Evaluation of algorithms to identify incident cancer cases by using French health administrative databases†. Issue 8 (9th May 2017)

• Record Type: Journal Article
• Authors: Ajrouche, Aya; Estellat, Candice; De Rycke, Yann; Tubach, Florence
• Is Part Of: Pharmacoepidemiology and drug safety. Volume 26:Issue 8(2017)
• Page Start: 935
• Page End: 944
• Publication Date: 2017-05-09
• Subjects: cancer -- incidence -- health insurance data -- algorithms -- pharmacoepidemiology; Pharmacoepidemiology -- Periodicals; Chemotherapy -- Periodicals; Epidemiology -- Periodicals; 615.705
• DOI: 10.1002/pds.4225
• Languages: English
• ISSNs: 1053-8569

Abstract

Abstract: 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 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. 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 © 2017 John Wiley & Sons, Ltd.