Abstract
To construct a nomogram risk prediction model for osteoporotic vertebral compression fracture (OVCF) in postmenopausal osteoporosis (POP). A retrospective study was conducted on 326 POP patients from July 2023 to November 2024. The patients were randomly included into a training cohort of 228 cases and a validation cohort of 98 cases based on a 7:3 ratio; The training queue was assigned into a fracture group of 82 cases and a non fracture group of 146 cases. Risk factors were screened based on multiple logistic regression analysis. R software was used to construct nomogram prediction models. ROC curve, calibration curve, and clinical decision curve were performed to evaluate model discrimination, calibration, and practicality. For the non fracture group, the fracture group showed manifest increases in age, physical exercise time < 1 h/d, gastrointestinal diseases, uric acid, and type I collagen carboxy terminal peptide (β-CTX), and manifest decreases in bone mineral density (BMD) (T value), hemoglobin (Hb), and 5-hydroxyvitamin D [25-(OH)D] (P < 0.05). Increase in age, decrease in BMD (T value), physical exercise time < 1 h/d, presence of gastrointestinal diseases, increase in uric acid, increase in β-CTX, and decrease in 25-(OH)D were independent risk factors for OVCF in POP (P < 0.05). The calibration curves of the training queue and validation queue indicated a high degree of agreement between the predicted results of the model and the actual results, Hosmer-Lemeshow χ2 = 5.155, 4.490, P = 0.631, 0.810. The AUC of ROC curve was 0.974 and 0.909. In the decision curve analysis, the model demonstrated a net clinical benefit across threshold probability ranges of 0.05–0.97 in the training cohort and 0.02–0.99 in the validation cohort. The established nomogram prediction model can be used to reasonably evaluate the risk of OVCF in POP patients.
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The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.
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Funding
This study were supported by the Big Data Platform of Affiliated Hospital of Guangdong Medical University and 2024 Guangdong Medical University Clinical+Basic Technology Innovation Special Plan（GDMULCJC2024030）,the 2025 Zhanjiang City Science and Technology Development Special Fund Competitive Allocation Project (Grant No. 2025B01347) and the Graduate Education Innovation Program of Guangdong Provincial Department of Education (2024JGXM_081).
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Jv Chen and Bo Wei：Project development, Data Collection, Data analysis, Manuscript writing.Jie Cai: Data collection. Hao Lin and Chengshuo Huang: Project development, Data collection, Data analysis, Manuscript editing.
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The study was in accordance with Affiliated Hospital Of Guangdong Medical University Ethics Review Board(No.PJKT2025-005)and with the 1964 Helsinki Declaration. As this was a retrospective study using anonymized clinical data, the requirement for written informed consent was waived by the Ethics Review Board.
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Chen, J., Wei, B., Cai, J. et al. Construction of a nomogram prediction model for individualized prediction of vertebral compression fracture risk in postmenopausal osteoporosis population. Sci Rep (2026). https://doi.org/10.1038/s41598-026-40375-z
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DOI: https://doi.org/10.1038/s41598-026-40375-z
