct 11; 76(2). PMID: 31598964    Free PMC article.
Pharmaceutical Advances and Proteomics Researches.
Ensieh KhalKhal, Mostafa Rezaei-Tavirani, Mohammad Rostamii-Nejad.
Iran J Pharm Res, 2020 Aug 18; 18(Suppl1). PMID: 32802089    Free PMC article.
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Phase III Precision Medicine Clinical Trial Designs That Integrate Treatment and Biomarker Evaluation.
Mei-Yin C Polley, Edward L Korn, Boris Freidlin.
JCO Precis Oncol, 2020 Sep 15; 3. PMID: 32923845    Free PMC article.
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• Pancho trial (p53-adapted neoadjuvant chemotherapy for resectable esophageal cancer) completed-mutation rate of the marker higher than expected.
Sonja Kappel-Latif, Johannes Zacherl, +23 authors, Pancho trialists and for the Medical University of Vienna p53research group.
Eur Surg, 2018 Dec 19; 50(4). PMID: 30559831    Free PMC article.
ctDNA and Adjuvant Therapy for Colorectal Cancer: Time to Re-Invent Our Treatment Paradigm.
Mahendra Naidoo, Peter Gibbs, Jeanne Tie.
Cancers (Basel), 2021 Jan 23; 13(2). PMID: 33477814    Free PMC article.
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