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      Pivotal Evaluation of the Accuracy of a Biomarker Used for Classification or Prediction: Standards for Study Design

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          Abstract

          Research methods for biomarker evaluation lag behind those for evaluating therapeutic treatments. Although a phased approach to development of biomarkers exists and guidelines are available for reporting study results, a coherent and comprehensive set of guidelines for study design has not been delineated. We describe a nested case–control study design that involves prospective collection of specimens before outcome ascertainment from a study cohort that is relevant to the clinical application. The biomarker is assayed in a blinded fashion on specimens from randomly selected case patients and control subjects in the study cohort. We separately describe aspects of the design that relate to the clinical context, biomarker performance criteria, the biomarker test, and study size. The design can be applied to studies of biomarkers intended for use in disease diagnosis, screening, or prognosis. Common biases that pervade the biomarker research literature would be eliminated if these rigorous standards were followed.

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          Most cited references 23

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          Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

          A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cancer.
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            ICH Harmonised Tripartite Guideline. Statistical principles for clinical trials. International Conference on Harmonisation E9 Expert Working Group.

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              The statistical evaluation of medical tests for classification and prediction

               MS Pepe,  M Pepe,  NS Pepe (2003)
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                Author and article information

                Journal
                J Natl Cancer Inst
                jnci
                jnci
                JNCI Journal of the National Cancer Institute
                Oxford University Press
                0027-8874
                1460-2105
                15 October 2008
                15 October 2008
                15 October 2008
                15 October 2008
                : 100
                : 20
                : 1432-1438
                Affiliations
                Affiliations of authors: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (MSP, ZF, HJ, JDP); Department of Clinical Epidemiology, Academic Medical Center, Amsterdam, The Netherlands (PMB)
                Author notes
                Correspondence to: Margaret S. Pepe, PhD, Program in Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, M2-B500, Seattle, WA 98109-1024 (e-mail: mspepe@ 123456u.washington.edu ).
                Article
                10.1093/jnci/djn326
                2567415
                18840817
                deb27dc1-b94f-4750-994c-bd1fc1709b40
                © 2008 The Author(s).

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Oncology & Radiotherapy

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