Remontet L, Mitton N, Couris C M, Iwaz J, Gomez F, Olive F, Polazzi S, Schott A M, Trombert B, Bossard N, Colonna M
Service de Biostatistique, Batiment 4D, Centre Hospitalier Lyon Sud, Pierre-Benite, 69495, France.
Eur J Epidemiol. 2008;23(10):681-8. doi: 10.1007/s10654-008-9282-y. Epub 2008 Aug 21.
One approach to estimate cancer incidence in the French Départements is to quantify the relationship between data in cancer registries and data obtained from the PMSI (Programme de Médicalisation des Systèmes d'Information Médicale). This relationship may then be used in Départements without registries to infer the incidence from local PMSI data. We present here some methodological solutions to apply this approach. Data on invasive breast cancer for 2002 were obtained from 12 Départemental registries. The number of hospital stays was obtained from the National PMSI using two different algorithms based on the main diagnosis only (Algorithm 1) or on that diagnosis associated to a mention of "resection" (Algorithm 2). Considering registry data as gold standard, a calibration approach was used to model the ratio of the number of hospital stays to the number of incident cases. In Départements with registries, validation of the predictions was done through cross-validation. In Départements without registries, validation was done through a study of homogeneity of the mean number of hospital stays per patient. Cross-validation showed that the estimates predicted by the model were true with data extracted by Algorithm 1 but not by Algorithm 2. However, with Algorithm 1, there was an important heterogeneity between French Départements as to the mean number of hospital stays per patient, which had an important impact on the estimations. In the near future, the method will allow using medico-administrative data (after calibration with registry data) to estimate Départemental incidence of selected cancers.
估算法国各省份癌症发病率的一种方法是量化癌症登记处的数据与从医学信息系统医疗化计划(PMSI)获得的数据之间的关系。然后,这种关系可用于没有登记处的省份,以便根据当地的PMSI数据推断发病率。我们在此介绍应用此方法的一些方法学解决方案。2002年侵袭性乳腺癌的数据来自12个省级登记处。住院次数是通过国家PMSI获得的,使用了两种不同的算法,一种仅基于主要诊断(算法1),另一种基于与“切除”提及相关的诊断(算法2)。将登记处数据视为金标准,采用校准方法对住院次数与发病病例数的比率进行建模。在有登记处的省份,通过交叉验证对预测进行验证。在没有登记处的省份,通过研究每位患者的平均住院次数的同质性进行验证。交叉验证表明,该模型预测的估计值与通过算法1提取的数据相符,但与算法2提取的数据不符。然而,使用算法1时,法国各省份之间每位患者的平均住院次数存在重要的异质性,这对估计产生了重要影响。在不久的将来,该方法将允许使用医疗行政数据(在用登记处数据校准后)来估计选定癌症的省级发病率。