TyG, AIP, and ABSI were independently associated with PCAD and provided modest incremental discrimination beyond conventional risk factors in this predominantly statin-treated case-control cohort, with dynamic nomograms developed that require external validation.
Key Findings
Methods
The study analyzed 3063 adults undergoing coronary angiography from the Iran Premature Coronary Artery Disease registry, comparing patients with PCAD to controls.
The sample comprised 1929 patients with PCAD and 1134 controls.
The design was a multicenter retrospective case-control study.
Twelve metabolic, lipid-based, and anthropometric indices were calculated from fasting glucose, lipid profiles, and body measurements.
Participants were randomly split into training and validation cohorts at a 7:3 ratio.
Results
The atherogenic index of plasma (AIP), triglyceride-glucose index (TyG), and a body shape index (ABSI) showed consistent independent associations with PCAD.
Associations were evaluated using logistic regression.
The abstract describes these three indices as showing consistent independent associations among the twelve evaluated.
Results
Individually, the indices showed only modest discrimination for PCAD.
Discrimination was assessed with receiver operating characteristic analysis.
The abstract states that conventional lipid markers may have limited discriminative value, particularly when lipid levels reflect ongoing statin therapy.
Results
The conventional clinical model achieved an AUC of 0.677 for PCAD discrimination.
This model served as the baseline against which the models with added indices were compared.
Results
Adding AIP and binary ABSI to the conventional model raised the AUC to 0.721.
This was described as a modest but statistically significant improvement over the conventional model.
Results
The TyG plus binary ABSI model showed the highest performance, with an AUC of 0.724.
This was a modest but statistically significant improvement over the conventional model (AUC 0.677).
Results
Both final models showed favorable internal calibration and improved reclassification and decision-curve net benefit.
Evaluation used calibration assessment, integrated discrimination improvement, net reclassification improvement, and decision-curve analysis.
Validation was internal (training/validation split).
Conclusions
Two dynamic web-based nomograms were developed for individualized PCAD case discrimination.
The nomograms correspond to the two final models (AIP + binary ABSI and TyG + binary ABSI added to conventional factors).
The authors state clinical applicability and absolute risk estimation require external validation in independent, preferably prospective, populations.
Discussion
The cohort was predominantly statin-treated, which may limit the value of conventional lipid markers, and the retrospective case-control design limits estimation of absolute risk.
The authors note that conventional lipid markers may have limited discriminative value when levels reflect ongoing statin therapy.
They caution that the nomograms are for case discrimination rather than absolute risk prediction.
What This Means
This study looked at whether simple measures calculated from routine blood tests and body measurements could help identify younger adults with premature coronary artery disease (blocked heart arteries at a young age). Researchers used data from 3063 people who had coronary angiography in Iran: 1929 with premature coronary disease and 1134 without. Most participants were taking statins, which can make standard cholesterol readings less informative.
Three measures were consistently linked to premature coronary disease: the atherogenic index of plasma (based on blood fats), the triglyceride-glucose index (based on blood triglycerides and sugar), and a body shape index (which accounts for waist size relative to height and weight). On their own they were only modestly useful at telling patients from non-patients. Adding them to conventional risk factors improved discrimination somewhat, from an AUC of 0.677 to about 0.72 (where 0.5 is chance and 1.0 is perfect). The researchers also built two online calculators (nomograms) based on these models.
This research suggests these indices may add a small amount of information beyond traditional risk factors, but the improvement was modest. Because the study compared existing cases to controls and was tested only internally, the tools cannot yet estimate an individual's actual future risk. The authors say they need testing in independent, preferably prospective, groups before clinical use.
Mirzohreh S, Ghaffari S, Javanshir E, Dehghan M, Tarighat F, Mohammadifard N, et al.. (2026). Metabolic, Atherogenic, and Anthropometric Markers for Discrimination of Premature Coronary Artery Disease in a Predominantly Statin-Treated Cohort.. Vascular health and risk management. https://doi.org/10.2147/VHRM.S630288