Evaluation of algorithms to identify incident cancer cases by using French health administrative databases

被引:17
作者
Ajrouche, Aya [1 ,2 ,3 ]
Estellat, Candice [1 ,2 ,3 ]
De Rycke, Yann [1 ,2 ,3 ]
Tubach, Florence [1 ,2 ,3 ,4 ]
机构
[1] Hop La Pitie Salpetriere, APHP, Ctr Pharmacoepidemiol Cephepi, Dept Biostat Sante Publ & Informat Med,CIC 1421, Paris, France
[2] Univ Paris Diderot, Sorbonne Paris Cite, Paris, France
[3] INSERM, UMR ECEVE 1123, Paris, France
[4] Sorbonne Univ, Univ Pierre & Marie Curie, Paris, France
关键词
cancer; incidence; health insurance data; algorithms; pharmacoepidemiology; MEDICARE CLAIMS DATA; BREAST-CANCER; PREDICTIVE-VALUE; SOLID TUMORS; SYSTEM PMSI; IDENTIFICATION; SURVEILLANCE; PROSTATE; REGISTRY; CARE;
D O I
10.1002/pds.4225
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Purpose 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. Methods We identified a cohort of 463 033 participants on 1 January 2012 in the Echantillon Generaliste des Beneficiaires (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. Results 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]). Conclusion The algorithms proposed could be used for cancer incidence monitoring and for future etiological cancer studies involving French healthcare databases. Copyright (C) 2017 John Wiley & Sons, Ltd.
引用
收藏
页码:935 / 944
页数:10
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