# Clinical and genetic determinants of glioblastoma survival: a retrospective study

## TL;DR

This study explores factors affecting survival in glioblastoma patients, emphasizing the importance of tumor location and surgical resection.

## Contribution

The study highlights the critical role of tumor proximity to the ventricular system and resection extent in glioblastoma outcomes.

## Key findings

- Patients with tumors closer to the ventricles had significantly shorter survival.
- Extent of surgical resection was strongly associated with improved survival outcomes.
- IDH1/2-mutant tumors were excluded, aligning with updated WHO classification guidelines.

## Abstract

This study analyzed 57 patients with glioblastoma treated at the General University Hospital of Castellon, Spain, focusing on clinical, tumor-specific and genetic factors influencing disease outcome. Variables included age, sex, BMI, extent of surgical resection, and use of radiotherapy or chemotherapy. Tumor characteristics assessed included location, size, proximity to the ventricular system and surgical approach. Genetic mutations in the EGFR, TP53 and CDKN2A genes were also analyzed.

Kaplan–Meier survival analysis was used to assess the impact of clinical, tumor-related, treatment, lifestyle and genetic variables on overall survival and progression-free survival, with group differences evaluated using log-rank tests. Given the exploratory nature of the study and the sample size, multivariable modeling was not performed. Patients with IDH1/2-mutant tumors were excluded in accordance with the 2021 World Health Organization (WHO) classification, which no longer defines IDH-mutant grade 4 astrocytomas as glioblastoma.

A significant finding was the strong association between extent of resection, tumor proximity to the ventricular system and survival: patients with tumors closer to the ventricles had significantly shorter survival, highlighting the critical role of spatial tumor characteristics in glioblastoma outcomes.

These results suggest that integrating clinical, genetic and spatial tumor data into personalized treatment approaches could improve prognosis.