Ajrouche Aya, Estellat Candice, De Rycke Yann, Tubach Florence
APHP, Hôpital Pitié Salpétrière, Centre de Pharmacoépidémiologie (Cephepi), CIC-1421, Département Biostatistique, Santé Publique et Information Médicale, Paris, France.
Université Paris Diderot, Sorbonne Paris Cité, Paris, France.
Pharmacoepidemiol Drug Saf. 2017 Aug;26(8):935-944. doi: 10.1002/pds.4225. Epub 2017 May 9.
Administrative databases are increasingly being used in cancer observational studies. Identifying incident cancer in these databases is crucial. This study aimed to develop algorithms to estimate cancer incidence by using health administrative databases and to examine the accuracy of the algorithms in terms of national cancer incidence rates estimated from registries.
We identified a cohort of 463 033 participants on 1 January 2012 in the Echantillon Généraliste des Bénéficiaires (EGB; a representative sample of the French healthcare insurance system). The EGB contains data on long-term chronic disease (LTD) status, reimbursed outpatient treatments and procedures, and hospitalizations (including discharge diagnoses, and costly medical procedures and drugs). After excluding cases of prevalent cancer, we applied 15 algorithms to estimate the cancer incidence rates separately for men and women in 2012 and compared them to the national cancer incidence rates estimated from French registries by indirect age and sex standardization.
The most accurate algorithm for men combined information from LTD status, outpatient anticancer drugs, radiotherapy sessions and primary or related discharge diagnosis of cancer, although it underestimated the cancer incidence (standardized incidence ratio (SIR) 0.85 [0.80-0.90]). For women, the best algorithm used the same definition of the algorithm for men but restricted hospital discharge to only primary or related diagnosis with an additional inpatient procedure or drug reimbursement related to cancer and gave comparable estimates to those from registries (SIR 1.00 [0.94-1.06]).
The algorithms proposed could be used for cancer incidence monitoring and for future etiological cancer studies involving French healthcare databases. Copyright © 2017 John Wiley & Sons, Ltd.
行政数据库在癌症观察性研究中的应用日益广泛。在这些数据库中识别新发癌症至关重要。本研究旨在开发利用卫生行政数据库估算癌症发病率的算法，并根据登记处估算的国家癌症发病率来检验这些算法的准确性。
我们于2012年1月1日在法国医保系统的代表性样本——普通受益人群样本（EGB）中确定了463033名参与者。EGB包含长期慢性病（LTD）状态、报销的门诊治疗和程序以及住院治疗（包括出院诊断、昂贵的医疗程序和药物）的数据。在排除现患癌症病例后，我们应用15种算法分别估算2012年男性和女性的癌症发病率，并通过间接年龄和性别标准化将其与法国登记处估算的国家癌症发病率进行比较。
对男性而言，最准确的算法结合了LTD状态、门诊抗癌药物、放疗疗程以及癌症的原发或相关出院诊断等信息，不过该算法低估了癌症发病率（标准化发病率比（SIR）为0.85[0.80 - 0.90]）。对女性而言，最佳算法采用与男性算法相同的定义，但将医院出院诊断限制为仅原发或相关诊断，并增加了与癌症相关的住院程序或药物报销，其估算结果与登记处的结果相当（SIR为1.00[0.94 - 1.06]）。
所提出的算法可用于癌症发病率监测以及未来涉及法国医疗数据库的癌症病因学研究。版权所有©2017约翰威立父子有限公司。
