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Record W4401978856 · doi:10.1158/1078-0432.ccr-24-1611

Update on Pediatric Cancer Surveillance Recommendations for Patients with Neurofibromatosis Type 1, Noonan Syndrome, CBL Syndrome, Costello Syndrome, and Related RASopathies

2024· review· en· W4401978856 on OpenAlexaff
Melissa R. Perrino, Anirban Das, Sarah Scollon, Sarah G. Mitchell, Mary‐Louise C. Greer, Marielle E. Yohe, Jordan R. Hansford, Jennifer M. Kalish, Kris Ann P. Schultz, Suzanne P. MacFarland, Wendy Kohlmann, Philip J. Lupo, Kara N. Maxwell, Stefan M. Pfister, Rosanna Weksberg, Orli Michaeli, Marjolijn C.J. Jongmans, Gail E. Tomlinson, Jack Brzezinski, Uri Tabori, Gina M. Ney, Karen W. Gripp, Andrea M. Gross, Brigitte C. Widemann, Douglas R. Stewart, Emma R. Woodward, Christian P. Kratz

Bibliographic record

VenueClinical Cancer Research · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersDivision of Cancer Epidemiology and Genetics, National Cancer InstituteManchester Biomedical Research CentreNational Institute for Health and Care ResearchAmerican Lebanese Syrian Associated CharitiesNational Cancer InstituteNational Institutes of HealthAlexion Pharmaceuticals
KeywordsCostello syndromeNoonan syndromeMedicineNeurofibromatosisGenetic counselingCancerPediatricsPopulationInternal medicinePathologyGeneticsColorectal cancer

Abstract

fetched live from OpenAlex

Neurofibromatosis type 1 (NF1), Noonan syndrome, and related syndromes, grouped as RASopathies, result from dysregulation of the RAS-MAPK pathway and demonstrate varied multisystemic clinical phenotypes. Together, RASopathies are among the more prevalent genetic cancer predisposition syndromes and require nuanced clinical management. When compared with the general population, children with RASopathies are at significantly increased risk of benign and malignant neoplasms. In the past decade, clinical trials have shown that targeted therapies can improve outcomes for low-grade and benign neoplastic lesions but have their own challenges, highlighting the multidisciplinary care needed for such individuals, specifically those with NF1. This perspective, which originated from the 2023 American Association for Cancer Research Childhood Cancer Predisposition Workshop, serves to update pediatric oncologists, neurologists, geneticists, counselors, and other health care professionals on revised diagnostic criteria, review previously published surveillance guidelines, and harmonize updated surveillance recommendations for patients with NF1 or RASopathies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.676
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.106
GPT teacher head0.462
Teacher spread0.356 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations28
Published2024
Admission routes1
Has abstractyes

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