Population Specific and Up to Date Cardiovascular Risk Charts Can Be Efficiently Obtained with Record Linkage of Routine and Observational Data

David Faeh, Julia Braun, Kaspar Rufibach, Milo A. Puhan, Pedro Marques-Vidal, Matthias Bopp

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Only few countries have cohorts enabling specific and up-to-date cardiovascular disease (CVD) risk estimation. Individual risk assessment based on study samples that differ too much from the target population could jeopardize the benefit of risk charts in general practice. Our aim was to provide up-to-date and valid CVD risk estimation for a Swiss population using a novel record linkage approach. Methods: Anonymous record linkage was used to follow-up (for mortality, until 2008) 9,853 men and women aged 25-74 years who participated in the Swiss MONICA (MONItoring of trends and determinants in CVD) study of 1983-92. The linkage success was 97.8%, loss to follow-up 1990-2000 was 4.7%. Based on the ESC SCORE methodology (Weibull regression), we used age, sex, blood pressure, smoking, and cholesterol to generate three models. We compared the 1) original SCORE model with a 2) recalibrated and a 3) new model using the Brier score (BS) and cross-validation. Results: Based on the cross-validated BS, the new model (BS = 14107×10-6) was somewhat more appropriate for risk estimation than the original (BS = 14190×10-6) and the recalibrated (BS = 14172×10-6) model. Particularly at younger age, derived absolute risks were consistently lower than those from the original and the recalibrated model which was mainly due to a smaller impact of total cholesterol. Conclusion: Using record linkage of observational and routine data is an efficient procedure to obtain valid and up-to-date CVD risk estimates for a specific population.

Original languageEnglish (US)
Article numbere56149
JournalPLoS One
Volume8
Issue number2
DOIs
StatePublished - Feb 14 2013

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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