Conte Cécile, Palmaro Aurore, Grosclaude Pascale, Daubisse-Marliac Laetitia, Despas Fabien, Lapeyre-Mestre Maryse
LEASP-UMR 1027, Inserm-University of Toulouse Medical and Clinical Pharmacology Unit CIC 1436, Toulouse University Hospital Claudius Regaud Institute, IUCT-O, Tarn Cancer Registry, Toulouse, France.
Medicine (Baltimore). 2018 Jan;97(2):e9418. doi: 10.1097/MD.0000000000009418.
The use of claims database to study lymphomas in real-life conditions is a crucial issue in the future. In this way, it is essential to develop validated algorithms for the identification of lymphomas in these databases. The aim of this study was to assess the validity of diagnosis codes in the French health insurance database to identify incident cases of lymphomas according to results of a regional cancer registry, as the gold standard.Between 2010 and 2013, incident lymphomas were identified in hospital data through 2 algorithms of selection. The results of the identification process and characteristics of incident lymphomas cases were compared with data from the Tarn Cancer Registry. Each algorithm's performance was assessed by estimating sensitivity, predictive positive value, specificity (SPE), and negative predictive value.During the period, the registry recorded 476 incident cases of lymphomas, of which 52 were Hodgkin lymphomas and 424 non-Hodgkin lymphomas. For corresponding area and period, algorithm 1 provides a number of incident cases close to the Registry, whereas algorithm 2 overestimated the number of incident cases by approximately 30%. Both algorithms were highly specific (SPE = 99.9%) but moderately sensitive. The comparative analysis illustrates that similar distribution and characteristics are observed in both sources.Given these findings, the use of claims database can be consider as a pertinent and powerful tool to conduct medico-economic or pharmacoepidemiological studies in lymphomas.
在实际情况下利用理赔数据库研究淋巴瘤是未来的一个关键问题。通过这种方式,开发用于在这些数据库中识别淋巴瘤的经过验证的算法至关重要。本研究的目的是根据作为金标准的地区癌症登记处的结果,评估法国健康保险数据库中诊断代码识别淋巴瘤新发病例的有效性。
在2010年至2013年期间,通过两种选择算法在医院数据中识别新发病例的淋巴瘤。将识别过程的结果和新发病例的淋巴瘤病例特征与塔恩癌症登记处的数据进行比较。通过估计敏感性、预测阳性值、特异性(SPE)和阴性预测值来评估每种算法的性能。
在此期间,登记处记录了476例淋巴瘤新发病例,其中52例为霍奇金淋巴瘤,424例为非霍奇金淋巴瘤。对于相应的地区和时期,算法1提供的新发病例数与登记处接近,而算法2高估了新发病例数约30%。两种算法都具有高度特异性(SPE = 99.9%)但敏感性中等。比较分析表明,两个来源中观察到相似的分布和特征。
鉴于这些发现,理赔数据库的使用可被视为在淋巴瘤中进行医学经济学或药物流行病学研究的相关且强大的工具。