Related Experiment Video
Updated: May 31, 2025
A Rapid Screening Workflow to Identify Potential Combination Therapy for GBM using Patient-Derived Glioma Stem Cells
Published on: March 28, 2021
Multi-center real-world data-driven web calculator for predicting outcomes in IDH-mutant gliomas: Integrating
Houshi Xu1,2,3, Beining Liu4,1,2, Yue Wang1,2,3
1Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
Background:
Isocitrate dehydrogenase (IDH)-mutant gliomas generally have a better prognosis than IDH-wild-type glioblastomas, and the extent of resection significantly impacts prognosis. However, there is a lack of integrated tools for predicting outcomes based on molecular subtypes and treatment modalities. This study aimed to identify factors influencing gross total resection (GTR) rates and to develop a clinical prognostic tool for IDH-mutant gliomas.
Methods:
We analyzed 650 patients with IDH-mutant gliomas from 3 Chinese medical centers (Shanghai, Hong Kong, and Zhengzhou). Data included age, sex, extent of resection, radiotherapy status, tumor grade, histology, and molecular markers (1p19q, TERT promoter, BRAF, EGFR, 10q). Patients were categorized based on GTR status, and a nomogram predicting 3-, 5-, and 10-year overall survival (OS) was developed using Cox proportional hazards regression and validated with time-dependent ROC and calibration plot analyses.
Results:
Non-GTR was associated with diffuse astrocytoma (73.0% vs. 53.5%), 1p19q non-codeletion (67.9% vs. 48.7%), and wildtype TERT promoter (63.6% vs. 52.4%). The nomogram, incorporating age, TERT promoter status, extent of resection, grade, and radiotherapy status, demonstrated strong discriminatory ability (AUC > 0.75) and good calibration. Decision curve analysis indicated that it outperformed WHO grade-based classification in identifying high-risk patients. An online calculator was developed for clinical use (http://www.szflab.site/nomogram/).
Conclusion:
We developed and validated a nomogram and online tool that integrates molecular and clinical factors for predicting outcomes in IDH-mutant gliomas, enhancing clinical decision-making.
