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Predictors of Long-Term Outcomes in Hypertrophic Cardiomyopathy: The NHLBI HCM Registry
, Christopher M Kramer1, Paul Kolm2
1University of Virginia Health, Charlottesville.
Insights
Improved hypertrophic cardiomyopathy risk prediction combines cardiac magnetic resonance imaging and NT-proBNP levels. This approach enhances accuracy, potentially reducing adverse events and unnecessary device implants for better patient outcomes.
Area of Science:
- Cardiology
- Medical Imaging
- Biomarkers
Background:
- Current hypertrophic cardiomyopathy risk stratification focuses on sudden cardiac death, with limitations leading to preventable mortality and overtreatment.
- Existing guidelines are imperfect, necessitating improved prediction models for adverse events.
Purpose of the Study:
- To develop a more accurate risk prediction model for adverse events in hypertrophic cardiomyopathy.
- To integrate clinical history, cardiac magnetic resonance (CMR) imaging, genetic data, and biomarkers.
Main Methods:
- A prospective registry study enrolled 2750 patients with hypertrophic cardiomyopathy across 44 North American and European centers.
- Patients underwent comprehensive assessments including questionnaires, biomarker analysis, genotyping, and contrast-enhanced CMR.
- Follow-up data were collected yearly to document adverse events.
Main Results:
- The primary event model identified left ventricular (LV) scar by late gadolinium enhancement (LGE%), LV mass index, LV end-systolic volume index, heart failure history, and NT-proBNP as significant predictors (C-index, 0.77).
- An LGE percentage of 9% or higher substantially increased the risk of primary composite events.
- The secondary model for sudden cardiac death and ventricular arrhythmias included LGE%, LV mass index, LV ejection fraction, and log(NT-proBNP) (C-index, 0.76).
Conclusions:
- Prospective data support the integration of CMR imaging and NT-proBNP levels into hypertrophic cardiomyopathy risk assessment.
- This enhanced approach promises more precise risk stratification for hypertrophic cardiomyopathy patients.
- Improved prediction can guide clinical decisions, potentially preventing deaths and reducing unnecessary interventions.
Importance:
Current risk prediction guidelines for hypertrophic cardiomyopathy predict only sudden cardiac death and are imperfect, leading to avoidable deaths and unnecessary implantable cardioverter defibrillators.
Objective:
To combine prospectively collected clinical history, imaging, genetic, and biomarker data to improve risk prediction of adverse events in hypertrophic cardiomyopathy.
Design, Setting, And Participants:
A total of 2750 patients with hypertrophic cardiomyopathy were prospectively enrolled in the registry-based study from 44 sites in North America and Europe with expertise in hypertrophic cardiomyopathy and cardiac magnetic resonance (CMR) imaging. Participants were enrolled from April 1, 2014, to April 7, 2017.
Exposures:
Patients underwent a health history questionnaire, blood sampling for biomarkers and genotyping, and contrast-enhanced CMR. Patients were followed up yearly by telephone and through records review regarding event documentation.
Main Outcomes And Measures:
The predefined composite adjudicated primary end point was time to first event for hypertrophic cardiomyopathy-related deaths; nonfatal sustained ventricular arrhythmias (VAs) requiring cardioversion or defibrillation; and left ventricular (LV) assist device implant or heart transplant. A secondary end point was a composite of sudden cardiac death and nonfatal VA events. The elastic-net method identified the most important predictors. Cox proportional hazards regression assessed associations with time to the first end point.
Results:
Of the 2750 prospectively enrolled patients, 2698 (98%) had analyzable data after 9 were excluded because they had hypertrophic cardiomyopathy phenocopies and 43 withdrew. Of these remaining patients, 1919 (71%) were male, mean age was 50 years (SD, 11 years), and 423 (16%) were from underrepresented racial and minority groups. The mean follow-up was 6.9 years (SD, 2.1 years). The primary event model in 104 patients included LV scar as a percentage of LV mass by late gadolinium enhancement (LGE%; hazard ratio [HR], 1.86; 95% CI, 1.58-2.20; P < .001), LV mass index (HR, 1.09; 95% CI, 1.01-1.17; P = .03), LV end-systolic volume index (HR, 1.28; 95% CI, 1.12-1.46; P < .001 ), all per 10-unit increase, history of heart failure at study entry (HR, 2.89; 95% CI, 1.75-4.77; P < .001), and log N-terminal pro-B-type natriuretic peptide (NT-proBNP; HR, 1.41; 95% CI, 1.17-1.70; P < .001) level per log unit, (C index for all, 0.77). An LGE percentage of the LV mass of 9% or higher substantially increased the primary composite event rate (P = .001). The secondary sudden cardiac death and VA risk factor model (in 69 patients) included LGE%, LV mass index, LV ejection fraction, and log(NT-proBNP) (C index, 0.76).
Conclusions And Relevance:
These results provide prospective evidence for incorporating cardiac magnetic resonance and NT-proBNP in the evaluation of patients with hypertrophic cardiomyopathy.
Trial Registration:
ClinicalTrials.gov Identifier: NCT01915615.
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