Budhu, Joshua A

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 Despite major strides in cancer research and therapy, these advances have not been equitable across race and ethnicity. Historically marginalized groups (HMG) are more likely to have inadequate preventive screening, increased delays in diagnosis, and poor representation in clinical trials. Notably, Black, Hispanic, and Indigenous people represent 30% of the population but only 9% of oncology clinical trial participants. As a result, HMGs lack equitable access to novel therapies, contradicting the principle of distributive justice, as enshrined in the Belmont report, which demands the equitable selection of subjects in research involving human subjects. The lack of clinical trial diversity also leads to low generalizability and potentially harmful medical practices. Specifically, patients with brain cancer face unique barriers to clinical trial enrollment and completion due to disease-specific neurologic and treatment-induced conditions. Collectively, the intersection of these disease-specific conditions with social determinants of health fosters a lack of diversity in clinical trials. To ameliorate this disparity in neuro-oncology clinical trial participation, we present interventions focused on improving engagement of HMGs. Proposals range from inclusive trial design, decreasing barriers to care, expanding trial eligibility, access to tumor profiling for personalized medical trials, setting reasonable metrics and goals for accrual, working with patient community stakeholders, diversifying the neuro-oncology workforce, and development of tools to overcome biases with options to incentivize equity. The diversification of participation amongst neuro-oncology clinical trials is imperative. Equitable access and inclusion of HMG patients with brain tumors will not only enhance research discoveries but will also improve patient care.