Baker Stuart G, Cook Nancy R, Vickers Andrew, Kramer Barnett S
National Cancer Institute, Bethesda, USA.
J R Stat Soc Ser A Stat Soc. 2009 Oct 1;172(4):729-748. doi: 10.1111/j.1467-985X.2009.00592.x.
Because many medical decisions are based on risk prediction models constructed from medical history and results of tests, the evaluation of these prediction models is important. This paper makes five contributions to this evaluation: (1) the relative utility curve which gauges the potential for better prediction in terms of utilities, without the need for a reference level for one utility, while providing a sensitivity analysis for missipecification of utilities, (2) the relevant region, which is the set of values of prediction performance consistent with the recommended treatment status in the absence of prediction (3) the test threshold, which is the minimum number of tests that would be traded for a true positive in order for the expected utility to be non-negative, (4) the evaluation of two-stage predictions that reduce test costs, and (5) connections among various measures of prediction performance. An application involving the risk of cardiovascular disease is discussed.
由于许多医疗决策是基于从病史和检查结果构建的风险预测模型，因此对这些预测模型的评估很重要。本文对这种评估做出了五项贡献：（1）相对效用曲线，它在效用方面衡量更好预测的潜力，无需一个效用的参考水平，同时为效用误设提供敏感性分析；（2）相关区域，它是在没有预测时与推荐治疗状态一致的预测性能值的集合；（3）测试阈值，即为使预期效用为非负，换取一个真阳性而愿意进行的最少测试次数；（4）对降低测试成本的两阶段预测的评估；（5）各种预测性能度量之间的联系。文中讨论了一个涉及心血管疾病风险的应用。
