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探索德国索赔数据的潜力,以识别发生的肺癌患者

Josephine Kanbach¹, Nikolaj Rischke¹, Sabine Luttmann¹

¹Department of Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology- BIPS, Achterstr. 30, 28359, Bremen, Germany.

BMC pulmonary medicine

|June 26, 2025

概括

一个算法有效地识别了发生的肺癌 (LC) 患者在德国索赔数据. 该方法支持使用现实世界医疗保健数据库进行关键的癌症研究和患者分层.

科学领域:

流行病学流行病学
医疗信息学医疗信息学
在瘤学瘤学.

背景情况:

现实世界医疗保健数据库对癌症研究有价值.
准确识别癌症患者对于数据库适用性至关重要.
这项研究的重点是验证一个算法肺癌 (LC) 患者识别在德国索赔数据.

研究的目的:

评估用于识别发生肺癌患者的算法的可信性和有效性.
将确诊的LC患者分为先进和未先进的阶段.
分析与人口和社会经济因素相关的肺癌发病率和存活率.

主要方法:

使用了德国制药流行病学研究数据库 (GePaRD),该数据库包含约20%的德国人口的索赔数据.
应用了先前开发的算法来识别发生的LC患者及其疾病阶段.
计算的年龄标准化发病率 (ASIR) 和年龄标准化五年生存率,按性别和贫困指数分层.

主要成果:

该算法每年识别出大约9500-10,500例LC患者.
2018年,71.4%的确诊LC患者被归类为晚期.
男人中LC的ASIR为45/100,000,女性为27/100,000,贫困地区的比例较低. 男性的五年生存率为27%至31%,女性为31%至34%.

结论:

应用的算法证明了在德国索赔数据中识别发生肺癌患者的可信结果.
这些发现支持了这种算法在流行病学研究中的有效性和实用性.
该研究强调了索赔数据在了解肺癌负担和生存模式方面的潜力.

关键词:

癌症登记处数据癌症登记处数据索赔数据索赔数据索赔数据影响影响影响影响肺癌是一种肺癌.幸存的生存方式

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