Ceramide-based risk score CERT-1 improves risk prediction for overall mortality and adverse cardiovascular outcomes in patients with and without cardiovascular disease: A prospective cohort study

Abstract

Aims: Whether the plasma-based ceramide-based risk score CERT1 improves risk prediction for cardiovascular disease (CVD) is uncertain.

Materials and methods: Baseline and follow-up data were combined from two cohorts, 334 patients with established/suspected CVD and 196 patients with type 2 diabetes followed for a median of 74 months (interquartile range 54-79 months). For the calculation of CERT1 risk score, we measured four specific plasma ceramides [Cer(d18:1/16:0), Cer(d18:1/18:0) and Cer(d18:1/24:1)] and their ratios to Cer(d18:1/24:0). Based on the CERT1 risk score, patients were split into four risk categories (low, moderate, increased or high risk). The primary outcome was a composite of overall mortality and incident nonfatal CVD outcomes (including myocardial infarction, ischaemic stroke or permanent atrial fibrillation).

Results: One hundred and thirty-nine patients developed the primary composite outcome (72 nonfatal CVD outcomes and 67 total deaths) during follow-up. Baseline CERT1 risk categories were significantly associated with the risk of developing the primary composite outcome (adjusted HR for high vs. low-risk category 2.43, 95% CI 1.39-4.22, p = 0.002, and adjusted HR for increased vs. low-risk category 2.16, 95% CI 1.28-3.63, p = 0.004). Receiver operator characteristic curve analysis showed that adding CERT1 risk score to traditional CVD risk factors and pre-existing CVD, improved the discriminatory capability of the regression model for predicting the primary composite outcome (AUROC 0.691 [95% CI 0.674-0.769] vs. 0.722 [95% CI 0.642-0.742], p = 0.0275).

Conclusions: The ceramide-based risk score CERT1 risk score improves risk prediction for long-term risk of overall mortality and adverse cardiovascular outcomes in patients with and without CVD.

Keywords: CERT1 score; CVD; cardiovascular morbidity; mortality; plasma ceramides.

FIGURE 1

Cumulative incidence rates of participants who developed the primary composite outcome at follow‐up stratified by the CERT1 risk categories at baseline (low vs. moderate vs. increased vs. high risk) (p = 0.0003 by the log‐rank test).

FIGURE 2

Subgroup analyses. Associations between the CERT1 risk categories at baseline (low risk [included as reference category] vs. moderate vs. increased vs. high risk) and the risk of developing the primary composite outcome in specific patient subgroups.

FIGURE 3

Receiver operating characteristic (ROC) curves and areas under the curves (AUROC) for estimating the discrimination of two predictive regression models between patients who developed the primary composite outcome and those did not. The predictive model 1 (blue curve) included traditional CVD risk factors, such as age, sex, smoking, hypertension, diabetes, prior history of CVD and use of antiplatelet or statin medications. The predictive regression model 2 (red curve) included these risk factors plus CERT1 risk score categories (p = 0.0275 for comparison by the DeLong test).