Related Experiment Video
Updated: Jan 7, 2026
Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections
Published on: July 31, 2017
Machine Learning-Enhanced Prognostic Modeling in Elderly Glioblastoma Isocitrate Dehydrogenase-Wildtype: A
Noa Ben Dor1, Filippo Friso2, Gal Ziv3
1Department of Neurosurgery, IRCCS Institute of Neurological Sciences of Bolognat, Bologna, Italy; Department of Biomorphology and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum University of Bolognat, Bologna, Italy.
Background:
Glioblastoma isocitrate dehydrogenase IDH-wildtype (GBM IDHwt) in elderly patients presents challenges due to biological heterogeneity and under-representation in clinical trials. Despite rising incidence, prognostication remains inadequate, with treatment decisions based on subjective criteria.
Objective:
To determine clinical, radiological, surgical, and molecular determinants of survival in elderly GBM IDHwt patients and explore prognostic utility of machine learning (ML) models using clinical and pretreatment data.
Methods:
We analyzed 155 patients aged ≥70 years with confirmed GBM IDHwt who underwent neurosurgery at a tertiary care institution. We examined variables related to clinical presentation, imaging, surgery, and molecular markers using multivariate regression and Histogram Gradient Boosting Regression ML models. Two ML models were developed: one incorporating full dataset variables, and another focusing on preoperative features.
Results:
Median overall survival (OS) was 11.3 months for patients undergoing resection and 3.7 months for biopsy. Independent predictors of prolonged OS included gross total resection (GTR), O6-methylguanine-DNA methyltransferase promoter methylation, nonacute symptom onset, and concomitant radiotherapy with temozolomide (RT + TMZ). ML models confirmed RT + TMZ and GTR as strongest predictors, while Karnofsky Performance Status showed negative importance. Body mass index (BMI) emerged as impactful; and the pretreatment model emphasized BMI and cognitive decline.
Conclusions:
This study confirmed prognostic relevance of GTR, O6-methylguanine-DNA methyltransferase methylation, and RT + TMZ combination. Baseline Karnofsky Performance Status and age did not demonstrate independent prognostic value, while BMI and cognitive decline were potential preoperative predictors. Our findings advocate a multidimensional, data-driven approach to preoperative risk stratification in elderly GBM patients, which may facilitate individualized treatment strategies.
More Related Videos
06:32Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
09:17Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
