Assessing two methods for estimating excess mortality of chronic diseases from aggregated data.


Journal

BMC research notes
ISSN: 1756-0500
Titre abrégé: BMC Res Notes
Pays: England
ID NLM: 101462768

Informations de publication

Date de publication:
10 Apr 2020
Historique:
received: 06 11 2019
accepted: 28 03 2020
entrez: 18 4 2020
pubmed: 18 4 2020
medline: 12 1 2021
Statut: epublish

Résumé

To assess the numerical properties of two recently published estimation techniques for excess mortality based on aggregated data about diabetes in Germany. Application of the new methods to the claims data yields implausible findings for the excess mortality of type 2 diabetes in ages below 50 years of age.

Identifiants

pubmed: 32299486
doi: 10.1186/s13104-020-05046-w
pii: 10.1186/s13104-020-05046-w
pmc: PMC7161167
doi:

Types de publication

Evaluation Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

216

Références

Theor Popul Biol. 2014 Mar;92:62-8
pubmed: 24333220
Nutr Metab Cardiovasc Dis. 2018 Sep;28(9):887-891
pubmed: 29960839
Diabet Med. 2015 Jan;32(1):47-53
pubmed: 25132043
BMC Public Health. 2019 Jun 28;19(1):844
pubmed: 31253126
Math Med Biol. 2015 Dec;32(4):425-35
pubmed: 25576933

Auteurs

Ralph Brinks (R)

Institute for Biometry and Epidemiology, German Diabetes Center, Auf'm Hennekamp 65, 40225, Duesseldorf, Germany. ralph.brinks@ddz.de.
Department and Hiller Research Unit for Rheumatology, University Hospital Duesseldorf, Moorenstr. 5, 40225, Duesseldorf, Germany. ralph.brinks@ddz.de.

Thaddäus Tönnies (T)

Institute for Biometry and Epidemiology, German Diabetes Center, Auf'm Hennekamp 65, 40225, Duesseldorf, Germany.

Annika Hoyer (A)

Institute for Biometry and Epidemiology, German Diabetes Center, Auf'm Hennekamp 65, 40225, Duesseldorf, Germany.

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Classifications MeSH