Key result
The DCM-PROGRESS model accurately predicted the 5-year risk of end-stage heart failure in patients with non-ischemic dilated cardiomyopathy, achieving a c-statistic of 0.75 in external validation.
Why the study?
Non-ischemic dilated cardiomyopathy patients face a considerable risk of end-stage heart failure, but models to predict 5-year risk to guide tailored monitoring and management were needed.
Does the DCM-PROGRESS model accurately predict the 5-year risk of end-stage heart failure in patients with non-ischemic dilated cardiomyopathy compared to the MAGGIC score?
Cohort (n=528)
Yes
Does the DCM-PROGRESS model accurately predict the 5-year risk of end-stage heart failure in patients with non-ischemic dilated cardiomyopathy compared to the MAGGIC score?
Effect estimate: c-statistic 0.75 (95% CI 0.61; 0.82)
Absolute Event Rate: 0.75% vs 0.69%
The DCM-PROGRESS model, utilizing six routinely collected clinical variables, provides highly discriminative 5-year risk prediction for end-stage heart failure in non-ischemic DCM patients, outperforming the standard MAGGIC score.
Aims: Patients with non-ischemic dilated cardiomyopathy (DCM) are at considerable risk for end-stage heart failure (HF), requiring close monitoring to identify early signs of disease. We aimed to develop a model to predict the 5-years risk of end-stage HF, allowing for tailored patient monitoring and management. Methods and results: Derivation data were available from a Dutch cohort of 293 DCM patients, with external validation available from a Czech Republic cohort of 235 DCM patients. Candidate predictors spanned patient and family histories, ECG and echocardiogram measurements, and biochemistry. End-stage HF was defined as a composite of death, heart transplantation, or implantation of a ventricular assist device. Lasso and sigmoid kernel support vector machine (SVM) algorithms were trained using cross-validation. During follow-up 65 (22%) of Dutch DCM patients developed end-stage HF, with 27 (11%) cases in the Czech cohort. Out of the two considered models, the lasso model (retaining NYHA class, heart rate, systolic blood pressure, height, R-axis, and TAPSE as predictors) reached the highest discriminative performance (testing c-statistic of 0.85, 95%CI 0.58; 0.94), which was confirmed in the external validation cohort (c-statistic of 0.75, 95%CI 0.61; 0.82), compared to a c-statistic of 0.69 for the MAGGIC score. Both the MAGGIC score and the DCM-PROGRESS model slightly over-estimated the true risk, but were otherwise appropriately calibrated. Conclusion: We developed a highly discriminative risk-prediction model for end-stage HF in DCM patients. The model was validated in two countries, suggesting the model can meaningfully improve clinical decision-making.
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Schmidt et al. (2023) conducted a cohort in non-ischemic dilated cardiomyopathy (n=528). DCM-PROGRESS model vs. MAGGIC score was evaluated on 5-year risk of end-stage heart failure (composite of death, VAD implantation, or heart transplantation) (c-statistic 0.75, 95% CI 0.61; 0.82). The DCM-PROGRESS model accurately predicted the 5-year risk of end-stage heart failure in patients with non-ischemic dilated cardiomyopathy, achieving a c-statistic of 0.75 in external validation.
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