Using relative utility curves to evaluate risk prediction
Using relative utility curves to evaluate risk prediction
复制标题
DOI：
10.1111/j.1467-985x.2009.00592.x
复制
发表时间：
2009-01-01
影响因子：
2
通讯作者：
Kramer, Barnett S.
中科院分区：
文献类型：
--
作者：
Baker, Stuart G.;Cook, Nancy R.;Kramer, Barnett S.
由于许多医疗决策都是基于根据病史和测试结果构建的风险预测模型，因此对这些预测模型的评估非常重要。本文对这一评估做出了五个贡献：相对效用曲线，衡量效用方面更好预测的潜力，无需一个效用的参考水平，同时提供对效用错误指定的敏感性分析；相关区域，即在没有预测的情况下与推荐治疗状态一致的一组预测性能值；测试阈值，即为了使预期效用非负而为真正的阳性预测进行的最小测试数量；两阶段预测的评估减少测试成本以及预测性能的各种度量之间的联系。讨论了涉及心血管疾病风险的应用。
Because many medical decisions are based on risk prediction models that are constructed from medical history and results of tests, the evaluation of these prediction models is important. This paper makes five contributions to this evaluation: 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 misspecification of utilities, the relevant region, which is the set of values of prediction performance that are consistent with the recommended treatment status in the absence of prediction, the test threshold, which is the minimum number of tests that would be traded for a true positive prediction in order for the expected utility to be non-negative, the evaluation of two-stage predictions that reduce test costs and connections between various measures of performance of prediction. An application involving the risk of cardiovascular disease is discussed.