Nomogram for prediction of recurrence in patients with lumbar disc herniation after unilateral biportal endoscopy spinal surgery: a retrospective study - Rong, Yi; Wang, Kaixuan; Pan, Yalan; Zhang, Tianchi; Ma, Yong; Wang, Lining; Guo, Yang; Chen, Si; Shao, Yang; Zhu, Tingchen; Wu, Shixiang; Hua, Zhen; et al. (Frontiers in Surgery, 2025)
ObjectiveThis study aimed to construct a nomogram to predict the likelihood of early recurrence in patients with lumbar disc herniation (LDH) following unilateral biportal endoscopic (UBE) surgery.MethodsA retrospective analysis was conducted on LDH patients who underwent UBE surgery in our department between January 1, 2022, and December 31, 2023. The eligible cohort was randomly divided into training and validation sets in a 7:3 ratio. Key predictors for the nomogram were identified through a combination of least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis. The model's performance was assessed using the C-index, the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. The validation set was used to further evaluate the model's robustness.ResultsA total of 289 patients were included in the study, among whom 50 experienced recurrent LDH (rLDH). Five risk factors were identified as significant predictors for rLDH: width of protrusion base (WPB), bone removal range (BRR), Modic changes, type of LDH, and middle vertebral space height (MVH). The C-index values for the training and validation sets were 0.834 and 0.804, respectively. The AUC values were 0.834 (95% CI: 0.750–0.918) in the training set and 0.804 (95% CI: 0.697–0.910) in the validation set. Calibration curves demonstrated excellent concordance between the predicted and observed outcomes. Decision curve analysis indicated that using the nomogram to predict rLDH risk provided a positive net benefit when the threshold probability was between 4% and 63%.ConclusionThis study successfully developed and validated a nomogram to predict early recurrence in LDH patients following UBE surgery. The model provides a valuable tool for clinicians to assess individual rLDH risk, enabling timely interventions to improve postoperative outcomes.