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A nomogram for predicting adjacent segment disease after anterior cervical surgery.
Burak Bahadir1, Fatma Betül Saylak2
1Department of Neurosurgery, Ankara Bilkent City Hospital, Ankara, Turkey.
Medicine
|July 11, 2026
Summary
A new nomogram predicts adjacent segment disease (ASD) after anterior cervical surgery. It uses factors like age and disc height to identify patients at higher risk, aiding in personalized treatment strategies.
Area of Science:
- Spine surgery outcomes
- Clinical prediction modeling
- Radiological assessment
Background:
- Adjacent segment disease (ASD) is a known complication of anterior cervical surgery, impacting long-term results.
- Predicting ASD risk is crucial for optimizing patient management and surgical planning.
Purpose of the Study:
- To develop and validate a prognostic nomogram for predicting ASD risk after anterior cervical surgery.
- To identify key clinical and radiological predictors of ASD development.
Main Methods:
- Retrospective cohort study of 234 patients undergoing anterior cervical surgery.
- LASSO regression for variable selection, followed by multivariable logistic regression.
- Nomogram construction and internal validation using AUROC, calibration, and decision curve analysis.
Main Results:
- ASD developed in 11.1% of patients.
- Key predictors identified: age, cage use, mJOA score, disc height, and Cobb angle.
- Cage use, increased disc height, and Cobb angle were independently associated with higher ASD risk (AUROC = 0.78).
Conclusions:
- The developed nomogram effectively predicts individualized ASD risk post-anterior cervical surgery.
- This tool can assist clinicians in identifying high-risk individuals and tailoring postoperative care.
- Integrating clinical and radiological data enhances risk stratification for ASD.