Quantifying the added value of new biomarkers: how and how not

被引:132
作者
Nancy R. Cook
机构
[1] Harvard Medical School,Division of Preventive Medicine, Brigham and Women’s Hospital
关键词
Biomarkers; Model fit; Calibration; Reclassification; Clinical utility;
D O I
10.1186/s41512-018-0037-2
中图分类号
学科分类号
摘要
Over the past few decades, interest in biomarkers to enhance predictive modeling has soared. Methodology for evaluating these has also been an active area of research. There are now several performance measures available for quantifying the added value of biomarkers. This commentary provides an overview of methods currently used to evaluate new biomarkers, describes their strengths and limitations, and offers some suggestions on their use.
引用
收藏
相关论文
共 144 条
[1]  
Kannel WB(1961)Factors of risk in the development of coronary heart disease--six year follow-up experience. The Framingham Study Annals int med 55 33-50
[2]  
Dawber TR(1998)Prediction of coronary heart disease using risk factor categories Circulation 97 1837-1847
[3]  
Kagan A(2011)One statistical test is sufficient for assessing new predictive markers BMC Med Res Methodol 11 13-1482
[4]  
Revotskie N(2013)Testing for improvement in prediction model performance Stat Med 32 1467-3360
[5]  
Stokes J(2017)Asymptotic distribution of AUC, NRIs, and IDI based on theory of U-statistics Stat Med 36 3334-36
[6]  
Wilson PW(1982)The meaning and use of the area under a receiver operating characteristic (ROC) curve Radiology 143 29-843
[7]  
D’Agostino RB(1983)A method of comparing the areas under receiver operating characteristic curves derived from the same cases Radiology 148 839-1546
[8]  
Levy D(1982)Evaluating the yield of medical tests JAMA 247 1543-2123
[9]  
Belanger AM(2004)Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation Stat Med 23 2109-970
[10]  
Silbershatz H(2005)Concordance probability and discriminatory power in proportional hazards regression Biometrika 92 965-1553