Hervey-Jumper, Shawn L

Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factors remains limited. To test the interactive effects of demographic, socioeconomic, and oncologic variables on trial enrollment, we designed boosted neural networks (BNNs) for all glioma patients ( n = 1042), women ( n = 445, 42.7%), and minorities ( n = 151, 14.5%) and externally validated these models [whole cohort, n = 230; women, n = 89 (38.7%); minority, n = 66 (28.7%)]. For the whole-cohort BNN, the most influential variables on enrollment were oncologic variables, including KPS [total effect (TE), 0.327], chemotherapy (TE, 0.326), tumor location (TE, 0.322), and seizures (TE, 0.239). The women-only BNN exhibited a similar trend. Conversely, for the minority-only BNN, socioeconomic variables [insurance status (TE, 0.213), occupation classification (TE, 0.204), and employment status (TE, 0.150)] were most influential. These results may help prioritize patient-specific initiatives to increase accrual.

Abstract Oligodendrogliomas are initially slow-growing brain tumors that are prone to malignant transformation despite surgery and cytotoxic therapy. Understanding of oligodendroglioma evolution and new treatments for patients have been encumbered by a paucity of patient-matched newly diagnosed and recurrent tumor samples for multiplatform analyses, and by a lack of preclinical models for interrogation of therapeutic vulnerabilities that drive oligodendroglioma growth. Here we integrate spatial and functional analyses of tumor samples and patient-derived organoid co-cultures to show that synaptic connectivity is a hallmark of oligodendroglioma evolution and recurrence. We find that patient-matched recurrent oligodendrogliomas are enriched in synaptic gene expression programs irrespective of previous therapy or histologic grade. Analyses of spatial, single-cell, and clinical data reveal epigenetic misactivation of synaptic genes that are concentrated in regions of cortical infiltration and can be used to predict eventual oligodendroglioma recurrence. To translate these findings to patients, we show that local field potentials from tumor-infiltrated cortex at the time of resection and neuronal hyperexcitability and synchrony in patient-derived organoid co-cultures are associated with oligodendroglioma proliferation and recurrence. In preclinical models, we find that neurophysiologic drugs block oligodendroglioma growth and pathologic electrophysiology. These results elucidate mechanisms underlying oligodendroglioma evolution from an indolent tumor to a fatal disease and shed light on new biomarkers and new treatments for patients.

Abstract The disease course and clinical outcome for brain tumor patients depend not only on the molecular and histological features of the tumor but also on the patient’s demographics and social determinants of health. While current investigations in neuro-oncology have broadly utilized artificial intelligence (AI) to enrich tumor diagnosis and more accurately predict treatment response, postoperative complications, and survival, equity-driven applications of AI have been limited. However, AI applications to advance health equity in the broader medical field have the potential to serve as practical blueprints to address known disparities in neuro-oncologic care. In this consensus review, we will describe current applications of AI in neuro-oncology, postulate viable AI solutions for the most pressing inequities in neuro-oncology based on broader literature, propose a framework for the effective integration of equity into AI-based neuro-oncology research, and close with the limitations of AI.

Abstract Background The NIH Revitalization Act, implemented 29 years ago, set to improve the representation of women and minorities in clinical trials. In this study, we investigate progress made in all phase therapeutic clinical trials for neuroepithelial CNS tumors stratified by demographic-specific age-adjusted disease incidence and mortality. Additionally, we identify workforce characteristics associated with clinical trials meeting established accrual benchmarks. Methods Registry study of published clinical trials for World Health Organization defined neuroepithelial CNS tumors between January 2000 and December 2019. Study participants were obtained from PubMed and ClinicalTrials.gov. Population-based data originated from the CBTRUS for incidence analyses. SEER-18 Incidence-Based Mortality data was used for mortality analysis. Descriptive statistics, Fisher exact, and χ 2 tests were used for data analysis. Results Among 662 published clinical trials representing 49 907 participants, 62.5% of participants were men and 37.5% women (P < .0001) representing a mortality specific over-accrual for men (P = .001). Whites, Asians, Blacks, and Hispanics represented 91.7%, 1.5%, 2.6%, and 1.7% of trial participants. Compared with mortality, Blacks (47% of expected mortality, P = .008), Hispanics (17% of expected mortality, P < .001) and Asians (33% of expected mortality, P < .001) were underrepresented compared with Whites (114% of expected mortality, P < .001). Clinical trials meeting accrual benchmarks for race included minority authorship. Conclusions Following the Revitalization Act, minorities and women remain underrepresented in therapeutic clinical trials for neuroepithelial tumors, relative to disease incidence and mortality. Study accrual has improved with time. This study provides a framework for clinical trial accrual efforts and offers guidance regarding workforce considerations associated with enrollment of underserved patients.