Consensus on Malignant and Benign Tumors in Pediatric Patients with Neurofibromatosis Type 1: On Behalf of the Brazilian Society of Pediatric Oncology (SOBOPE)
Bibliographic record
Abstract
Neurofibromatosis type 1 (NF1) is an inherited, autosomal dominant syndrome that affects about 1 in every 3000 people worldwide. Early tumor detection is crucial for surveillance and intervention, especially given the potential for serious complications, including visual impairment, skeletal deformities, and malignancy. Therefore, it is essential for pediatricians and other healthcare professionals who provide care to these patients to be aware of all signs, treatments, and management strategies to deliver the best possible care. This study aims to develop a consensus for the diagnosis, treatment, and management of benign and malignant tumors associated with pediatric patients with NF1. Delphi methodology was used to achieve consensus among experts on the diagnostic accuracy, therapeutic efficacy, safety, and surveillance of pediatric patients with NF1. The consensus made 24 recommendations: gliomas in the optic pathway-6 statements, non-optical gliomas-2 statements, plexiform neurofibromas-5 statements, malignant peripheral nerve sheath tumors (MPNST)-6 statements, melanoma-1 statement, juvenile myelomonocytic leukemia (JMML)-1 statement, pheochromocytoma and paraganglioma-2 statements, and gastrointestinal stromal tumors (GIST)-1 statement. This consensus represents the first Brazilian recommendations on malignant and benign tumors in pediatric patients with NF1, providing a framework to standardize and optimize the clinical application for this disease.
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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 | 0.025 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".