Blood-based biomarkers for the prediction of hypertrophic cardiomyopathy prognosis: a systematic review and meta-analysis

Abstract

Aims: Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease. HCM is an important cause of sudden cardiac death and may also lead to outflow tract obstruction and heart failure. Disease severity is highly variable and risk stratification remains limited. Therefore, we aimed to review current knowledge of prognostic blood-based biomarkers in HCM.

Methods and results: A systematic literature search was performed on PubMed, Embase, and the Cochrane library to identify studies assessing plasma or serum biomarkers for outcomes involving malignant ventricular arrhythmia, outflow tract obstruction, and heart failure. Risk of bias was assessed using the QUIPS tool. Meta-analyses were performed using the random effects method. A total of 26 unique cohort studies assessing 42 biomarkers were identified. Overall risk of bias was moderate. Thirty-two biomarkers were significantly associated to an HCM outcome in at least one study (nine biomarkers in at least two studies). In pooled analyses, cardiovascular mortality was predicted by N-terminal prohormone of brain natriuretic peptide (hazard ratio [HR] 5.38 per log[pg/mL], 95% confidence interval [CI] 2.07-14.03, P < 0.001, I² = 0%) and high-sensitivity C-reactive protein (HR 1.30 per μg/mL, 95% CI 1.00-1.68, P = 0.05, I² = 78%), all-cause mortality by low-density lipoprotein cholesterol (HR 0.63 per μmol/mL, 95% CI 0.49-0.80, P < 0.001, I² = 0%), and a combined congestive heart failure, malignant ventricular arrhythmia, and stroke outcome by high-sensitivity cardiac troponin T (pooled HR 4.19 for ≥0.014 ng/mL, 95% CI 2.22-7.88, P < 0.001, I² = 0%). Quality of evidence was low-moderate.

Conclusions: Several blood-based biomarkers were identified as predictors of HCM outcomes. Additional studies are required to validate their prognostic utility within current risk stratification models.

Keywords: Biomarker; Heart failure; Hypertrophic cardiomyopathy; Prognosis; Sudden cardiac death; Systematic review.

Figure 1

Study inclusion flow diagram. Flow diagram of study inclusion showing the reasons for exclusion during full‐text screening. The numbers within square brackets indicate the number of studies without potential cohort overlap.

Figure 2

Risk of bias assessment. Review authors' judgement regarding risk of bias for each included study, assessed using the Quality in Prognostic Studies tool. Green circles with a plus sign (+) indicate low risks of bias, yellow triangles with a plus–minus sign (±) indicate moderate risks of bias, and red diamonds with a minus sign (−) indicate high risks of bias.

Figure 3

Pooled analyses. Forest plots of the hazard ratios eligible for pooled analysis, stratified per biomarker. Outcomes included (A) cardiovascular mortality, (B) all‐cause mortality, and (C) cardiovascular events (congestive heart failure, malignant ventricular arrythmia, and stroke). Pooled analyses were performed using an inverse variance, random effects model. The I ² index was used to assess statistical heterogeneity. CI, confidence interval; hs‐CRP, high‐sensitivity C‐reactive protein; hs‐cTnT, high‐sensitivity cardiac troponin T; IV, inverse variance; LDL, low‐density lipoprotein; NT‐proBNP, N‐terminal prohormone of brain natriuretic peptide.