PURPOSE

This study aimed to develop and validate a new model that focused on the risk of imminent vertebral fractures in women with osteoporosis.

METHODS

Data from 2,048 patients were extracted from three hospitals, of which 1,720 patients passed the inclusion and exclusion screen. The patients from Nanfang Hospital (NFH) were randomized at a 2:1 ratio to create a training cohort (n = 709) and an internal validation cohort (n = 355), with the patients from the other two hospitals (n = 656) used for external validation. The risk factors included in the imminent osteoporotic vertebral compression fractures (OVCFs) prediction model (labelled TVF) were sorted by the least absolute shrinkage and selection operator and constructed by logistic regression. The area under the receiver operating characteristic curve (AUC), the decision curve, and the clinical impact curves of the optimal model were analyzed to verify the model.

RESULTS

There were 138 and 161 fresh fractures in NFH and the other two hospitals, respectively. The lowest BMD T value and the history of vertebral fracture were integrated into the TVF model. The prediction power of TVF was demonstrated by the AUCs of 0.788 (95% confidence interval [CI], 0.728-0.849) in the training cohort and 0.774 (95% CI, 0.705-0.842) in the internal validation cohort, and 0.790 (95% CI, 0.742-0.839) and 0.741 (95% CI, 0.668-0.813) in the external validation cohorts.

CONCLUSION

The TVF model demonstrated good discrimination to stratify the imminent risk of OVCFs. We therefore consider the model as a pertinent commencement in the search for more accurate imminent OVCFs prediction.