Ascertainment of Dementia Cases in the Spanish European Prospective Investigation into Cancer and Nutrition-Murcia Cohort.


Journal

Neuroepidemiology
ISSN: 1423-0208
Titre abrégé: Neuroepidemiology
Pays: Switzerland
ID NLM: 8218700

Informations de publication

Date de publication:
2019
Historique:
received: 29 01 2018
accepted: 25 08 2018
pubmed: 27 11 2018
medline: 20 12 2019
entrez: 27 11 2018
Statut: ppublish

Résumé

Cohort studies generally focus on a particular disease, although they offer the possibility of evaluating different outcomes with minimal additional investment. The objective of this study was to describe the methodology used to assess dementia in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Murcia study. The EPIC-Murcia cohort consists of 8,515 healthy participants (68% women, aged 30-70 years), recruited between 1992 and 1996 and followed up for over 20 years. Incident cases were ascertained by a 2-step protocol: a record linkage with health databases to identify potential events and a review of medical records of potential cases to validate incident cases. Overall, 1,202 potential cases were identified, and 275 dementia cases were validated. Medical reports were the source of information in 243 cases, with complete neurological information in 227, and a high degree of certainty of the diagnosis in 229 cases. P70 (dementia code) and/or antidementia drugs and/or ICD codes identified 259 cases (sensitivity: 94.2%, 95% CI 90.7-96.6; specificity: 98.1%, 95% CI 97.8-98.4). Ascertainment of incident dementia in the EPIC-Murcia cohort study was feasible using information from medical records. This systematic 2-step validation protocol is proposed as a feasible way to ascertain dementia in cohort studies originally designed for other endpoints.

Sections du résumé

BACKGROUND
Cohort studies generally focus on a particular disease, although they offer the possibility of evaluating different outcomes with minimal additional investment. The objective of this study was to describe the methodology used to assess dementia in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Murcia study.
METHODS
The EPIC-Murcia cohort consists of 8,515 healthy participants (68% women, aged 30-70 years), recruited between 1992 and 1996 and followed up for over 20 years. Incident cases were ascertained by a 2-step protocol: a record linkage with health databases to identify potential events and a review of medical records of potential cases to validate incident cases.
RESULTS
Overall, 1,202 potential cases were identified, and 275 dementia cases were validated. Medical reports were the source of information in 243 cases, with complete neurological information in 227, and a high degree of certainty of the diagnosis in 229 cases. P70 (dementia code) and/or antidementia drugs and/or ICD codes identified 259 cases (sensitivity: 94.2%, 95% CI 90.7-96.6; specificity: 98.1%, 95% CI 97.8-98.4).
CONCLUSION
Ascertainment of incident dementia in the EPIC-Murcia cohort study was feasible using information from medical records. This systematic 2-step validation protocol is proposed as a feasible way to ascertain dementia in cohort studies originally designed for other endpoints.

Identifiants

pubmed: 30476922
pii: 000493209
doi: 10.1159/000493209
doi:

Types de publication

Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

63-73

Informations de copyright

© 2018 S. Karger AG, Basel.

Auteurs

María Encarnación Andreu-Reinón (ME)

Murcia Regional Health Council, Murcia, Spain, m.encarna.andreu@gmail.com.
Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain, m.encarna.andreu@gmail.com.

Diana Gavrila (D)

Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.

María Dolores Chirlaque (MD)

Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Department of Health and Social Sciences, University of Murcia, Murcia, Spain.

Sandra M Colorado-Yohar (SM)

Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia.

Pilar Amiano (P)

CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Public Health Division of Gipuzkoa, Instituto BIO-Donostia, Basque Government, Donostia/San Sebastián, Spain.

Eva Ardanaz (E)

CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Public Health Institute of Navarra, IDISNA, Pamplona, Spain.

Fernando Navarro-Mateu (F)

CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Unidad de Docencia, Investigación y Formación en Salud Mental (UDIF-SM), Servicio Murciano de Salud, IMIB-Arrixaca, Murcia, Spain.

Carmen Navarro (C)

Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Department of Health and Social Sciences, University of Murcia, Murcia, Spain.

José María Huerta (JM)

Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain.
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.

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