Neuroblastoma Predisposition and Surveillance—An Update from the 2023 AACR Childhood Cancer Predisposition Workshop
Bibliographic record
Abstract
Genetic predisposition to neuroblastoma (NB) is relatively rare. Only 1% to 2% of patients have a family history of NB, 3% to 4% of cases present with bilateral or multifocal primary tumors, and occasional patients have syndromes that are associated with increased NB risk. Previously, a germline pathogenic variant (GPV) in PHOX2B was associated with Hirschsprung disease and congenital central hypoventilation syndrome. Recently, certain GPVs were shown to be responsible for congenital central hypoventilation syndrome and NB predisposition. Also, several groups determined that activating GPVs in ALK accounted for a substantial number of familial NB. Finally, there are additional genes and cancer predisposition syndromes in which NB occurs with greater frequency or that have been associated with NB based on genome-wide association studies. We review the evidence for all these genes and whether there is sufficient evidence to warrant surveillance. We review recommended surveillance for hereditary patients with NB, including minor updates to surveillance recommendations that were published previously in 2017.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".