QLTI-02. Management of adverse events occurring with MAPK-directed therapies in patients with pediatric low-grade glioma: Recommendations from an expert Delphi consensus initiative
Bibliographic record
Abstract
Abstract BACKGROUND Pediatric low-grade gliomas (pLGGs) can become a chronic disease requiring multiple courses of therapy. Emerging mitogen-activated protein kinase (MAPK) inhibitors (MAPKi) are targeted therapies that are effective in patients with pLGGs harboring mutations in the MAPK/extracellular signal-regulated kinase 1/2 (ERK) signaling pathway. Successful management of adverse events (AEs) that occur with MAPKi is important to optimize clinical benefit. A modified Delphi consensus initiative was conducted to provide recommendations on the monitoring and management of AEs that occur with MAPKi in patients with pLGG. METHODS A steering committee (n=9) of healthcare professionals (HCPs) from five countries was convened to develop statements based on the findings of a comprehensive literature review of AEs reported with use of MAPKi in pediatric cancers. Consensus on statements was determined via two online surveys completed by a large, global panel of experts in pLGG. RESULTS From the literature review, 117 articles and 31 abstracts containing information on the toxicity and tolerability profiles of MAPKi were relevant for the development of statements. Of the 129 statements drafted, consensus (≥75% agreement) amongst 82 global experts in pLGG from 29 countries was reached for 50 statements. Most of the consensus statements were related to the general management of AEs occurring with MAPKi and the management of cutaneous AEs. Guidance on skin care and specific cutaneous conditions was developed. Other AEs occurring with MAPKi, such as gastrointestinal, cardiac, endocrine, and ophthalmologic, were drug class or drug-specific, seen rarely, or had limited evidence or experience from which to achieve consensus recommendations. CONCLUSIONS Guidance and recommendations for the management of common AEs in patients with pLGG treated with MAPKi were developed. Sharing this knowledge amongst HCPs may lead to patients with pLGG achieving optimal benefit from MAPKi, while minimizing and effectively managing AEs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.266 | 0.213 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".