For Doctors in a Hurry
- Researchers evaluated whether the PREVENT and SCORE2 equations accurately predict cardiovascular risk across diverse global populations and clinical trial settings.
- This validation study analyzed data from 44 observational cohorts and 18 randomized trials involving more than 6.4 million individual participants.
- Both algorithms demonstrated similar discrimination and calibration across regions during a mean follow-up period of 5.1 years.
- The authors concluded that both equations effectively stratify cardiovascular risk despite differences in outcome definitions and specific predictor variables.
- These findings support using these tools to guide lipid and blood pressure-lowering therapy in diverse clinical environments worldwide.
Standardizing Global Cardiovascular Risk Assessment
Cardiovascular disease remains a leading cause of global morbidity, necessitating precise risk stratification to guide primary prevention strategies such as blood pressure control and lipid management [1, 2]. Clinicians rely on validated algorithms to identify high-risk patients who would benefit most from intensive interventions, as seen in major trials targeting lower systolic blood pressure [1]. However, the performance of these tools often varies across different geographic regions and patient populations, complicating the application of international guidelines in daily practice [3, 4]. Furthermore, while chronic conditions like obesity and kidney disease significantly elevate cardiovascular risk, the ability of standard equations to maintain accuracy across diverse global cohorts remains a subject of active clinical investigation [5, 6]. To address this uncertainty, a new large-scale analysis evaluates the reliability of two major risk prediction models across millions of individuals worldwide.
Validation Across Six Million Individuals
To evaluate the global utility of current cardiovascular risk assessment tools, researchers conducted a massive validation study utilizing data from 44 observational cohorts and 18 randomized trials. This analysis focused on two primary models: the American Heart Association PREVENT equations and the SCORE2 risk algorithm. The PREVENT equations are designed to estimate the risk of total cardiovascular disease, atherosclerotic cardiovascular disease, and heart failure for individuals aged 30 to 79 years in the United States. In contrast, the SCORE2 algorithm is utilized to estimate cardiovascular disease risk for individuals aged 40 and older in Europe. By applying these models to diverse datasets, the study sought to determine if tools developed for specific Western populations remain accurate when applied to patients in North America, Europe, and Asia. The scale of the validation included a total study population for the PREVENT equations of 6,422,714 individuals, while the validation for the SCORE2 algorithm encompassed 5,437,384 individuals. The researchers focused on two critical performance metrics: discrimination and calibration. Discrimination (a statistical measure of how well a model correctly distinguishes between patients who will and will not have a clinical event, such as a myocardial infarction) and calibration (the agreement between the predicted risk calculated by the model and the actual observed risk within the patient population) are essential for ensuring that clinical tools do not overprescribe or underprescribe preventive therapies. Despite the inherent differences in how each model defines cardiovascular outcomes and the specific predictor variables they use, both equations demonstrated generally good performance across all geographical regions, including within multi-regional randomized trials.
The validation effort spanned a broad geographic range, encompassing patient data from North America, Europe, and Asia, as well as data from multi-region trials. Over a mean follow-up period of 5.1 years, the researchers tracked a substantial number of clinical outcomes to test the predictive accuracy of both models. Specifically, the study recorded 293,737 PREVENT total cardiovascular disease events, which were defined as a composite of fatal and non-fatal atherosclerotic cardiovascular disease or heart failure. In the cohort evaluated using the European model, there were 258,086 SCORE2 cardiovascular disease events, defined specifically as myocardial infarction, stroke, or cardiovascular death. A critical finding of the study was that overall discrimination and calibration were similar for both equations, even though they utilize different predictor variables and target distinct populations. This reliability persisted despite the differences in cardiovascular disease outcome definitions, where PREVENT includes heart failure and SCORE2 focuses strictly on traditional atherosclerotic events. The researchers noted generally good performance across all regions, including within the complex datasets of multi-regional randomized trials. For practicing physicians, this means that a risk score calculated for a patient in Asia or Europe using these tools is just as reliable for guiding statin or antihypertensive therapy as a score calculated for a patient in the United States.
Clinical Utility and Shorter-Term Prediction
To enhance the flexibility of the American Heart Association model, the researchers created scaling factors for risk prediction over 1 to 9 years using the PREVENT equations. Scaling factors are mathematical adjustments that allow a model originally designed for a 10-year horizon to accurately estimate cardiovascular risk over much shorter intervals. While this technical adjustment is particularly relevant for facilitating clinical trial enrollment, it also offers immediate value in daily practice. For the practicing physician, this capability provides a more granular view of a patient's near-term risk profile, which can be highly effective when counseling a hesitant patient about the immediate benefits of starting pharmacological interventions today rather than waiting a decade. The extensive validation of these models across 44 observational cohorts and 18 randomized trials confirms their utility in a wide array of clinical environments. Because the algorithms maintained consistent accuracy across different geographic regions and trial types, the findings support the adoption of PREVENT or SCORE2 for cardiovascular risk stratification across diverse global settings. This suggests that clinicians can reliably use these tools to guide lipid and blood pressure-lowering therapies in patients worldwide. Ultimately, the study provides the necessary evidence base to integrate these equations into routine practice, ensuring that primary prevention strategies are directed toward those with the highest validated risk of cardiovascular events.
References
1. Group TSR. A Randomized Trial of Intensive versus Standard Blood-Pressure Control. New England Journal of Medicine. 2015. doi:10.1056/nejmoa1511939
2. Davies MJ, D’Alessio DA, Fradkin J, et al. Management of Hyperglycemia in Type 2 Diabetes, 2018. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2018. doi:10.2337/dci18-0033
3. McDonagh TA, Metra M, Adamo M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. European Heart Journal. 2021. doi:10.1093/eurheartj/ehab368
4. Visseren FL, Mach F, Smulders YM, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. European Heart Journal. 2021. doi:10.1093/eurheartj/ehab484
5. Guh D, Zhang W, Bansback N, Amarsi Z, Birmingham CL, Anis AH. The incidence of co-morbidities related to obesity and overweight: A systematic review and meta-analysis. BMC Public Health. 2009. doi:10.1186/1471-2458-9-88
6. Hill NR, Fatoba S, Oke J, et al. Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis. PLoS ONE. 2016. doi:10.1371/journal.pone.0158765
