Variable and Limited Predictive Value of the European Society of Cardiology Hypertrophic Cardiomyopathy Sudden-Death Risk Model: A Meta-analysis

Abstract

Background: We performed a systematic review and meta-analysis to assess the discrimination performance of the 2014 European Society of Cardiology (ESC) sudden cardiac death (SCD) risk-prediction model for hypertrophic cardiomyopathy (HCM).

Methods: We searched the PubMed, Embase and Web of Science, CNKI, WanFang, and China Biology Medicine disc (CBMdisc) databases for English and Chinese articles validating the risk model. The model's discrimination performance with cutoff points of 4% and 6% based on extracted information was calculated. The extracted C statistic and calculated area under the curve (AUC) with 95% confidence intervals (CIs) of all studies were weighted and summarized. Heterogeneity was quantified through I² statistics; sensitivity analysis and publication bias were assessed with Egger's test.

Results: We included 13 studies validating the model's usefulness. We concluded that the model has excellent specificity, although it has poor sensitivity when setting a recommended cutoff value of 6% for identifying high-risk patients with HCM. In addition, there was moderate discrimination value (global C statistic = 0.75, 95% CI, 0.67-0.83; cutoff point of ≥ 4%; AUC = 0.69, 95% CI, 0.62-0.75; cutoff point of ≥ 6%; AUC = 0.65, 95% CI, 0.59-0.72). Subgroup analysis by region showed slightly weaker predictive ability for North America. There was no significant publication bias (all P > 0.05); sensitivity analysis did not change the results significantly.

Conclusions: The 2014 ESC HCM SCD risk-prediction model has excellent specificity and poor sensitivity and has moderate discrimination performance. In addition, it may have lower prediction value for North America compared with other regions.