Modeling and construction of nomogram of cage subsidence after single-segment transforaminal lumbar interbody fusions.

Authors

Jinxiang Zhan, Qipeng Wei, Weijun Guo, Zihao Liu, Shiji Chen, Qingyan Huang, Dongling Cai

Published in

Journal of orthopaedic surgery and research. Volume 20. Issue 1. Pages 399. Apr 21, 2025. Epub Apr 21, 2025.

Abstract

The purpose of this study is to explore and analyze the risk factors for interbody cage subsidence in patients undergoing single-segment transforaminal lumbar interbody fusion (TLIF) and to construct and validate a visual nomogram risk prediction model.
A retrospective analysis was conducted on the clinical data of 159 patients who underwent single-segment TLIF at the Spine Surgery Department of Panyu District Traditional Chinese Medicine Hospital from January 2021 to June 2023. Using the caret package in R, patients were randomly divided into a training set (n = 111) and a validation set (n = 48) in a 7:3 ratio. Multivariable logistic regression was employed for variable selection and the construction of the nomogram model. The predictive model's discrimination, calibration, and clinical utility were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
There were no statistically significant differences in various indicators between the training set (n = 111) and the validation set (n = 48) (P > 0.05). Univariate analysis in the training set revealed that age, bone density, endplate morphology, anterior vertebral bone spurs, lumbar CT values, and VBQ were statistically significant. Multivariable logistic regression analysis indicated that bone density, anterior vertebral bone spurs, and lumbar CT values were independent predictors of interbody cage subsidence (P < 0.05), and a nomogram model was constructed based on these indicators. The area under the ROC curve (AUC) for the training set and validation set was 0.93 (95% CI 0.89-0.98) and 0.93 (95% CI 0.86-1.00), respectively. The calibration curves showed good fit (training set P = 0.616; validation set P = 0.904). DCA analysis demonstrated that the model has high clinical utility.
Bone density, anterior vertebral bone spurs, and lumbar CT values are risk factors for interbody cage subsidence in patients after single-segment transforaminal lumbar interbody fusion. The constructed nomogram model exhibits good predictive value and clinical utility.

PMID:
40259298
Bibliographic data and abstract were imported from PubMed on 22 Apr 2025.

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