Key result
Integrating genetics into the ESC SCD risk model reduces the prophylactic ICD NNT to 9.
Why the study?
European and US cardiac societies have established different risk models to prevent SCD in HCM, prompting validation of these methods in a German cohort and evaluation of whether adding genotype information improves them.
Does the addition of genotype information to established clinical variables improve sudden cardiac death risk stratification in adult patients with hypertrophic cardiomyopathy?
Cohort (n=283)
No
Does the addition of genotype information to established clinical variables improve sudden cardiac death risk stratification in adult patients with hypertrophic cardiomyopathy?
Effect estimate: AUC 0.76 (95% CI 0.71-0.81)
Absolute Event Rate: 0.76% vs 0.74%
p-value: p=<0.0001
Integrating genetic findings into current SCD risk stratification methods for hypertrophic cardiomyopathy improves risk prediction and reduces the number-needed-to-treat for prophylactic ICD implantation.
May enhance HCM SCD stratification; leaves open whether genotype integration alters ICD decisions in practice.
BACKGROUND AND AIMS: The cardiac societies of Europe and the United States have established different risk models for preventing sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). The aim of this study is to validate current SCD risk prediction methods in a German HCM cohort and to improve them by the addition of genotype information. METHODS: HCM patients without prior SCD or equivalent arrhythmic events ≥ 18 years of age were enrolled in an expert cardiomyopathy center in Germany. The primary endpoint was defined as SCD/-equivalent within 5 years of baseline evaluation. 5-year SCD-risk estimates and recommendations for ICD implantations, as defined by the ESC and AHA/ACC guidelines, were analyzed. Multivariate cox proportional hazards analyses were integrated with genetic findings as additive SCD risk. RESULTS: 283 patients were included and followed for in median 5.77 years (2.92; 8.85). A disease-causing variant was found in 138 (49%) patients. 14 (5%) patients reached the SCD endpoint (5-year incidence 4.9%). Kaplan-Meier survival analysis shows significantly lower overall SCD event-free survival for patients with an identified disease-causing variant (p < 0.05). The ESC HCM Risk-SCD model showed an area-under-the-curve (AUC) of 0.74 (95% CI 0.68-0.79; p < 0.0001) with a sensitivity of 0.29 (95% CI 0.08-0.58) and specificity of 0.83 (95% CI 0.78-0.88) for a risk estimate ≥ 6%/5-years. By comparison, the AHA/ACC HCM SCD risk stratification model showed an AUC of 0.70 (95% CI 0.65-0.76; p = 0.003) with a sensitivity of 0.93 (95% CI, 0.66-0.998) and specificity of 0.28 (95% CI 0.23-0.34) at the respective cut-off. The modified SCD Risk Score with genetic information yielded an AUC of 0.76 (95% CI 0.71-0.81; p < 0.0001) with a sensitivity of 0.86 (95% CI 0.57-0.98) and specificity of 0.69 (95% CI 0.63-0.74). The number-needed-to-treat (NNT) to prevent 1 SCD event by prophylactic ICD-implantation is 13 for the ESC model, 28 for AHA/ACC and 9 for the modified Genotype-model. CONCLUSION: This study confirms the performance of current risk models in clinical decision making. The integration of genetic findings into current SCD risk stratification methods seem feasible and can add in decision making, especially in borderline risk-groups. A subgroup of patients with high SCD risk remains unidentified by current risk scores.
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Amr et al. (2023) conducted a cohort in Hypertrophic cardiomyopathy (n=283). Modified Genotype-model vs. ESC HCM Risk-SCD model was evaluated on Sudden cardiac death or equivalent event within 5 years (AUC 0.76, 95% CI 0.71-0.81, p=<0.0001). Integrating genetic findings into the ESC sudden cardiac death risk model improved the area-under-the-curve to 0.76 and reduced the number-needed-to-treat for prophylactic ICD implantation to 9.
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