Improving the prediction of major adverse cardiovascular events in patients with hypertrophic cardiomyopathy by adding plasma SVEP1 to conventional clinical model including NT-proBNP
Authors: Osawa I , Akita K , Hasegawa K , Fifer M A , Tower-Rader A , Reilly M P , Maurer M S , Stitziel N O , Javaheri A , Shimada Y J 
Published: October 2024

Background

Hypertrophic cardiomyopathy (HCM) is the most common genetic heart disease with a prevalence between 1 in 200 to 500 [1]. HCM can lead to major adverse cardiovascular events (MACE) such as heart failure (HF) hospitalization and cardiac death [2,3]. A protein named "sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1" (SVEP1) is a large extracellular matrix protein whose activity can be measured in plasma [4,5]. SVEP1 promotes inflammation and atherosclerosis [4,5]. SVEP1 is associated with risk of HF hospitalization and cardiac death in patients with HF with reduced ejection fraction [6]. However, no prior study has assessed the prognostic value of SVEP1 in patients with HCM.

Purpose

To test the hypothesis that the addition of SVEP1 improves the predictive performance of the conventional model based on clinical risk factors plus NT-proBNP for future MACE in patients with HCM.

Methods

We performed a multicenter prospective cohort study of patients with HCM [7]. The outcome was MACE, defined as a composite of HF hospitalization or cardiac death [6]. After dividing the cohort into four groups using the median values of SVEP1 and NT-proBNP, we compared the risk of the outcome event using the Cox proportional hazards model adjusting for 15 clinical risk factors known to be associated with MACE in HCM (Figure 1) [8-11]. We also developed the Lasso-regularized Cox proportional hazards model to predict the time to first MACE by adding SVEP1 to the 15 clinical risk factors with or without NT-proBNP in the training cohort (randomly selected 75% of the cohort). We then compared the predictive performance in the test cohort (25% of the cohort) using the C-statistic of each model.

Results

During a median follow-up of 1.9 (25 percentile-75 percentile, 0.7-4.3) years, the outcome event occurred in 63 (10%) of 610 patients. The four groups stratified by the median of SVEP1 and NT-proBNP levels had different risks of the outcome event (log-rank p&lt;0.001: Figure 1). Even in the groups with lower-than-median NT-proBNP levels, the high-SVEP1 group had higher risks of MACE compared with the low-SVEP1 group (adjusted hazard ratio 4.52, p=0.042: Figure 1). In the prediction of time to first MACE, the addition of SVEP1 improved the C-statistic of the clinical model (p&lt;0.001) and that of the clinical plus NT-proBNP model (p=0.01: Figure 2). The clinical plus SVEP1 model also outperformed the clinical plus NT-proBNP model (p=0.005: Figure 2).

Conclusions

In the present multicenter prospective cohort study of 610 patients with HCM, SVEP1 improved MACE risk stratification when added to the conventional model consisting of clinical risk factors plus NT-proBNP. SVEP1 also exhibited a superior predictive ability than NT-proBNP to predict MACE in patients with HCM. These data collectively indicate that SVEP1 provides additional risk stratification and may be a better biomarker than NT-proBNP for the prognostication of patients with HCM.Figure 1.Kaplan-Meier curves for MACEFigure 2.Time-dependent AUROC curves