Wang Jing-Jing, Hu Jie, Xu Yi-Fan, Dai Wu, Wu Jun-Cang, Cao Yong-Hong
Department of Endocrinology, Hefei Hospital Affiliated to Anhui Medical University (The Second People's Hospital of Hefei), Hefei, Anhui, 230011, People's Republic of China.
The Fifth Clinical School of Medicine, Anhui Medical University, Hefei, Anhui, 230032, People's Republic of China.
Diabetes Metab Syndr Obes. 2025 Sep 9;18:3363-3373. doi: 10.2147/DMSO.S524654. eCollection 2025.
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.
探讨2型糖尿病（T2DM）绝经后女性血液生物标志物及血糖波动与骨质疏松症（OP）风险之间的相关性，并构建OP预测列线图。
根据双能X线吸收法（DXA）测量的骨密度（BMD）结果，将参与者分为OP组（BMD T值≤-2.5 SD）和非OP组（BMD T值>-2.5 SD）。采用逻辑回归分析探索潜在危险因素，随后构建预测OP风险的列线图。使用一致性指数（C指数）、曲线下面积（AUC）和校准曲线评估列线图的辨别力和校准度。
最终纳入381名参与者，其中OP组147名。相关性分析显示年龄与系统性免疫炎症指数（SII）呈显著正相关，体重指数（BMI）与血糖变异系数（CV）呈负相关。SII和CV与OP呈正剂量反应关系，而游离三碘甲状腺原氨酸（FT3）呈负相关。多因素逻辑回归分析显示，年龄（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）和CV（OR=1.051，95%CI 1.007-1.097，P=0.022）是独立危险因素。亚组分析显示SII与OP的相关性主要发生在年龄≥60岁的个体中。基于年龄、BMI、SII、FT3和CV构建了预测列线图模型，C指数为0.842（范围0.801-0.883）。决策曲线分析（DCA）表明该模型具有良好的临床拟合度。
SII可预测年龄≥60岁女性的OP发生情况，而FT3适用于预测年龄≥70岁及BMI<24 kg/m²女性的OP。该预测列线图在T2DM绝经后女性中显示出较大的预测价值。
