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Canadian Consensus for Treatment of BRAF V600E Mutated Pediatric and AYA Gliomas.

Craig ErkerMagimairajan Issai VananLarouche ValérieLiana NobreChantel CacciottiStephanie VairyShayna ZelcerAdam J FlemingEric BouffetNada JabadoGeneviève LegaultSamuele RenziTara McKeownBruce CrooksNirav ThackerVijay RamsawamiHallie ColtinLucie Lafay-CousinSylvia ChengJuliette HukinSeth Andrew ClimansMary Jane Lim-FatSarah McKillopSarah LapointeMélanie AlvesJulie BennettUri TaboriSébastien Perreault
Published in: Current oncology (Toronto, Ont.) (2024)
Background: The treatment of BRAF V600E gliomas with BRAF inhibitors (BRAFis) and MEK inhibitors (MEKis) has been increasingly integrated into clinical practice for pediatric low-grade gliomas (PLGGs) and pediatric high-grade gliomas (HGGs). However, some questions remain unanswered, such as the best time to start targeted therapy, duration of treatment, and discontinuation of therapy. Given that no clinical trial has been able to address these critical questions, we developed a Canadian Consensus statement for the treatment of BRAF V600E mutated pediatric as well as adolescent and young adult (AYA) gliomas. Methods : Canadian neuro-oncologists were invited to participate in the development of this consensus. The consensus was discussed during monthly web-based national meetings, and the algorithms were revised until a consensus was achieved. Results : A total of 26 participants were involved in the development of the algorithms. Two treatment algorithms are proposed, one for the initiation of treatment and one for the discontinuation of treatment. We suggest that most patients with BRAF V600E gliomas should be treated with BRAFis ± MEKis upfront. Discontinuation of treatment can be considered in certain circumstances, and we suggest a slow wean. Conclusions: Based on expert consensus in Canada, we developed algorithms for treatment initiation of children and AYA with BRAF V600E gliomas as well as a discontinuation algorithm.
Keyphrases
  • high grade
  • low grade
  • clinical trial
  • machine learning
  • clinical practice
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  • randomized controlled trial
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  • signaling pathway
  • phase ii