Net Reclassification Improvement: Computation, Interpretation, and Controversies

被引:476
作者
Leening, Maarten J. G.
Vedder, Moniek M.
Witteman, Jacqueline C. M.
Pencina, Michael J.
Steyerberg, Ewout W.
机构
[1] Erasmus MC Univ Med Ctr Rotterdam, NL-3000 CA Rotterdam, Netherlands
[2] Duke Univ, Durham, NC USA
关键词
CORONARY-HEART-DISEASE; C-REACTIVE PROTEIN; CARDIOVASCULAR RISK PREDICTION; PENCINA; M.J; ET-AL; COMMON GENETIC-VARIANTS; INTIMA-MEDIA THICKNESS; CHRONIC KIDNEY-DISEASE; BODY-MASS INDEX; ROC CURVE; ABDOMINAL ADIPOSITY;
D O I
10.7326/M13-1522
中图分类号
R5 [内科学];
学科分类号
100201 [内科学];
摘要
The net reclassification improvement (NRI) is an increasingly popular measure for evaluating improvements in risk predictions. This article details a review of 67 publications in high-impact general clinical journals that considered the NRI. Incomplete reporting of NRI methods, incorrect calculation, and common misinterpretations were found. To aid improved applications of the NRI, the article elaborates on several aspects of the computation and interpretation in various settings. Limitations and controversies are discussed, including the effect of miscalibration of prediction models, the use of the continuous NRI and "clinical NRI," and the relation with decision analytic measures. A systematic approach toward presenting NRI analysis is proposed: Detail and motivate the methods used for computation of the NRI, use clinically meaningful risk cutoffs for the category-based NRI, report both NRI components, address issues of calibration, and do not interpret the overall NRI as a percentage of the study population reclassified. Promising NRI findings need to be followed with decision analytic or formal cost-effectiveness evaluations.
引用
收藏
页码:122 / +
页数:15
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