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Lifetime risk predictions for cardiovascular diseases: competing risks analyses on a population-based cohort in Sweden
Umeå University, Faculty of Medicine, Department of Epidemiology and Global Health.
Umeå University, Faculty of Medicine, Department of Biobank Research. Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.ORCID iD: 0000-0001-6808-4405
Umeå University, Faculty of Medicine, Department of Epidemiology and Global Health.ORCID iD: 0000-0003-2475-7131
Umeå University, Faculty of Medicine, Department of Epidemiology and Global Health.ORCID iD: 0000-0002-0457-2175
2020 (English)In: Atherosclerosis, ISSN 0021-9150, E-ISSN 1879-1484, Vol. 312, p. 90-98Article in journal (Refereed) Published
Abstract [en]

Background and aims: There are guideline discussions on a lifetime approach to cardiovascular risk. Many of the available risk models estimate the short-term, usually 10-year risk of non-fatal and fatal cardiovascular diseases (CVD) grouped together. We aimed to develop lifetime risk models for non-fatal coronary heart disease, stroke, heart failure and death from CVD and non-CVD.

Methods: We included 92,915 individuals who had participated in a community-based lifestyle intervention programme at 40, 50 and/or 60 years of age. Their collected data on selected risk factors were linked to register data on hospitalizations and death. Parametric multivariable survival regression with a competing risks approach was employed to model cause-specific hazards, which were translated into cumulative incidence functions to provide the risk of experiencing each event separately. All analyses were performed gender-age wise. For illustrative purposes, "better" and "worse" risk profiles were created by setting three modifiable risk factors to the best and worst levels, respectively.

Results: Most of the risk factors qualified for inclusion in the regressions. Men had a higher risk of cardiovascular events and the events occurred at a younger age than women. In the created risk profiles, where serum total cholesterol, smoking status and blood pressure were modified, an excessive number of CVD events were observed in the worse profiles.

Conclusions: Using these models, the lifetime risk of each of the first CVD events can be estimated for different risk factor profiles. Since the predictions are diagnosis specific, the estimates are more accurate.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 312, p. 90-98
Keywords [en]
Cardiovascular diseases, Models, Risk factors, Survival analysis, Cohort studies, Middle age
National Category
Cardiac and Cardiovascular Systems Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:umu:diva-175673DOI: 10.1016/j.atherosclerosis.2020.08.014ISI: 000579385700013PubMedID: 33011606Scopus ID: 2-s2.0-85091739665OAI: oai:DiVA.org:umu-175673DiVA, id: diva2:1473383
Available from: 2020-10-06 Created: 2020-10-06 Last updated: 2023-03-24Bibliographically approved

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Stenling, AnnaHäggström, ChristelNorberg, MargaretaNorström, Fredrik

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Department of Epidemiology and Global HealthDepartment of Biobank Research
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Atherosclerosis
Cardiac and Cardiovascular SystemsPublic Health, Global Health, Social Medicine and Epidemiology

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CiteExportLink to record
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