Cohort profile: decoding the epidemiology of liver disease in Sweden (DELIVER).


Journal

Scandinavian journal of gastroenterology
ISSN: 1502-7708
Titre abrégé: Scand J Gastroenterol
Pays: England
ID NLM: 0060105

Informations de publication

Date de publication:
08 2022
Historique:
pubmed: 17 3 2022
medline: 29 7 2022
entrez: 16 3 2022
Statut: ppublish

Résumé

Swedish nationwide registries can be used to identify patients with a wide range of diagnoses. This information can be used to construct cohorts useful to determine prognosis and identify risk factors for disease progression. Here, we describe a new register-based cohort of patients with a diverse set of chronic liver disease diagnoses in Sweden. The DELIVER (DEcoding the epidemiology of LIVER disease in sweden) was constructed using extensive data linkages between different Swedish registers, diagnosed between 1964 and 2016. Patients in DELIVER are matched 1:10 to reference individuals from the general population on age, sex, municipality and calendar year of first liver disease diagnosis. Longitudinal cross-linked data from several registers allow for identification of outcomes occurring before or after liver disease diagnosis. Further, since July 2005 all dispensed drugs can be identified. In total, 307 768 unique individuals with a diagnosis of a chronic liver disease since 1964 were identified, and these were matched with 3 067 714 reference individuals from the general population. As examples, DELIVER contains data on 90 948 patients with a diagnosis of viral hepatitis; 50 593 patients with alcohol-related liver disease and 13 242 patients with non-alcoholic fatty liver disease. The DELIVER cohort can be used to examine several important research questions. Long-term outcomes of chronic liver diseases, risk factors for disease progression, impact of dispensed drugs, disease panorama and time trends are examples. Here we describe the construction and data availability of DELIVER.

Sections du résumé

BACKGROUND AND AIMS
Swedish nationwide registries can be used to identify patients with a wide range of diagnoses. This information can be used to construct cohorts useful to determine prognosis and identify risk factors for disease progression. Here, we describe a new register-based cohort of patients with a diverse set of chronic liver disease diagnoses in Sweden.
METHODS
The DELIVER (DEcoding the epidemiology of LIVER disease in sweden) was constructed using extensive data linkages between different Swedish registers, diagnosed between 1964 and 2016. Patients in DELIVER are matched 1:10 to reference individuals from the general population on age, sex, municipality and calendar year of first liver disease diagnosis. Longitudinal cross-linked data from several registers allow for identification of outcomes occurring before or after liver disease diagnosis. Further, since July 2005 all dispensed drugs can be identified.
RESULTS
In total, 307 768 unique individuals with a diagnosis of a chronic liver disease since 1964 were identified, and these were matched with 3 067 714 reference individuals from the general population. As examples, DELIVER contains data on 90 948 patients with a diagnosis of viral hepatitis; 50 593 patients with alcohol-related liver disease and 13 242 patients with non-alcoholic fatty liver disease.
CONCLUSIONS
The DELIVER cohort can be used to examine several important research questions. Long-term outcomes of chronic liver diseases, risk factors for disease progression, impact of dispensed drugs, disease panorama and time trends are examples. Here we describe the construction and data availability of DELIVER.

Identifiants

pubmed: 35293282
doi: 10.1080/00365521.2022.2051202
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

978-983

Auteurs

Hannes Hagström (H)

Division of Hepatology, Department of Upper GI, Karolinska University Hospital, Stockholm, Sweden.
Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.

Ying Shang (Y)

Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.

Axel Wester (A)

Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.

Linnea Widman (L)

Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden.
Division of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

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