Development and validation of a nomogram for predicting cerebrospinal fluid leak after endoscopic craniopharyngioma resection

To identify risk factors for cerebrospinal fluid (CSF) leak after extended endoscopic endonasal surgery for craniopharyngiomas and develop a predictive model for predicting postoperative CSF leak.

Six hundred and sixty cases of craniopharyngioma (training cohort: n = 462; validation cohort: n = 198) were retrospectively reviewed between October 2018 and May 2024, and relevant risk factors were identified. A nomogram was built using a stepwise logistic regression method based on the Akaike information criterion. The performance of the nomogram was evaluated using area under the curve (AUC), calibration curve, and decision curve analysis.

The overall rate of postoperative CSF leak was 4.5%. Higher prognostic nutritional index (PNI) level (OR 0.819, 95% confidence interval [CI] 0.735–0.912; p < 0.001) and larger dural defect (OR 6.789, 95% CI 3.112–14.807; p < 0.001) were identified as independent predictors for postoperative CSF leak in multivariable logistic regression analysis. The AUCs of the nomogram were 0.870 (95% CI, 0.782–0.957; p < 0.001) and 0.842 (95% CI, 0.722–0.963; p < 0.001) in the training and validation sets, respectively. Calibration curves in the training and validation cohorts showed satisfactory agreement between predictive and actual outcomes (p = 0.608 and p = 0.564, respectively). Decision curve analysis further confirmed the clinical usefulness of the nomogram.

Higher PNI levels may help reduce the risk of postoperative CSF leak, while a larger dural defect size was demonstrated as an independent risk factor. We developed and validated a nomogram for predicting CSF leak after endoscopic craniopharyngioma resection, which showed strong predictive performance and could assist clinicians in formulating personalized treatment strategies.