Evolving biomarkers improve prediction of long‐term mortality in patients with stable coronary artery disease: the BIO‐VILCAD score

Abstract

Objective Algorithms to predict the future long‐term risk of patients with stable coronary artery disease (CAD) are rare. The VIenna and Ludwigshafen CAD (VILCAD) risk score was one of the first scores specifically tailored for this clinically important patient population. The aim of this study was to refine risk prediction in stable CAD creating a new prediction model encompassing various pathophysiological pathways. Therefore, we assessed the predictive power of 135 novel biomarkers for long‐term mortality in patients with stable CAD. Design, setting and subjects We included 1275 patients with stable CAD from the LUdwigshafen RIsk and Cardiovascular health study with a median follow‐up of 9.8 years to investigate whether the predictive power of the VILCAD score could be improved by the addition of novel biomarkers. Additional biomarkers were selected in a bootstrapping procedure based on Cox regression to determine the most informative predictors of mortality. Results The final multivariable model encompassed nine clinical and biochemical markers: age, sex, left ventricular ejection fraction (LVEF), heart rate, N‐terminal pro‐brain natriuretic peptide, cystatin C, renin, 25OH‐vitamin D3 and haemoglobin A1c. The extended VILCAD biomarker score achieved a significantly improved C‐statistic (0.78 vs. 0.73; P = 0.035) and net reclassification index (14.9%; P < 0.001) compared to the original VILCAD score. Omitting LVEF, which might not be readily measureable in clinical practice, slightly reduced the accuracy of the new BIO‐VILCAD score but still significantly improved risk classification (net reclassification improvement 12.5%; P < 0.001). Conclusion The VILCAD biomarker score based on routine parameters complemented by novel biomarkers outperforms previous risk algorithms and allows more accurate classification of patients with stable CAD, enabling physicians to choose more personalized treatment regimens for their patients.

Significant association between Cystatin C, Gensini score, and Potential biomarker for Increased Risk of coronary artery lesions

“…Past studies have disclosed the strong relationship between high serum levels of Cystatin C and the stable coronary artery disease [7], acute coronary syndrome (ACS), non-ST-elevation acute coronary syndrome (NSTEMI) [17] and ST elevated myocardial infarction (STEMI) [6]. The aim of current study was to investigate the relationship between the serum level of cystatin C and coronary artery lesions in CAD patients.…”

“…Previous studies have proposed Cystatin C as a novel biomarker for serum creatinine in the evaluation of early impaired renal dysfunction, predominantly to distinguish small drops in GFR [3,4]. Of interest, cystatin C has also been proposed as a useful biomarker for cardiovascular risk and associated with the mortality in diverse clinical scenarios [5][6][7].…”

Potential impacts of high-sensitivity creatine kinase-MB on long-term clinical outcomes in patients with stable coronary heart disease

“…Combination of multiple markers usually may enhance the risk assessment of CV disease. Kleber et al developed a new Vienna and Ludwigshafen CAD (VILCAD) biomarker risk score, which is a composite of age, haemoglobin A1c, LVEF, heart rate, NT-proBNP, sex, renin, 25-OH vitamin D, and cystatin C to predict the future long-term prognosis of patients with SCHD 27 . Compared to the original VILCAD score which did not include novel biomarkers, the new VILCAD biomarker risk score represents a valuable tool for risk prediction in patients with SCHD.…”

Can the onset of heart failure be delayed by treating diabetic cardiomyopathy?

“…Kleber et al [32] suggested that BIO-VILCAD score including age, sex, left ventricular ejection fraction (EF), heart rate, N-terminal pro-brain natriuretic peptide, cystatin C, renin, 25OH-vitamin D3 and HbA1c, can be helpful in predicting the risk of long-term mortality in diabetics [32]. …”