Biomarker Discovery and Validation: Statistical Considerations

被引:81
|
作者
Ou, Fang-Shu [1 ]
Michiels, Stefan [2 ]
Shyr, Yu [3 ]
Adjei, Alex A. [4 ]
Oberg, Ann L. [1 ]
机构
[1] Mayo Clin, Dept Hlth Sci Res, 200 First St SW, Rochester, MN 55905 USA
[2] Univ Paris Saclay, Dept Biostat & Epidemiol, Labelel Ligue Canc, INSERM,Gustave Roussy,Oncostat U1018,CESP, Villejuif, France
[3] Vanderbilt Univ, Dept Biostat, 221 Kirkland Hall, Nashville, TN 37235 USA
[4] Mayo Clin, Dept Oncol, Rochester, MN 55905 USA
基金
美国国家卫生研究院;
关键词
Biomarker; Exploratory analysis; Confirmation analysis; Clinical trial; CANCER; SPECIMENS; IMPACT; BIAS;
D O I
10.1016/j.jtho.2021.01.1616
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Biomarkers have various applications including disease detection, diagnosis, prognosis, prediction of response to intervention, and disease monitoring. In this era of precision medicine, having validated biomarkers to inform clinical decision making is more important than ever. In this article, we discuss best the practices and potential issues in biomarker discovery and validation. We encourage team science partnerships to bring cutting-edge discovery from bench to bedside, leading to improved patient care and outcomes. Biomarkers have various applications including disease detection, diagnosis, prognosis, prediction of response to intervention, and disease monitoring. In this era of precision medicine, having validated biomarkers to inform clinical decision making is more important than ever. In this article, we discuss best the practices and potential issues in biomarker discovery and validation. We encourage team science partnerships to bring cutting-edge discovery from bench to bedside, leading to improved patient care and outcomes. ? 2021 International Association for the Study of Lung Cancer. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:537 / 545
页数:9
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