An approach to identifying incident breast cancer cases using Medicare claims data
An approach to identifying incident breast cancer cases using Medicare claims data
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DOI：
10.1016/s0895-4356(99)00173-0
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发表时间：
2000-06-01
影响因子：
7.2
通讯作者：
Goodwin, JS
中科院分区：
文献类型：
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作者：
Freeman, JL;Zhang, D;Goodwin, JS
本研究开发并评估了一种方法，以确定一个新诊断的乳腺癌病例使用多个来源的数据从医疗保险索赔系统。事件病例的预测因子在操作上被定义为乳腺癌相关诊断和住院、门诊和医生索赔程序的代码。预测因子的最佳组合随后通过逻辑回归模型确定，该模型使用1992年SEER注册表-医疗保险索赔数据库的数据和从SEER地区抽取的非癌症对照样本。ROC曲线显示该模型的敏感性和特异性均在90%以上，但阳性预测值较低（67-70%）。这种低预测值主要是由于该模型在区分复发性和继发性恶性肿瘤与偶发病例方面存在局限性，也可能是由于该模型识别了未被SEER识别的真实偶发病例。然而，逻辑回归方法是确定事件案例的有用方法，因为它允许更大的灵活性，通过根据应用程序选择不同的切割点来改变性能特征（例如，注册表验证的高灵敏度，结果研究的高特异性）。它还允许我们对基于人群的乳腺癌发病率估算进行具体调整。(C) 2000 Elsevier Science Inc.；版权所有。
This study developed and evaluated a method for ascertaining a newly diagnosed breast cancer case using multiple sources of data from the Medicare claims system. Predictors of an incident case were operationally defined as codes for breast cancer-related diagnoses and procedures from hospital inpatient, hospital outpatient, and physician claims. The optimal combination of predictors was then determined from a logistic regression model using 1992 data from the linked SEER registries-Medicare claims data base and a sample of noncancer controls drawn from the SEER areas. While the ROC curve demonstrates that the model can produce levels of sensitivity and specificity above 90%, the positive predictive value is comparatively low (67-70%). This low predictive value is largely the result of the model's limitation in distinguishing recurrent and secondary malignancies from incident cases and possibly from the model identifying true incident cases not identified by SEER. Nevertheless, the logistic regression approach is a useful method for ascertaining incident cases because it allows for greater flexibility in changing the performance characteristics by selecting different cut-points depending on the application (e.g., high sensitivity for registry validation, high specificity for outcomes research). It also allows us to make specific adjustments to population based estimates of breast cancer incidence with claims. (C) 2000 Elsevier Science Inc. All rights reserved.