New model strongly predicts CV death in patients with stable CHD
The novel “ABC-CHD” model appears to be a robust tool for predicting cardiovascular (CV) death in patients with stable coronary heart disease (CHD), reports a new study.
Furthermore, the model is based on a small number of readily available biomarkers and clinical factors; thus, it can be widely used to complement clinical assessment and guide management based on CV risk.
Researchers analysed a number of candidate biomarkers and clinical variables in a prospective, randomized trial cohort of 13,164 patients with stable CHD, and used multivariable Cox regression to develop a clinical prediction model based on the most important markers.
CV death was the primary outcome, but model performance was also explored for other key outcomes. The model was internally bootstrap validated, and it was externally authenticated in 1,547 patients in another study.
A total of 591 cases of CV death were recorded during a median follow-up of 3.7 years. N-terminal pro–B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT) and low-density lipoprotein cholesterol were the three most important biomarkers. In addition, NT-proBNP and hs-cTnT showed greater prognostic value compared with any other biomarker or clinical variable.
Age (A), biomarkers (B; NT-proBNP, hs-cTnT and low-density lipoprotein cholesterol) and clinical variables (C; smoking, diabetes mellitus and peripheral arterial disease) were included in the final prediction model.
“This ‘ABC-CHD’ model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort; 0.78 in validation cohort), with adequate calibration in both cohorts,” according to researchers.