A Simple Framework to Identify Optimal Cost-Effective Risk Thresholds for a Single Screen: Comparison to Decision Curve Analysis
提出一个简单框架，通过成本和效果参数计算单次筛查的增量净效益，从而确定最优风险阈值，并对比决策曲线分析（DCA）的局限性。
Abstract Decision curve analysis (DCA) is a popular approach for assessing biomarkers and risk models, but does not require costs and thus cannot identify optimal risk thresholds for actions. Full decision analyses can identify optimal thresholds, but typically used methods are complex and often difficult to understand. We develop a simple framework to calculate the incremental net benefit for a single-time screen as a function of costs (for tests and treatments) and effectiveness (life-years gained). We provide simple expressions for the optimal cost-effective risk threshold and, equally importantly, for the monetary value of life-years gained associated with the risk threshold. We consider the controversy over the risk threshold to screen women for mutations in BRCA1/2. Importantly, most, and sometimes even all, of the thresholds identified by DCA are infeasible based on their associated dollars per life-year gained. Our simple framework facilitates sensitivity analyses to cost and effectiveness parameters. The proposed approach estimates optimal risk thresholds in a simple and transparent manner, provides intuition about which quantities are critical, and may serve as a bridge between DCA and a full decision analysis.