Is the SMART risk prediction model ready for real-world implementation? A validation study in a routine care setting of approximately 380 000 individuals
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Published version
Supplementary information
Author(s)
Type
Journal Article
Abstract
AIMS: Reliably quantifying event rates in secondary prevention could aid clinical decision-making, including quantifying potential risk reductions of novel, and sometimes expensive, add-on therapies. We aimed to assess whether the SMART risk prediction model performs well in a real-world setting. METHODS AND RESULTS: We conducted a historical open cohort study using UK primary care data from the Clinical Practice Research Datalink (2000-2017) diagnosed with coronary, cerebrovascular, peripheral, and/or aortic atherosclerotic cardiovascular disease (ASCVD). Analyses were undertaken separately for cohorts with established (≥6 months) vs. newly diagnosed ASCVD. The outcome was first post-cohort entry occurrence of myocardial infarction, stroke, or cardiovascular death. Among the cohort with established ASCVD [n = 244 578, 62.1% male, median age 67.3 years, interquartile range (IQR) 59.2-74.0], the calibration and discrimination achieved by the SMART model was not dissimilar to performance at internal validation [Harrell's c-statistic = 0.639, 95% confidence interval (CI) 0.636-0.642, compared with 0.675, 0.642-0.708]. Decision curve analysis indicated that the model outperformed treat all and treat none strategies in the clinically relevant 20-60% predicted risk range. Consistent findings were observed in sensitivity analyses, including complete case analysis (n = 182 482; c = 0.624, 95% CI 0.620-0.627). Among the cohort with newly diagnosed ASCVD (n = 136 445; 61.0% male; median age 66.0 years, IQR 57.7-73.2), model performance was weaker with more exaggerated risk under-prediction and a c-statistic of 0.559, 95% CI 0.556-0.562. CONCLUSIONS: The performance of the SMART model in this validation cohort demonstrates its potential utility in routine healthcare settings in guiding both population and individual-level decision-making for secondary prevention patients.
Date Issued
2022-03-01
Date Acceptance
2021-05-21
Citation
European Journal of Preventive Cardiology, 2022, 29 (4), pp.654-663
ISSN
2047-4873
Publisher
Oxford University Press
Start Page
654
End Page
663
Journal / Book Title
European Journal of Preventive Cardiology
Volume
29
Issue
4
Copyright Statement
© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/34160035
PII: 6308229
Subjects
Cardiovascular disease
Risk calculator
Risk prediction
Secondary prevention
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2021-06-23