Predictive model for preoperative risk calculation of cerebrospinal fluid leak after resection of midline craniofacial mass lesions

Background: Complex anterior skull base defects produced by resection of mass lesions vary in size and configuration and may be extensive. We analyzed the largest single-center series of midline craniofacial lesions extending intra- and extracranially. The study aims at the development of a predictive model for preoperative measurement of the risk of the postoperative cerebrospinal fluid (CSF) leak based on patients' characteristics and surgical plans. Methods: 166 male and 149 female patients with mean age 40,5 years (1 year and – 81 years) operated for benign and tumor-like midline craniofacial mass lesions were retrospectively analyzed using logistic regression method (Ridge regression algorithm was selected). The overall CSF leak rate was 9.6%. The ROSE algorithm and ‘glmnet’ software suite in R were used to overcome the cohort's disbalance and avoid overtraining the model. Results: The most influential modifiable negative predictor of the postoperative CSF leak was the use of extracranial and combined approaches. Use of transbasal approaches, gross total resection, utilization of one or two vascularized flaps for skull base reconstruction were the foremost modifiable predictors of a good outcome. Criterium of elevated risk was established at 50% with a specificity of the model as high as 0.83. Conclusions: The performed study has allowed for identifying the most significant predictors of postoperative CSF leak and developing an effective formula to estimate the risk of this complication using data known for each patient. We believe that the suggested web-based online calculator can be helpful for decision making support in off-pattern clinical situations.