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Background: Oncogenic FGFR-TACC fusions are present in 3-5% of high-grade gliomas (HGGs). Fexagratinib (AZD4547) is an oral FGFR1-3 inhibitor with preclinical activity in FGFR-TACC+ gliomas. We tested its safety and efficacy in patients with recurrent FGFR-TACC + HGGs., Patients and Methods: TARGET (NCT02824133) is a phase I/II open-label multicenter study that included adult patients with FGFR-TACC + HGGs relapsing after ≥1 line of standard chemoradiation. Patients received fexagratinib 80 mg bd on a continuous schedule until disease progression or unacceptable toxicity. The primary endpoint was the 6-month progression-free survival rate (PFS6)., Results: Twelve patients with recurrent IDH wildtype FGFR-TACC + HGGs (all FGFR3-TACC3+) were included in the efficacy cohort (male/female ratio = 1.4, median age = 61.5 years). Most patients (67%) were included at the first relapse. The PFS6 was 25% (95% confidence interval 5-57%), with a median PFS of 1.4 months. All patients without progression at 6 months ( n  = 3) were treated at first recurrence (versus 56% of those in progression) and remained progression-free for 14-23 months. The best response was RANO partial response in 1 patient (8%), stable disease in 5 (42%), and progressive disease in 6 (50%). Median survival was 17.5 months from inclusion. Grade 3 toxicities included lymphopenia, hyperglycaemia, stomatitis, nail changes, and alanine aminotransferase increase ( n  = 1 each). No grade 4-5 toxicities were seen. A 32-gene signature was associated with the benefit of FGFR inhibition in FGFR3-TACC3 + HGGs., Conclusions: Fexagratinib exhibited acceptable toxicity but limited efficacy in recurrent FGFR3-TACC3 + HGGs. Patients treated at first recurrence appeared more likely to benefit, yet additional evidence is required., Competing Interests: A.P. and M.S. declare having received travel support from Astra Zeneca. The other authors have declared no conflict of interest relevant to this paper., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

In cluster randomized trials, the intraclass correlation coefficient (ICC) is classically used to measure clustering. When the outcome is binary, the ICC is known to be associated with the prevalence of the outcome. This association challenges its interpretation and can be problematic for sample size calculation. To overcome these situations, Crespi et al. extended a coefficient named R , initially proposed by Rosner for ophthalmologic data, to cluster randomized trials. Crespi et al. asserted that R may be less influenced by the outcome prevalence than is the ICC, although the authors provided only empirical data to support their assertion. They also asserted that "the traditional ICC approach to sample size determination tends to overpower studies under many scenarios, calling for more clusters than truly required", although they did not consider empirical power. The aim of this study was to investigate whether R could indeed be considered independent of the outcome prevalence. We also considered whether sample size calculation should be better based on the R coefficient or the ICC. Considering the particular case of 2 individuals per cluster, we theoretically demonstrated that R is not symmetrical around the 0.5 prevalence value. This in itself demonstrates the dependence of R on prevalence. We also conducted a simulation study to explore the case of both fixed and variable cluster sizes greater than 2. This simulation study demonstrated that R decreases when prevalence increases from 0 to 1. Both the analytical and simulation results demonstrate that R depends on the outcome prevalence. In terms of sample size calculation, we showed that an approach based on the ICC is preferable to an approach based on the R coefficient because with the former, the empirical power is closer to the nominal one. Hence, the R coefficient does not outperform the ICC for binary outcomes because it does not offer any advantage over the ICC.