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Risk Factor Analysis and Risk Prediction Model Construction of Ossification Progression After Postoperative Cervical
Changlin Lv1, Jianyi Li1, Jianwei Guo1
1The Affiliated Hospital of Qingdao University, Shandong Province, China.
Study Design:
Retrospective analysis.
Objective:
To develop a nomogram to predict the progression of ossification of the posterior longitudinal ligament (OPLL) after surgery, identify potential risk factors, and provide a theoretical basis for preventing postoperative ossification progression.
Summary Of Background Data:
OPLL is a degenerative condition prevalent in Asian populations, leading to spinal cord and nerve root compression. While surgery is the primary treatment, postoperative ossification progression, particularly after posterior surgeries, remains a challenge, potentially requiring reoperation. Current methods for predicting risk factors rely on clinical experience, highlighting the need for a multidimensional prediction model to identify at-risk patients and improve outcomes.
Materials And Methods:
This retrospective study analyzed 271 patients who underwent posterior cervical spine surgery for OPLL. Univariate and multivariate logistic regression were used to identify independent risk factors for postoperative ossification progression. A nomogram was constructed based on these factors. The model's performance was evaluated using the C-index, ROC curve, calibration curve, and decision curve analysis (DCA), with validation conducted using data from a separate group.
Results:
Multivariate logistic regression analysis identified four independent risk factors for ossification progression after OPLL. A nomogram was subsequently constructed based on these factors. The C-index values in both the training and validation groups demonstrated high accuracy and stability of the model. The area under the ROC curve (AUC) indicated excellent discriminative ability, while the calibration curves showed high agreement between predicted and observed outcomes in both groups. The decision curve analysis demonstrated that the nomogram provided the highest net clinical benefit within a probability threshold range 0.01 to 1.
Conclusion:
Younger patients with OPLL, greater initial ossification thickness, more than three affected levels, or continuous/mixed ossification types are at higher risk of postoperative progression. The nomogram provides clinicians with an effective tool to predict and prevent postoperative ossification progression.
