Development and Validation of a Predictive Model and Web-Based Calculator for Cage Subsidence After Midline Lumbar Interbody Fusion (MIDLIF) Surgery

Study DesignRetrospective study.ObjectiveTo develop and validate a predictive model for cage subsidence (CS) after midline lumbar interbody fusion (MIDLIF) with cortical bone trajectory (CBT) screws.MethodsThis retrospective two-center study included patients diagnosed with lumbar degenerative disorders undergoing MIDLIF between January 2018 and October 2023 at two independent hospitals under identical eligibility criteria and variable definitions. Patients were stratified into CS and non-CS groups according to postoperative outcomes. Variables with <i>P</i> < 0.1 in the univariate analysis were subsequently included in multivariate logistic regression to determine independent predictors. Bone mineral density (BMD) was indirectly evaluated using endplate bone quality (EBQ) scores from MRI and Hounsfield units (HU) measurements from CT scans. Inter-rater reliability of EBQ was reported using the intraclass correlation coefficient (ICC) with 95% CIs. The model's performance was assessed using ROC analysis, calibration curves, and decision curve analysis (DCA).ResultsAcross both centers, 316 patients were included, of whom 71 (22.5%) developed CS (development center: 48/216, 22.2%; external center: 23/100, 23.0%). Elevated BMI, higher EBQ scores, lower HU values, and reduced preoperative disc height were found to be independent predictors. The prediction model exhibited favorable discriminative ability, with AUCs of 0.924 in the training set and 0.884 in the internal validation set, and it maintained performance in a geographically external cohort (AUC = 0.842). Calibration curves demonstrated good agreement between predicted and observed outcomes, and DCA indicated strong clinical applicability. Although lower than in the training and internal validation sets, external net benefit stayed positive across a broad clinical threshold range and, for most thresholds, exceeded treat-none and treat-all. EBQ inter-rater reliability (ICC, 95% CIs) was 0.960 (0.945-0.971), 0.940 (0.902-0.964), and 0.920 (0.881-0.946) in the training, internal validation, and external cohorts, respectively. In addition, the nomogram was developed into an online calculator that visually displays the predicted probability of CS following MIDLIF.ConclusionsThe developed nomogram serves as a practical and reliable means to predict the risk of cage subsidence in patients undergoing MIDLIF. An online risk calculator based on this model further enhances its clinical utility, providing clinicians with a valuable reference for tailoring surgical strategies and improving perioperative decision-making.