  Gender disparities in health outcomes have garnered significant attention,
prompting investigations into their underlying causes. Glioblastoma (GBM), a
devastating and highly aggressive form of brain tumor, serves as a case for
such inquiries. Despite the mounting evidence on gender disparities in GBM
outcomes, investigations specific at the molecular level remain scarce and
often limited by confounding biases in observational studies. In this study, I
aimed to investigate the gender-related differences in GBM outcomes using
propensity score matching (PSM) to control for potential confounding variables.
The data used was accessed from the Cancer Genome Atlas (TCGA), encompassing
factors such as gender, age, molecular characteristics and different glioma
grades. Propensity scores were calculated for each patient using logistic
regression, representing the likelihood of being male based on the baseline
characteristics. Subsequently, patients were matched using the nearest-neighbor
(with a restricted caliper) matching to create a balanced male-female group.
After PSM, 303 male-female pairs were identified, with similar baseline
characteristics in terms of age and molecular features. The analysis revealed a
higher incidence of GBM in males compared to females, after adjusting for
potential confounding factors. This study contributes to the discourse on
gender equity in health, paving the way for targeted interventions and improved
outcomes, and may guide efforts to improve gender-specific treatment strategies
for GBM patients. However, further investigations and prospective studies are
warranted to validate these findings and explore additional factors that might
contribute to the observed gender-based differences in GBM outcomes aside from
the molecular characteristics.
