Self-Report Tool for Identification of Individuals With Coronary Atherosclerosis : The Swedish CardioPulmonary BioImage Study
(2024) In Journal of the American Heart Association 13(14).- Abstract
BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis.
METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home... (More)
BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis.
METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76,
P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly.
CONCLUSIONS: We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.
(Less)
- author
- organization
-
- Cardiovascular Research - Epidemiology (research group)
- EpiHealth: Epidemiology for Health
- Molecular Cardiology (research group)
- Cardiovascular Research - Translational Studies (research group)
- EXODIAB: Excellence of Diabetes Research in Sweden
- Cardiovascular Research - Hypertension (research group)
- publishing date
- 2024-07-03
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of the American Heart Association
- volume
- 13
- issue
- 14
- publisher
- Wiley-Blackwell
- external identifiers
-
- scopus:85199125824
- pmid:38958022
- ISSN
- 2047-9980
- DOI
- 10.1161/JAHA.124.034603
- language
- English
- LU publication?
- yes
- id
- 05c0278e-81fb-4945-bc20-5d5ca4c77495
- date added to LUP
- 2024-07-08 07:13:59
- date last changed
- 2024-11-12 15:49:30
@article{05c0278e-81fb-4945-bc20-5d5ca4c77495, abstract = {{<p>BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis.</p><p>METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76,<br> P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly.<br> </p><p>CONCLUSIONS: We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.</p>}}, author = {{Bergström, Göran and Hagberg, Eva and Björnson, Elias and Adiels, Martin and Bonander, Carl and Strömberg, Ulf and Andersson, Jonas and Brunström, Mattias and Carlhäll, Carl-Johan and Engström, Gunnar and Erlinge, David and Goncalves, Isabel and Gummesson, Anders and Hagström, Emil and Hjelmgren, Ola and James, Stefan and Janzon, Magnus and Jonasson, Lena and Lind, Lars and Magnusson, Martin and Oskarsson, Viktor and Sundström, Johan and Svensson, Per and Söderberg, Stefan and Themudo, Raquel and Östgren, Carl Johan and Jernberg, Tomas}}, issn = {{2047-9980}}, language = {{eng}}, month = {{07}}, number = {{14}}, publisher = {{Wiley-Blackwell}}, series = {{Journal of the American Heart Association}}, title = {{Self-Report Tool for Identification of Individuals With Coronary Atherosclerosis : The Swedish CardioPulmonary BioImage Study}}, url = {{http://dx.doi.org/10.1161/JAHA.124.034603}}, doi = {{10.1161/JAHA.124.034603}}, volume = {{13}}, year = {{2024}}, }