12 Anatomy as prognosis: are frontal lobe glioblastomas associated with worse outcomes? A single-centre retrospective population-based review

Vollständiger Abstract

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Abstract Introduction Glioblastoma multiforme (GBM) is an aggressive brain malignancy with universally poor outcomes, and multiple covariant prognostic factors. While clinicians have long suspected that GBM’s lobe-location influences surgical and functional outcomes, its independent effect on survival has not been previously established. We aimed to determine whether frontal lobe involvement is associated with reduced overall survival in patients with GBM. Methods A retrospective cohort review of 58 patients diagnosed with GBM between April 2022 and May 2024 was conducted. Affected lobes were identified by analyzing diagnostic imaging reports. A Cox proportional hazard regression model (scripted in Python) was fitted to assess whether frontal lobe involvement was associated with reduced overall survival. Proportional hazards assumptions were met. Essential model outputs included hazard ratios (HRs), 95% confidence intervals (CIs), and Wald statistics. Results Median overall survival was 9.7 months, with 52% patients showing frontal lobe involvement. Fifty-five of fifty-eight patients (95%) died during follow-up, highlighting the lethality of GBM. Frontal lobe involvement was independently associated with increased mortality (HR 1.80, 95% CI 1.01–3.20; z = 2.00; p = 0.05), equating to an 80% higher hazard of death versus non-frontal tumours. Likelihood ratio testing confirmed model significance (χ²=4.17, p≈0.04). Despite modest precision, the effect direction was uniformly adverse. Conclusion Frontal lobe involvement conferred a clinically meaningful survival disadvantage in this GBM cohort. Although limited by sample size (n = 58), the magnitude and consistency of effect suggest tumour location may represent an under-recognised prognostic marker. These findings warrant urgent validation in larger, multi-site cohorts and consideration in surgical planning, risk stratification, and future prognostic modelling.