Development and validation of a novel glucolipid metabolism-related nomogram to enhance the predictive performance for osteoporosis complications in prediabetic and diabetic patients.

Background: Diabetes is the most prevalent metabolic disorder worldwide, imposing a significant economic burden on society. Prediabetes has not received as much attention as diabetes, and among its complications, osteoporosis has been relatively under-researched compared to cardiovascular disease. Recent studies have identified nine indices related to glucose and lipid metabolism that may enhance osteoporosis risk assessment in diabetic and prediabetic individuals. The research examined the osteoporosis risk prediction potential of these indices and developed a nomogram to enhance predictive performance.

Methods: 2,735 prediabetic and diabetic subjects were derived from National Health and Nutrition Examination Survey (NHANES) dataset collected between 2011 and 2020, then randomly assigned to development and validation cohorts in 7:3. The predictive capacity of glucolipid metabolism-related indices for osteoporosis risk was evaluated using receiver operating characteristic (ROC) curve analysis. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to identify predictors for constructing the risk model, which was visualized using a nomogram. The model's performance was further validated.

Results: All the glucolipid metabolism-related indices showed predictive ability, and the best-performing index was metabolic score for insulin resistance (METS-IR). Multivariate logistic regression identified 5 predictors [Triglyceride-glucose index (TyG), age, METS-IR, TyG-waist circumference, and TyG-body mass index] with good predictive performance. These predictors were selected to establish the nomogram. ROC curve, calibration plot, as well as decision curve analysis (DCA) collectively demonstrated fairly good predictive ability of the nomogram.

Conclusions: Glucolipid metabolism-related indices are the predictors of osteoporosis risk. This newly developed nomogram based on glucolipid metabolism indices demonstrates optimal predictive accuracy for assessing combined osteoporosis risk in individuals with prediabetes and diabetes.