期刊
MEDICAL DECISION MAKING
卷 33, 期 2, 页码 154-162出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/0272989X12461856
关键词
cardiology; internal medicine; preventive medicine-screening; public health.
资金
- NHLBI BAA award [HHSN268200960011C]
- National Heart, Lung and Blood Institute, Bethesda, Maryland, USA [HL-43851, CA-47988]
- National Cancer Institute, Bethesda, Maryland, USA
Background. Comparing prediction models using reclassification within subgroups at intermediate risk is often of clinical interest. Objective. To demonstrate a method for obtaining an unbiased estimate for the Net Reclassification Improvement (NRI) evaluated only on a subset, the clinical NRI. Study Design and Setting. We derived the expected value of the clinical NRI under the null hypothesis using the same principles as the overall NRI. We then conducted a simulation study based on a logistic model with a known predictor and a potential predictor, varying the effects of the known and potential predictors to test the performance of our bias-corrected clinical NRI measure. Finally, data from the Women's Health Study, a prospective cohort of 24 171 female health professionals, were used as an example of the proposed method. Results. Our bias-corrected estimate is shown to have a mean of zero in the null case under a range of simulated parameters and, unlike the naive estimate, to be unbiased. We also provide 2 methods for obtaining a variance estimate, both with reasonable type 1 errors. Conclusion. Our proposed method is an improvement over currently used methods of calculating the clinical NRI and is recommended to reduce overly optimistic results.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据