Chukwueke, Ugonma N

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.

PURPOSE The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial that uses response adaptive randomization and genomic profiling to efficiently identify novel therapies for phase III testing. Three initial experimental arms (abemaciclib [a cyclin-dependent kinase [CDK]4/6 inhibitor], neratinib [an epidermal growth factor receptor [EGFR]/human epidermal growth factor receptor 2 inhibitor], and CC-115 [a deoxyribonucleic acid–dependent protein kinase/mammalian target of rapamycin inhibitor]) were simultaneously evaluated against a common control arm. We report the results for each arm and examine the feasibility and conduct of the adaptive platform design. PATIENTS AND METHODS Patients with newly diagnosed O 6 -methylguanine–DNA methyltransferase-unmethylated glioblastoma were eligible if they had tumor genotyping to identify prespecified biomarker subpopulations of dominant glioblastoma signaling pathways (EGFR, phosphatidylinositol 3-kinase, and CDK). Initial random assignment was 1:1:1:1 between control (radiation therapy and temozolomide) and the experimental arms. Subsequent Bayesian adaptive randomization was incorporated on the basis of biomarker-specific progression-free survival (PFS) data. The primary end point was overall survival (OS), and one-sided P values are reported. The trial is registered with ClinicalTrials.gov (identifier: NCT02977780 ). RESULTS Two hundred thirty-seven patients were treated (71 control; 73 abemaciclib; 81 neratinib; 12 CC-115) in years 2017-2021. Abemaciclib and neratinib were well tolerated, but CC-115 was associated with ≥ grade 3 treatment-related toxicity in 58% of patients. PFS was significantly longer with abemaciclib (hazard ratio [HR], 0.72; 95% CI, 0.49 to 1.06; one-sided P = .046) and neratinib (HR, 0.72; 95% CI, 0.50 to 1.02; one-sided P = .033) relative to the control arm but there was no PFS benefit with CC-115 (one-sided P = .523). None of the experimental therapies demonstrated a significant OS benefit ( P > .05). CONCLUSION The INSIGhT design enabled efficient simultaneous testing of three experimental agents using a shared control arm and adaptive randomization. Two investigational arms had superior PFS compared with the control arm, but none demonstrated an OS benefit. The INSIGhT design may promote improved and more efficient therapeutic discovery in glioblastoma. New arms have been added to the trial.