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Oxford University Press, Neuro-Oncology, 2023

DOI: 10.1093/neuonc/noad036

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A critical analysis of neuro-oncology clinical trials

Journal article published in 2023 by Yeonju Kim, Terri S. Armstrong ORCID, Mark R. Gilbert, Orieta Celiku ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

AbstractBackgroundLimitations in trial design, accrual, and data reporting impact efficient and reliable drug evaluation in cancer clinical trials. These concerns have been recognized in neuro-oncology but have not been comprehensively evaluated. We conducted a semi-automated survey of adult interventional neuro-oncology trials, examining design, interventions, outcomes, and data availability trends.MethodsTrials were selected programmatically from ClinicalTrials.gov using primary malignant central nervous system tumor classification terms. Regression analyses assessed design and accrual trends; effect size analysis utilized survival rates among trials investigating survival.ResultsOf 3038 reviewed trials, most trials reporting relevant information were nonblinded (92%), single group (65%), nonrandomized (51%), and studied glioblastomas (47%) or other gliomas. Basic design elements were reported by most trials, with reporting increasing over time (OR = 1.24, P < .00001). Trials assessing survival outcomes were estimated to assume large effect sizes of interventions when powering their designs. Forty-two percent of trials were completed; of these, 38% failed to meet their enrollment target, with worse accrual over time (R = −0.94, P < .00001) and for US versus non-US based trials (OR = 0.5, P < .00001). Twenty-eight percent of completed trials reported partial results, with greater reporting for US (34.6%) versus non-US based trials (9.3%, P < .00001). Efficacy signals were detected by 15%–23% of completed trials reporting survival outcomes.ConclusionLow randomization rates, underutilization of controls, and overestimation of effect size, particularly pronounced in early-phase trials, impede generalizability of results. Suboptimal designs may be driven by accrual challenges, underscoring the need for cooperative efforts and novel designs. The limited results reporting highlights the need to incentivize data reporting and harmonization.