Incidence and survival among children with neuroblastoma in Spain over 22 years
Bibliographic record
Abstract
BACKGROUND: Neuroblastoma is the most common extracranial solid childhood tumour. Advances in risk stratification have improved survival by enabling better-tailored treatments. The Toronto Guidelines (TG) aim to standardise childhood cancer stage collection by cancer registries. However, population-based survival analyses by stage remain scarce. We aimed to study incidence and survival of neuroblastoma cases among Spanish children aged < 15 years, with special attention to the role of stage at diagnosis. METHODS: The Spanish Registry of Childhood Tumours (RETI-SEHOP) and the Spanish Neuroblastoma Clinical Database (NBL-CDB) were cross-linked to achieve nearly complete registration of neuroblastoma in Spain for the period of diagnosis 2000–2021. Kaplan-Meier estimates were obtained for overall survival (OS). Adjusted survival was estimated using a Cox proportional hazards model with stratification by age group. RESULTS: During 2000–2021, 1774 neuroblastoma cases aged 0–14 years were recorded, making a rough average of 81 cases diagnosed annually. Age-standardised incidence rate (World) 2000–2021: 14.0 cases per million children (0–14 years). Distribution of stage at diagnosis remained stable from 2000 to 2021. 5-year OS increased from 74% (2000–2005) to 81% (2012–2017). Statistically significant OS differences were identified between sexes, age groups, tumour morphologies, primary sites and stages. Over time, survival improvement was centred mostly on male and locoregional cases. CONCLUSIONS: Neuroblastoma incidence and survival results in Spain were consistent with those from other high-income countries. Survival improvements were related to changes in clinical management, such as administration of anti-GD2 immunotherapy or the start of the LINES clinical trial (EudraCT 2010-021396-81, registered on 15 June 2011; ClinicalTrials.gov identifier: NCT01728155). This study underscores the clinical interest in stage data being collected by cancer registries, as per the TG.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".