Using radiation risk models in cancer screening simulations: important assumptions and effects on outcome projections.
Using radiation risk models in cancer screening simulations: important assumptions and effects on outcome projections.
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DOI：
10.1148/radiol.11110352
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发表时间：
2012-03
期刊：
影响因子：
19.7
通讯作者：
C. Kong;Janie M. Lee;P. McMahon;K. Lowry;Z. Omer;Jonathan D. Eisenberg;P. Pandharipande;G. Gazelle
中科院分区：
文献类型：
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作者：
C. Kong;Janie M. Lee;P. McMahon;K. Lowry;Z. Omer;Jonathan D. Eisenberg;P. Pandharipande;G. Gazelle
目的评估将辐射风险纳入乳腺癌和肺癌筛查的微模拟（一阶蒙特卡罗）模型的效果，以说明纳入辐射风险对患者预后预测的影响。材料和方法本研究中使用的所有数据均来自公开可用或未确定的人类受试者数据。不需要机构审查委员会的批准。两个癌症筛查模型（乳腺癌模型和肺癌政策模型）分别适应了乳房x光检查和胸部计算机断层扫描（CT）的辐射暴露效应，说明了将辐射风险纳入模拟模型的挑战。乳房模型预测的主要结果是BRCA1突变携带者的预期寿命（LE）。从25岁、30岁、35岁和40岁开始的数字乳房x线摄影筛查在筛查假阳性结果和辐射暴露影响的背景下进行评估。肺模型的主要结果是由于每年筛查肺癌特异性死亡率降低，比较两种诊断CT方案用于肺结节评估。采用Metropolis-Hastings算法以95%的不确定区间（ui）估计结果的平均值。结果：在不受辐射照射影响的情况下，乳房模型显示，25岁开始每年进行数字乳房x光检查的LE最高（72.03年；95% UI: 72.01年，72.05年），假阳性结果筛查次数最多（每名妇女2.0次）。当包括辐射影响时，30岁开始的年度数字化乳房x光检查最大的LE（71.90年；95% UI: 71.87年，71.94年），假阳性结果的筛查次数较少（每名妇女1.4次）。对于每年对直径小于4 mm的50岁女性进行胸部CT筛查，无随访的肺模型预测无辐射风险的肺癌特异性死亡率降低21.50% (95% UI: 20.90%, 22.10%)，有辐射风险的肺癌特异性死亡率降低17.75% （95% UI: 16.97%, 18.41%）。结论：由于包括辐射暴露风险会影响模拟模型的长期预测，因此在进行基于模型的诊断成像评估时，包括这些风险是很重要的。
PURPOSE To evaluate the effect of incorporating radiation risk into microsimulation (first-order Monte Carlo) models for breast and lung cancer screening to illustrate effects of including radiation risk on patient outcome projections. MATERIALS AND METHODS All data used in this study were derived from publicly available or deidentified human subject data. Institutional review board approval was not required. The challenges of incorporating radiation risk into simulation models are illustrated with two cancer screening models (Breast Cancer Model and Lung Cancer Policy Model) adapted to include radiation exposure effects from mammography and chest computed tomography (CT), respectively. The primary outcome projected by the breast model was life expectancy (LE) for BRCA1 mutation carriers. Digital mammographic screening beginning at ages 25, 30, 35, and 40 years was evaluated in the context of screenings with false-positive results and radiation exposure effects. The primary outcome of the lung model was lung cancer-specific mortality reduction due to annual screening, comparing two diagnostic CT protocols for lung nodule evaluation. The Metropolis-Hastings algorithm was used to estimate the mean values of the results with 95% uncertainty intervals (UIs). RESULTS Without radiation exposure effects, the breast model indicated that annual digital mammography starting at age 25 years maximized LE (72.03 years; 95% UI: 72.01 years, 72.05 years) and had the highest number of screenings with false-positive results (2.0 per woman). When radiation effects were included, annual digital mammography beginning at age 30 years maximized LE (71.90 years; 95% UI: 71.87 years, 71.94 years) with a lower number of screenings with false-positive results (1.4 per woman). For annual chest CT screening of 50-year-old females with no follow-up for nodules smaller than 4 mm in diameter, the lung model predicted lung cancer-specific mortality reduction of 21.50% (95% UI: 20.90%, 22.10%) without radiation risk and 17.75% (95% UI: 16.97%, 18.41%) with radiation risk. CONCLUSION Because including radiation exposure risk can influence long-term projections from simulation models, it is important to include these risks when conducting modeling-based assessments of diagnostic imaging.