Modelling the cumulative risk of a false-positive screening test.
Modelling the cumulative risk of a false-positive screening test.
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DOI：
10.1177/0962280209359842
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发表时间：
2010-10
影响因子：
2.3
通讯作者：
Smith RA
中科院分区：
文献类型：
--
作者：
Hubbard RA;Miglioretti DL;Smith RA
筛查试验的目标是通过早期发现疾病来降低发病率和死亡率;但筛查的益处必须与潜在危害进行权衡，例如假阳性（FP）结果，这可能导致医疗费用增加，患者焦虑以及与诊断随访程序相关的其他不良结果。准确估计多轮筛查后FP检测的累积风险对于项目评估和目标设定非常重要，并告知接受筛查的个人随着时间的推移他们应该从检测中获得什么。累积FP风险的估计因删失的存在和删失时间对事件历史的可能依赖性而变得复杂。目前用于估计删失数据累积FP风险的统计方法遵循两种不同的方法，要么以观察到的筛选试验次数为条件，要么边缘化该随机变量。我们回顾这些现有的方法，确定其局限性和可能不切实际的假设，并提出简单的扩展，以解决这些局限性。我们讨论的领域，额外的扩展可能是有用的。我们举例说明了用于估计筛查乳腺X线摄影的累积FP回忆风险的方法，并使用乳腺癌监测联盟收集的13年数据调查建模假设的适当性。在BCSC的数据中，我们发现了违反这两类统计方法建模假设的证据。根据所使用的方法，10次筛查乳房X线照片后FP回忆的估计风险在58%至77%之间变化，根据我们认为最合理的建模假设，估计为63%。
The goal of a screening test is to reduce morbidity and mortality through the early detection of disease; but the benefits of screening must be weighed against potential harms, such as false-positive (FP) results, which may lead to increased healthcare costs, patient anxiety, and other adverse outcomes associated with diagnostic follow-up procedures. Accurate estimation of the cumulative risk of a FP test after multiple screening rounds is important for program evaluation and goal setting, as well as informing individuals undergoing screening what they should expect from testing over time. Estimation of the cumulative FP risk is complicated by the existence of censoring and possible dependence of the censoring time on the event history. Current statistical methods for estimating the cumulative FP risk from censored data follow two distinct approaches, either conditioning on the number of screening tests observed or marginalizing over this random variable. We review these current methods, identify their limitations and possibly unrealistic assumptions, and propose simple extensions to address some of these limitations. We discuss areas where additional extensions may be useful. We illustrate methods for estimating the cumulative FP recall risk of screening mammography and investigate the appropriateness of modeling assumptions using 13 years of data collected by the Breast Cancer Surveillance Consortium. In the BCSC data we found evidence of violations of modeling assumptions of both classes of statistical methods. The estimated risk of a FP recall after 10 screening mammograms varied between 58% and 77% depending on the approach used, with an estimate of 63% based on what we feel are the most reasonable modeling assumptions.
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影响因子：
1.9
作者：
LANE, PW;NELDER, JA
通讯作者：
NELDER, JA
影响因子：
10.3
作者：
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Kerlikowske, K
影响因子：
39.2
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影响因子：
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作者：
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通讯作者：
Chen, THH
影响因子：
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作者：
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通讯作者：
Sullivan, DC