Factors associated with longer survival among older medicare patients after diagnosis of supratentorial primary brain malignancies: a retrospective cohort study.

OBJECTIVES: Despite recent advances, the prognosis for primary malignant brain tumors (PMBTs) remains poor. Some commonly prescribed medications may exhibit anti-tumor properties in various cancers, and neurodegenerative diseases may activate pathways that counteract gliomagenesis. Our study is focused on determining if there is a correlation between the use of metformin, beta-blockers, angiotensin converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs), or the presence of Parkinson's disease (PD), and the survival rates following a diagnosis of a PMBT. METHODS: This analysis of the 100% Texas Medicare Database identified patients aged 66+ years diagnosed with a supratentorial PMBT from 2014-2017. Cox proportional hazards regression was employed to analyze survival following diagnosis and associations of survival with surgical intervention, radiation, PD diagnosis, and prescription of metformin, beta-blockers, ACEIs, or ARBs. RESULTS: There were 1,943 patients who met study criteria, and the median age was 74 years. When medication utilization was stratified by none, pre-diagnosis only, post-diagnosis only, or both pre- and post-diagnosis (continuous), continuous utilization of metformin, beta-blockers, ACEIs, or ARBs was associated with prolonged survival compared to no utilization (hazard ratio [HR]:0.45, 95% CI:0.33-0.62; HR:0.71. 95% CI:0.59-0.86; HR:0.59, 95% CI:0.48-0.72; and HR:0.45, 95% CI:0.35-0.58 respectively). PD was also associated with longer survival (HR:0.59-0.63 across the four models). DISCUSSION: Our study suggests that metformin, beta-blockers, ACEIs, ARBs, and comorbid PD are associated with a survival benefit among geriatric Medicare patients with supratentorial PMBTs.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities.

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.