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Validated Model for Prediction of Adverse Cardiac Outcome in Patients With Fabry Disease
Christopher Orsborne1, Joshua Bradley2, Laura J Bonnett3
1Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom; Manchester University NHS Foundation Trust, Wythenshawe, Manchester, United Kingdom; Salford Royal NHS Foundation Trust, Salford, United Kingdom.
Insights
A new risk model for Fabry disease accurately predicts adverse cardiac events using cardiac MRI biomarkers. This tool aids in identifying high-risk patients for better treatment guidance.
Area of Science:
- Cardiology
- Genetics
- Biomarkers
Background:
- Cardiac manifestations of Fabry disease are a leading cause of mortality.
- Current risk stratification for adverse cardiac outcomes is inadequate.
- Prognostic value of cardiac magnetic resonance (CMR) biomarkers needs clarification.
Purpose of the Study:
- Develop and validate a prognostic model for predicting adverse cardiac outcomes in Fabry disease patients.
- Incorporate deep phenotyping and CMR biomarkers for precise risk estimation.
- Create a risk calculator for individual 5-year risk assessment.
Main Methods:
- Longitudinal prospective cohort study of 200 Fabry disease patients.
- Utilized cardiac magnetic resonance (CMR) imaging.
- Developed prognostic models using Cox proportional hazards modeling with a median follow-up of 4.5 years.
Main Results:
- The best model included age, myocardial T1 dispersion, and left ventricular mass.
- Achieved an optimism-adjusted c-statistic of 0.77 (95% CI: 0.70-0.84).
- Demonstrated excellent model calibration across the risk spectrum.
Conclusions:
- A validated risk prediction model for 5-year adverse cardiac outcome in Fabry disease was developed.
- The model accurately predicts risk for both men and women.
- This tool can be integrated into clinical practice, with external validation recommended.
Background:
The cardiac manifestations of Fabry disease are the leading cause of death, but risk stratification remains inadequate. Identifying patients who are at risk of adverse cardiac outcome may facilitate more evidence-based treatment guidance. Contemporary cardiovascular cardiac magnetic resonance biomarkers have become widely adopted, but their prognostic value remains unclear.
Objectives:
The objective of this study was to develop, internally validate, and evaluate the performance of, a prognostic model, including contemporary deep phenotyping, which can be used to generate individual risk estimates for adverse cardiac outcome in patients with Fabry disease.
Methods:
This longitudinal prospective cohort study consisted of 200 consecutive patients with Fabry disease undergoing clinical cardiac magnetic resonance. Median follow-up was 4.5 years (IQR: 2.7-6.3 years). Prognostic models were developed using Cox proportional hazards modeling. Outcome was a composite of adverse cardiac events. Model performance was evaluated. A risk calculator, which provides 5-year estimated risk of adverse cardiac outcome for individual patients, including men and women, was generated.
Results:
The highest performing, internally validated, parsimonious multivariable model included age, native myocardial T1 dispersion (SD of per voxel myocardial T1 relaxation times), and indexed left ventricular mass. Median optimism-adjusted c-statistic across 5 imputed model development data sets was 0.77 (95% CI: 0.70-0.84). Model calibration was excellent across the full risk profile.
Conclusions:
This study developed and internally validated a risk prediction model that accurately predicts 5-year risk of adverse cardiac outcome for individual patients with Fabry disease, including men and women, which could easily be integrated into clinical care. External validation is warranted.
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