Lipids & metabolic liver disease
Cardiovascular Disease Risk Prediction in Patients With Metabolic Dysfunction‐Associated Steatohepatitis
Authors' conclusion
We describe a first-in-kind predictive model to assess the risk of CVD in patients with MASH, which has the potential to more accurately inform the treatment and management of this population.
Study context
- Population
- Patients with MASH, UK Clinical Practice Research Datalink (CPRD)
- Participants
- 10,461 patients
- Exposure
- Accelerated failure time (AFT) prediction models vs QRisk3 algorithm
- Femalen = 5,364
- Malen = 5,097
- Outcome
- Time to CVD
Methodological detailsprediction model development, accelerated failure time models, sex-specific models, Covariables from the QRisk3 algorithm included, Calibration and discrimination determined
- Prediction model development
- Accelerated failure time models
- Sex-specific models
- Covariables from the QRisk3 algorithm included
- Calibration and discrimination determined
Main finding
As reported in the abstract
Predictive performance of AFT models for time to CVD
C-statistics (moderate predictive power)
0.7-0.72
Observational data: associations, not effects.
Original publication
Cardiovascular Disease Risk Prediction in Patients With Metabolic Dysfunction‐Associated Steatohepatitis. Diabetes Obes Metab. Published 31 May 2026. doi:10.
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