A novel approach for medical research on lymphomas: A study validation of claims-based algorithms to identify incident cases

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 Fren...

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Veröffentlicht in:Medicine (Baltimore) Jg. 97; H. 2; S. e9418
Hauptverfasser: Conte, Cécile, Palmaro, Aurore, Grosclaude, Pascale, Daubisse-Marliac, Laetitia, Despas, Fabien, Lapeyre-Mestre, Maryse
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved 01.01.2018
Wolters Kluwer Health
Schlagworte:
Adult
Aged
Aged, 80 and over
Algorithms
Biomedical Research - methods
Databases, Factual
Female
Humans
Insurance, Health
Lymphoma - diagnosis
Lymphoma - therapy
Male
Middle Aged
Observational Study
Registries
ISSN:0025-7974, 1536-5964, 1536-5964
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Zusammenfassung: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.
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ISSN:0025-7974
1536-5964
1536-5964
DOI:10.1097/MD.0000000000009418