Nomogram for predicting inadequate treatment response in vertebral osteomyelitis.

BACKGROUND

Vertebral osteomyelitis (VO) is frequently complicated by inadequate treatment response (ITR), resulting in prolonged hospitalisation and recurrence. No validated tool currently exists for early ITR risk prediction.

PURPOSE: To develop and internally validate a nomogram for predicting ITR probability in patients with VO.

MATERIALS AND

METHODS

This retrospective study consecutively enrolled 219 patients with vertebral osteomyelitis who were admitted to the Department of Orthopaedics at Shandong Public Health Clinical Centre between January 1, 2021, and December 31, 2024; all data were extracted and analysed in October 2025.ITR was defined as clinical, microbiological, or radiological progression despite ≥4 weeks of appropriate antimicrobial therapy. Predictors were selected using LASSO regression and multivariate logistic regression. Nomogram performance was assessed by AUC, calibration curve, Hosmer-Lemeshow test, decision curve analysis (DCA), and 1000 bootstrap resamples for internal validation.

RESULTS

Fifty-one patients (23.3%) developed ITR within 6 months. Six independent predictors were identified: intraspinal abscess, paraspinal abscess, spinal implant, concomitant pneumonia, low prealbumin, and multiple-site infections. The nomogram yielded excellent discrimination (AUC 0.909, 95% CI 0.862-0.956), confirmed by bootstrap validation (AUC 0.91, 95% CI 0.85-0.95). At the optimal cutoff of 0.308, sensitivity was 76.5%, specificity 91%, Positive Predictive Value (PPV) 70%, and Negative Predictive Value (NPV) 93.2%. Calibration was satisfactory (Hosmer-Lemeshow p = 0.750), and DCA demonstrated clear clinical net benefit.

CONCLUSION

We developed the first validated nomogram for individualised ITR risk prediction in VO, enabling early therapeutic intensification and potentially improving clinical outcomes.