Related Experiment Videos
Retrospective Development and Internal Validation of a Diagnostic Model to Identify Secondary Osteoporosis in
Yi-You Fang1, Liang Zhang1, Gang Dong1
1Orthopedics Department, Hangzhou Traditional Chinese Medicine Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310007, People's Republic of China.
Objective:
To develop and validate a clinical prediction model integrating lumbar spine bone mineral density (LS-BMD) and fall risk assessment for identifying secondary osteoporosis in community-dwelling elderly men.
Methods:
This retrospective cross-sectional study enrolled men aged 65 years or older from community health centers and geriatric outpatient clinics (June 2023-December 2025). Secondary osteoporosis was defined as T-score ≤ -2.5 at any site (lumbar spine, femoral neck, or total hip) with at least one confirmed major secondary etiology (hypogonadism, glucocorticoid use, vitamin D deficiency, etc). Controls were men with normal BMD or osteopenia without secondary etiology. Participants were randomly assigned to training (70%) and validation (30%) sets. LASSO regression and multivariate logistic regression were used for variable selection and model construction. Bootstrap resampling provided optimism-corrected performance estimates.
Results:
Among 843 eligible participants (mean age 73.12±5.27 years), 187 (22.18%) were diagnosed with secondary osteoporosis. Six independent predictors were identified: age, LS-BMD T-score, history of fall, testosterone, glucocorticoid use, and vitamin D level. The apparent AUC was 0.846 (95% CI: 0.815-0.878) in the training set and 0.798 (95% CI: 0.741-0.854) in the validation set; the optimism-corrected AUC was 0.731, indicating moderate discrimination. Calibration was satisfactory. Decision curve analysis confirmed clinical net benefit. Of note, three predictors (testosterone, vitamin D, glucocorticoid use) overlap with the diagnostic criteria for secondary osteoporosis, and the AUC values should be interpreted with this caveat in mind.
Conclusion:
This study developed a preliminary clinical prediction model for identifying secondary osteoporosis in elderly men using internal validation. The model integrates LS-BMD T-score, fall risk, Vitamin D, testosterone, and glucocorticoid use, but external validation is required before clinical application. The overlap between several predictors and the diagnostic criteria represents an important limitation.
