To investigate the correlation between blood biomarkers and blood glucose fluctuations with the risk of osteoporosis (OP) in postmenopausal women with type 2 diabetes mellitus (T2DM), and to construct a predictive nomogram for OP. Based on bone mineral density (BMD) results from dual-energy X-ray absorptiometry (DXA), participants were divided into OP (BMD T-value ≤ -2.5 SD) and Non-OP (BMD T-value > -2.5 SD) groups. Logistic analysis were used to explore the potential risk factors, following by the construction of a nomogram to predict the risk of OP. The discrimination and calibration of the nomogram were evaluated using concordance index (C-index), area under curve (AUC), and calibration curves. We finally included 381 participants, with 147 in the OP group. Correlation analysis revealed a significant positive correlation between age and SII, and a negative correlation between BMI and CV. SII and CV demonstrated a positive dose-response relationship with OP, while FT3 exhibited a negative relationship. Multivariate logistic analysis showed that age (OR=1.088, 95% CI 1.052-1.125, P<0.001), BMI (OR=0.772, 95% CI 0.702-0.848, P<0.001), SII (OR=1.004, 95% CI 1.003-1.005, P<0.001), FT3 (OR=0.529, 95% CI 0.280-0.998, P=0.049), and CV (OR=1.051, 95% CI 1.007-1.097, P=0.022) were independent risk factors. The subgroup analysis showed the correlation between SII and OP occurred primarily in individuals aged ≥60 years. A predictive nomogram model was constructed based on age, BMI, SII, FT3, and CV, with a C-index of 0.842 (range 0.801-0.883). Decision Curve Analysis (DCA) demonstrated good clinical fit of the model. SII can predict the OP occurrence in women aged ≥60 years, while FT3 is applicable for predicting OP in women aged ≥70 years and those with a BMI <24 kg/m². The predictive nomogram demonstrated great predictive value in postmenopausal women with T2DM.
Wang et al. (Mon,) studied this question.