Development and Validation of a Nomogram for Predicting Low Bone Mineral Density in Male Patients with Ankylosing Spondylitis

Xiaotong Yang¹Qin Cheng²Yifan Li¹Hao Tang^1,3Xin Chen¹Lijun Ma¹Jing Gao¹Wei Ji^4*

• ¹Nanjing University of Chinese Medicine, Nanjing, China
• ²Nanjing Jiangning District Chinese Medicine Hospital, Nanjing, Jiangsu Province, China
• ³Liyang City Hospital of Traditional Chinese Medicine, Liyang, China
• ⁴Jiangsu Provincial Hospital of Traditional Chinese Medicine, Nanjing, Jiangsu Province, China

Objective: This retrospective cohort study aimed to develop and validate clinical nomogram models for predicting site-specific low bone mineral density (BMD) risk in male patients with ankylosing spondylitis (AS). Methods: This study enrolled male AS patients treated at the Rheumatology Department of Jiangsu Provincial Hospital of Traditional Chinese Medicine between January 2017 and September 2024. A total of 322 eligible patients were randomly allocated to training and validation cohorts at a 7:3 ratio. Predictors of low BMD at lumbar spine (LS) and left hip (LH) were screened through univariate and multivariate logistic regression. Nomograms and an online tool were developed and evaluated for discrimination, calibration, and clinical utility. Results: This study included 322 male AS patients randomly allocated to training (n=225) and validation (n=97) cohorts with balanced baseline characteristics (all P>0.05). Multivariate logistic regression identified age at onset, BMI, serum uric acid , and hip involvement as common independent predictors for low BMD at both sites, while serum calcium (OR=12.19, 95%CI:1.44-103.25) was specific to LS. The developed nomograms, including web-based versions, demonstrated good discrimination (LS AUC:0.77 training/0.73 validation; LH AUC:0.82/0.85) and calibration. Decision curve analysis revealed significant net clinical benefit across probability thresholds (LS:0.17-0.86 training/0.20-0.82 validation; LH:0.15-0.92/0.27-0.91). The protective effect of BMI exhibited site-specific patterns: LS (low-TC: OR=0.86; high-TC: OR=0.77), LH (low-TC: OR=0.77; mid-TC: OR=0.74), with the most pronounced effect observed in the LS low-TG subgroup (OR=0.79). SUA demonstrated consistent protective effects (LS/LH: OR=0.95-0.99, all P<0.05), potentially independent of disease stage.Interaction analyses revealed that neither lipid levels nor disease stage significantly modified the effects of BMI and SUA (all interaction P>0.4).Conclusion: This study developed clinical prediction models with excellent discriminative ability and substantial clinical utility for male patients with AS. These models offer rheumatologists an efficient tool to rapidly assess individual risks of low BMD, facilitating early diagnostic decision-making and enabling personalized interventions tailored to anatomical site-specific osteoporosis risks.