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Cardiovascular Risk Assessment Tools are Insufficient for Patients With Metabolic Dysfunction-Associated Steatotic
A Sidney Barritt1, Elliot B Tapper2, Philip N Newsome3
1UNC Liver Center, University of North Carolina, Chapel Hill, North Carolina, USA.
Insights
Cardiovascular risk scores like FRS and PCE perform poorly in patients with MASLD. New tools are needed to accurately assess cardiovascular event risk in this population.
Area of Science:
- Cardiology
- Hepatology
- Public Health
Background:
- Cardiovascular (CV) event risk is typically estimated using Framingham Risk Score (FRS), Pooled Cohort Equation (PCE), and AHA PREVENT equation.
- The accuracy of these established risk assessment tools in patients with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) remains uncertain.
Purpose of the Study:
- To evaluate the predictive accuracy of FRS, PCE, and PREVENT for 5-10 year CV events in a real-world MASLD cohort.
- To assess the calibration and discrimination of these risk prediction models in the MASLD population.
Main Methods:
- Analysis of US adults (≥30 years) with MASLD from the TARGET-NASH study.
- Estimation of CV risk using original and recalibrated FRS and PCE, and original PREVENT equation.
- Assessment of model discrimination (C-statistic) and calibration (Hosmer-Lemeshow test).
Main Results:
- The Framingham Risk Score (FRS) showed weak predictive ability (C-statistic 0.58).
- The AHA PREVENT model also demonstrated limited discrimination (C-statistic 0.60).
- Both FRS and PCE exhibited significant calibration issues, overestimating risk in high-risk groups and underestimating in low-risk groups.
Conclusions:
- Standard cardiovascular risk prediction tools are inadequate for patients with MASLD.
- There is a critical need for improved risk assessment strategies to address the high mortality from CV events in MASLD patients.
Introduction:
Risk of cardiovascular (CV) events is estimated by the Framingham Risk Score (FRS), Pooled Cohort Equation (PCE), and the American Heart Association Predicting Risk of cardiovascular disease (CVD) EVENTs (PREVENT) equation. The applicability of these risk tools in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) is uncertain. This study sought to determine the accuracy of the FRS, PCE, and PREVENT in a real-world cohort of patients with MASLD.
Methods:
This analysis included US adults 30 years and older with MASLD in the TARGET-NASH study. Five to ten-year CV risk was estimated using original and recalibrated versions of the FRS and PCE, and original PREVENT equation. Discrimination among prediction models was assessed using the Harrell concordance statistic, and calibration was evaluated using a modified Hosmer Lemeshow test comparing observed and predicted CV events. Logistic regression was used to assess the contribution of liver disease to observed CV events.
Results:
Overall, 1,090 patients were included. There was an increase in observed CV events from metabolic dysfunction-associated steatotic livers to cirrhosis. FRS demonstrated a weak ability to identify patients who went on to experience a CV event (C-statistic 0.58, 95% confidence interval 0.52-0.63) as did the American Heart Association PREVENT model (C-statistic 0.60, 95% confidence interval 0.54-0.65). Both the FRS and PCE demonstrated a significant lack of calibration ( P < 0.01), with overestimation in the highest deciles and underestimation in the lowest deciles of predicted risk.
Discussion:
Commonly used tools to identify CV risk performed poorly in a cohort of patients with MASLD. Because CV related death is the greatest source of mortality among patients with MASLD, better risk assessment tools are required.
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