Nonhomogeneous Markov chain for estimating the cumulative risk of multiple false positive screening tests.
Nonhomogeneous Markov chain for estimating the cumulative risk of multiple false positive screening tests.
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DOI：
10.1111/biom.13484
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发表时间：
2022-09
期刊：
影响因子：
1.9
通讯作者：
Miglioretti DL
中科院分区：
文献类型：
--
作者：
Golmakani MK;Hubbard RA;Miglioretti DL
筛查测试被广泛推荐用于在无症状个体中早期发现疾病。虽然在早期阶段检测疾病有可能改善结果，但筛查也有负面影响，包括假阳性结果，可能导致焦虑，不必要的诊断程序和增加医疗费用。此外，多个假阳性结果可能会阻碍参与随后的筛查轮次。筛查指南通常建议在多年的时间内重复筛查，但很少有先前的研究调查了个人接受多个假阳性检测结果的频率。由于存在删失和竞争风险，估计多轮筛选过程中多个假阳性结果的累积风险具有挑战性，这可能取决于假阳性风险、筛选轮数和既往假阳性结果的数量。为了解决估计多个假阳性测试结果的累积风险的一般挑战，我们提出了一个非齐次多状态模型来描述包括竞争事件的筛选过程。我们开发了替代方法，用于估计多个假阳性结果的累积风险，使用这种多状态模型的基础上，现有的估计一个假阳性的累积风险。我们通过模拟研究比较了新提出的模型的性能，并使用来自乳腺癌监测联盟的筛查乳腺X线摄影数据来说明模型性能。在大多数模拟场景中，与其他方法相比，删失偏差模型的多状态扩展表现出较低的偏差。在筛查乳腺X线摄影的背景下，我们发现多个假阳性结果的累积风险很高。例如，基于删失偏倚模型，对于高风险个体，在10轮年度筛查之后，至少两次假阳性乳房X线摄影结果的累积概率为40.4
Screening tests are widely recommended for the early detection of disease among asymptomatic individuals. While detecting disease at an earlier stage has the potential to improve outcomes, screening also has negative consequences, including false positive results which may lead to anxiety, unnecessary diagnostic procedures and increased healthcare costs. In addition, multiple false positive results could discourage participating at subsequent screening rounds. Screening guidelines typically recommend repeated screening over a period of many years, but little prior research has investigated how often individuals receive multiple false positive test results. Estimating the cumulative risk of multiple false positive results over the course of multiple rounds of screening is challenging due to the presence of censoring and competing risks, which may depend on false positive risk, screening round and number of prior false positive results. To address the general challenge of estimating the cumulative risk of multiple false positive test results, we propose a non-homogeneous multi-state model to describe the screening process including competing events. We developed alternative approaches for estimating the cumulative risk of multiple false positive results using this multi-state model based on existing estimators for cumulative risk of a single false positive. We compared the performance of the newly proposed models through simulation studies and illustrate model performance using data on screening mammography from the Breast Cancer Surveillance Consortium. Across most simulation scenarios, the multi-state extension of a censoring bias model demonstrated lower bias compared to other approaches. In the context of screening mammography, we found that the cumulative risk of multiple false positive results is high. For instance, based on the censoring bias model, for a high risk individual, the cumulative probability of at least two false positive mammography results after 10 rounds of annual screening is 40.4
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影响因子：
19.7
作者：
Lehman, Constance D.;Arao, Robert F.;Miglioretti, Diana L.
通讯作者：
Miglioretti, Diana L.
影响因子：
39.2
作者：
Burman, ML;Taplin, SH;Elmore, JG
通讯作者：
Elmore, JG
DOI：
10.1001/jama.2015.12783
发表时间：
2015-10-20
期刊：
JAMA
影响因子：
--
作者：
Oeffinger KC;Fontham ET;Etzioni R;Herzig A;Michaelson JS;Shih YC;Walter LC;Church TR;Flowers CR;LaMonte SJ;Wolf AM;DeSantis C;Lortet-Tieulent J;Andrews K;Manassaram-Baptiste D;Saslow D;Smith RA;Brawley OW;Wender R;American Cancer Society
通讯作者：
American Cancer Society
影响因子：
2.3
作者：
Hubbard RA;Miglioretti DL;Smith RA
通讯作者：
Smith RA
影响因子：
1.9
作者：
Xu, JL;Fagerstrom, RM;Kramer, BS
通讯作者：
Kramer, BS