Neuroblastoma: The impact of biology and cooperation leading to personalized treatments
Bibliographic record
Abstract
Neuroblastoma is the most common extra-cranial solid tumor in children. It is a heterogeneous disease, consisting of neural crest-derived tumors with remarkably different clinical behaviors. It can present in a wide variety of ways, including lesions which have the potential to spontaneously regress, or as an extremely aggressive form of metastatic cancer which is resistant to all forms of modern therapy. They can arise anywhere along the sympathetic nervous system. The median age of presentation is approximately 18 months of age. Urinary catecholamines (HVA and VMA) are extremely sensitive and specific tumor markers and are used in diagnosis, treatment response assessment and post-treatment surveillance. The largest national treatment groups from North America, Europe and Japan have formed the International Neuroblastoma Risk Group Task Force (INRG) to identify prognostic factors, to understand the mechanisms of tumorigenesis in this rare disease and to develop multi-modality therapies to improve outcomes and decrease treatment-related toxicities. This international cooperation has resulted in a significant leap in our understanding of the molecular pathogenesis of neuroblastoma. Lower staged disease can be cured if the lesion is resectable. Treatment of unresectable disease (loco-regional and metastatic) is stratified depending on clinical features (age at presentation, staging investigations) and specific tumor biological markers that include histopathological analyses, chromosomal abnormalities and the quantification of expression of an oncogene (MYCN). Modern treatment of high-risk neuroblastoma is the paradigm for the evolution of therapy in pediatric oncology. Outcomes have improved substantially with multi-modality therapy, including chemotherapy, surgery, radiation therapy, myeloablative therapy with stem cell transplant, immunotherapy and differentiation therapy; these comprise the standard of care worldwide. In addition, newer targeted therapies are being tested in phase I/II trials. If successful these agents will be incorporated into mainstream treatment programs.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".