Prognostic Value of a Nomogram Model Based on Tumor Immune Markers and Clinical Factors for Adult Primary Gliomas

Objective: This study aimed to analyze the factors associated with overall survival (OS) in adult patients with primary gliomas, develop a nomogram prediction model, and optimize its predictive performance. Methods: Clinical data were retrospectively collected from adult patients newly diagnosed with gliomas who underwent surgical treatment at the Department of Neurosurgery, Fourth Hospital of Hebei Medical University, between January 2019 and December 2023. External validation was performed using data from the Chinese Glioma Genome Atlas (CGGA) database. Data analysis and visualization were performed using Statistical Package for the Social Sciences (SPSS) 26.0 and R software (Version 4.4.1). Results: A total of 257 adult patients were included in this study. Multivariate Cox regression analysis revealed that age, Karnofsky Performance Status score, tumor diameter, World Health Organization grade, postoperative radiotherapy and chemotherapy, and the expression of tumor immune markers (ATRX, IDH1, and Ki-67) were all associated with patient prognosis. Factors with P < 0.05 in the multivariate analysis and those included in the CGGA external database were used to construct a nomogram for predicting 1-, 2-, and 3-year survival rates. Multiple validations demonstrated that the model exhibited excellent generalizability and clinical applicability. Conclusion: The nomogram model constructed based on clinical factors, tumor immune markers, and other parameters exhibited strong predictive efficacy and may serve as an effective alternative to molecular testing.