Improving the diagnostic accuracy of a stratified screening strategy by identifying the optimal risk cutoff.
Improving the diagnostic accuracy of a stratified screening strategy by identifying the optimal risk cutoff.
复制标题
通过确定最佳风险截止值来提高分层筛查策略的诊断准确性。
DOI：
10.1007/s10552-019-01208-9
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Glueck,DeborahH
中科院分区：
文献类型：
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作者：
Brinton,JohnT;Hendrick,REdward;Ringham,BrandyM;Kriege,Mieke;Glueck,DeborahH
背景：美国癌症协会（ACS）建议采用分层策略进行乳腺癌筛查。该策略包括评估乳腺癌风险，同时使用核磁共振成像和乳房x光检查筛查高风险妇女，以及仅使用乳房x光检查筛查低风险妇女。美国癌症学会根据专家共识选择了他们的高风险临界值。方法我们提出了一种分析方法，可以最大限度地提高人群中基于风险的分层筛查策略的诊断准确性（AUC/ROC）。输入是筛查测试分数的联合分布，以及给定风险分数的疾病几率。使用该方法进行乳腺癌筛查，我们估计了两种不同风险模型的最佳风险临界值：乳腺癌筛查联盟（breast cancer screening Consortium， BCSC）模型和具有更好区分准确性的假设模型。乳房x线摄影和MRI测试评分分布数据来自磁共振成像筛查研究组。结果一个具有极好的鉴别准确度（c统计量）的风险模型产生了一个合理的截止点，其中只有约20%的妇女进行了双重筛查。然而，BCSC风险模型（c统计）在区分需要双重筛查的妇女和只需要乳房x光检查的妇女方面缺乏歧视性的准确性。结论本研究为优化人群分层筛查策略的诊断准确性提供了一种通用方法，并评估风险模型是否足够准确以指导分层筛查。对于乳腺癌，大多数风险模型缺乏足够的区分准确性，不足以使分层筛查成为合理的推荐。
BackgroundThe American Cancer Society (ACS) suggests using a stratified strategy for breast cancer screening. The strategy includes assessing risk of breast cancer, screening women at high risk with both MRI and mammography, and screening women at low risk with mammography alone. The ACS chose their cutoff for high risk using expert consensus.MethodsWe propose instead an analytic approach that maximizes the diagnostic accuracy (AUC/ROC) of a risk-based stratified screening strategy in a population. The inputs are the joint distribution of screening test scores, and the odds of disease, for the given risk score. Using the approach for breast cancer screening, we estimated the optimal risk cutoff for two different risk models: the Breast Cancer Screening Consortium (BCSC) model and a hypothetical model with much better discriminatory accuracy. Data on mammography and MRI test score distributions were drawn from the Magnetic Resonance Imaging Screening Study Group.ResultsA risk model with an excellent discriminatory accuracy (c-statistic) yielded a reasonable cutoff where only about 20% of women had dual screening. However, the BCSC risk model (c-statistic) lacked the discriminatory accuracy to differentiate between women who needed dual screening, and women who needed only mammography.ConclusionOur research provides a general approach to optimize the diagnostic accuracy of a stratified screening strategy in a population, and to assess whether risk models are sufficiently accurate to guide stratified screening. For breast cancer, most risk models lack enough discriminatory accuracy to make stratified screening a reasonable recommendation.