MATERIAL and METHODS: Data from 185 patients diagnosed with high-grade gliomas, who underwent surgical treatment between March 2013 and December 2022, were retrospectively analysed. Patients were randomly divided into training and validation cohorts. The nomogram was developed using multivariate Cox regression analysis according to selected risk factors using least absolute shrinkage and selection operator (i.e., ?LASSO?) regression. The area under the receiver operating characteristic curve, calibration curve, and C-index were used to assess the performance of the prediction model.

RESULTS: This study included data from 185 patients; six independent risk factors were identified and used to generate a prognostic nomogram: WHO grade, body mass index (BMI), smoking, platelet (PLT) count, fibrinogen (FIB) level, and AGR. The nomogram demonstrated considerable prognostic consistency and discrimination. The prognostic utility of AGR was identified in patients with glioma [hazard ratio 0.7876 (95% confidence interval 0.6471?0.9585); p=0.0172].

CONCLUSION: AGR was found to be a potential risk factor for predicting overall survival in patients with glioma after surgery. The nomogram integrated WHO grade, BMI, smoking status, PLT count, and FIB level. AGR provided clinical guidance for surgeons to predict survival rates in patients with glioma. Keywords : AGR, Glioma, Nomogram, Overall survival