Development and Validation of a Nomogram for Predicting the Probability of Adjacent Segmental Fractures After Vertebral Augmentation of Osteoporotic Vertebral Compression Fractures

Abstract

Background Adjacent segmental fractures are adverse events after vertebral augmentation of osteoporotic vertebral compression fractures(OVCFs). Predicting the risk of adjacent segmental fractures accurately after surgery is still a significant challenge for spinal surgeons. The aim of our study was to identify predictive factors of the risk of adjacent segmental fractures after vertebral augmentation of OVCFs and develop a nomogram. Methods A nomogram was compiled based on the training cohort of 403 patients, who were hospitalized for OVCFs and performed vertebral augmentation, in the People's Hospital of Ningxia Hui Autonomous Region from June 2014 to December 2016. The independent predictive factors of postoperative adjacent segmental fractures were determined by LASSO, univariate analysis and multivariate logistic regression analysis. Then, establish a nomogram based on these independent predictors. We assessed nomograme using variety methods, including area under the curve (AUC), calibration curve and decision curve analysis (DCA).The above results were verified by the validation cohort of 159 patients, who were hospitalized for OVCFs and performed vertebral augmentation between January 2017 and June 2018. Results The establishment of the nomogram was based on six independent predictors， were determined by multivariate analysis，including age, bone cement injection, bone cement leakage, contact between bone cement and vertebral endplates, bone cement dispersion, and anti-osteoporosis treatment. In the training and validation cohort, the AUC of the nomogram were 0.882 (95% confidence interval, 0.824–0.940) and 0.869 (95% confidence interval: 0.811–0.927),respectively.In the training and validation cohort, the optimal calibration curves demonstrated the coincidence between prediction and actual status, and the decision curve analysis demonstrated that the full model had the highest clinical net benefit across the entire range of threshold probabilities. Conclusion The risk prediction model shows a satisfactory prediction effect and could quantify the probability of adjacent segmental fractures after vertebral augmentation of OVCFs.