Equity in Focus : Investigating Gender Disparities in Glioblastoma via Propensity Score Matching
Solomon Eshun

TL;DR
This study uses propensity score matching on TCGA data to investigate gender disparities in glioblastoma outcomes, revealing higher incidence in males after controlling for confounders, and highlights the need for gender-specific treatment strategies.
Contribution
It applies propensity score matching to molecular and demographic data to rigorously analyze gender differences in GBM outcomes, addressing confounding biases in observational studies.
Findings
Higher GBM incidence in males after adjustment
Balanced male-female groups with similar baseline characteristics
Results suggest gender-specific differences in GBM outcomes
Abstract
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…
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Taxonomy
TopicsAdvanced Causal Inference Techniques · Sex and Gender in Healthcare · Gender Politics and Representation
