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首页> 外文期刊>BMC Medical Informatics and Decision Making >How does age affect baseline screening mammography performance measures? A decision model
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How does age affect baseline screening mammography performance measures? A decision model

机译：年龄如何影响乳腺X线摄影基线检查的性能指标？决策模型

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Background In order to promote consumer-oriented informed medical decision-making regarding screening mammography, we created a decision model to predict the age dependence of the cancer detection rate, the recall rate and the secondary performance measures (positive predictive values, total intervention rate, and positive biopsy fraction) for a baseline mammogram. Methods We constructed a decision tree to model the possible outcomes of a baseline screening mammogram in women ages 35 to 65. We compared the single baseline screening mammogram decision with the no screening alternative. We used the Surveillance Epidemiology and End Results national cancer database as the primary input to estimate cancer prevalence. For other probabilities, the model used population-based estimates for screening mammography accuracy and diagnostic mammography outcomes specific to baseline exams. We varied radiologist performance for screening accuracy. Results The cancer detection rate increases from 1.9/1000 at age 40 to 7.2/1000 at age 50 to 15.1/1000 at age 60. The recall rate remains relatively stable at 142–157/1000, which varies from 73–236/1000 at age 50 depending on radiologist performance. The positive predictive value of a screening mammogram increases from 1.3% at age 40 to 9.8% at age 60, while the positive predictive value of a diagnostic mammogram varies from 2.9% at age 40 to 19.2% at age 60. The model predicts the total intervention rate = 0.013*AGE2 - 0.67*AGE + 40, or 34/1000 at age 40 to 47/1000 at age 60. Therefore, the positive biopsy (intervention) fraction varies from 6% at age 40 to 32% at age 60. Conclusion Breast cancer prevalence, the cancer detection rate, and all secondary screening mammography performance measures increase substantially with age.
机译：背景技术为了促进针对消费者进行乳腺X线筛查的知情医疗决策，我们创建了一个决策模型来预测癌症检出率，召回率和次要性能指标（阳性预测值，总干预率，活检分数为阳性）。方法我们构建了决策树，以对35岁至65岁女性进行基线筛查乳房X线照片的可能结果进行建模。我们将单项基线筛查乳房X线照片与无筛查替代方案进行了比较。我们使用监视流行病学和最终结果国家癌症数据库作为估计癌症患病率的主要输入。对于其他概率，该模型使用基于人群的估计值来筛查乳房X线照片的准确性和特定于基线检查的乳房X线照片的诊断结果。我们改变了放射科医生的筛查准确性。结果癌症检出率从40岁时的1.9 / 1000增加到50岁时的7.2 / 1000到60岁时的15.1 / 1000。召回率保持相对稳定在142-157 / 1000，在30岁时为73-236 / 1000。 50岁取决于放射线医师的表现。乳房X线检查的阳性预测值从40岁的1.3％增加到60岁的9.8％，而诊断性乳房X射线照片的阳性预测值从40岁的2.9％变化到60岁的19.2％。该模型预测了总的干预率= 0.013 * AGE 2 -0.67 * AGE + 40，即40岁时的34/1000到60岁时的47/1000。因此，活检（干预）阳性率在6％时为6％。年龄在40岁至60％时为32％。结论乳腺癌的患病率，癌症检出率和所有二次筛查乳房X线摄影表现指标均随年龄的增长而显着增加。

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