JMIR Publications

ABSTRACT

Background:

Serum levels of silent information regulator 6 (SIRT6), a key biomarker of aging, were identified as a predictor of coronary artery disease (CAD), but whether SIRT6 can distinguish severity of coronary artery lesions in elderly patients is unknown.

Objective:

This study developed a nomogram to demonstrate the functionality of SIRT6 in assessing severity of coronary artery atherosclerosis.

Methods:

Patients aged ≥60 with angina pectoris were screened for this single-center clinical study between Oct 1, 2022, and Mar 31, 2023. Serum specimens of eligible patients were collected for SIRT6 detection by enzyme-linked immunosorbent assay. Clinical data and putative predictors, including 29 physiological characteristics, biochemical parameters, carotid artery ultrasound results, and complete coronary angiography findings, were evaluated, with CAD diagnosis as the primary outcome. The nomogram was derived from the XGBoost model, with logistic regression for variable selection. Model performance was assessed by examining discrimination, calibration, and clinical utility. Internal validation of models was conducted using bootstrapping on a validation cohort.

Results:

Eligible patients (n=222) were divided into two cohorts: the development cohort (n=178) and the validation cohort (n=44). Serum SIRT6 levels were identified as both an independent risk factor and a predictor for CAD in elderly individuals. The area under the receiver operating characteristic curve (AUC) was 0.725 (95% confidence interval [95%CI]: 0.653–0.797). The optimal cut-off value of SIRT6 for predicting CAD was 546.384 pg/mL. Predictors included in this nomogram were serum SIRT6 levels, triglyceride glucose (TyG) index, and apolipoprotein B. The AUC of the model in the development cohort was 0.978 (95%CI: 0.96–0.996). Similar values were achieved in internal validation (AUC: 0.906; 95%CI: [0.82–0.995]). All models demonstrated satisfactory calibration, with predictions closely aligning with outcomes.

Conclusions:

SIRT6 shows promise in predicting CAD, with enhanced predictive abilities when combined with the TyG index. In clinical settings, monitoring fluctuations in SIRT6 and TyG may offer valuable insights for early CAD detection. The nomogram for CAD outcome prediction in elderly patients with angina pectoris may aid in clinical trial design and personalized clinical decision-making, particularly in institutions where SIRT6 is being explored as a biomarker for aging or cardiovascular health. Clinical Trial: N/A