Evidence for an Age Cutoff Greater Than 365 Days for Neuroblastoma Risk Group Stratification in the Children's Oncology Group
Bibliographic record
Abstract
PURPOSE: In the Children's Oncology Group, risk group assignment for neuroblastoma is critical for therapeutic decisions, and patients are stratified by International Neuroblastoma Staging System stage, MYCN status, ploidy, Shimada histopathology, and diagnosis age. Age less than 365 days has been associated with favorable outcome, but recent studies suggest that older age cutoff may improve prognostic precision. METHODS: To identify the optimal age cutoff, we retrospectively analyzed data from the Pediatric Oncology Group biology study 9047 and Children's Cancer Group studies 321p1-p4, 3881, 3891, and B973 on 3,666 patients (1986 to 2001) with documented ages and follow-up data. Twenty-seven separate analyses, one for each different age cutoff (adjusting for MYCN and stage), tested age influence on outcome. The cutoff that maximized outcome difference between younger and older patients was selected. RESULTS: Thirty-seven percent of patients were younger than 365 days, and 64% were > or = 365 days old (4-year event-free survival [EFS] rate +/- SE: 83% +/- 1% [n = 1,339] and 45% +/- 1% [n = 2,327], respectively; P < .0001). Graphical analyses revealed the continuous nature of the prognostic contribution of age to outcome. The optimal 460-day cutoff we selected maximized the outcome difference between younger and older patients. Forty-three percent were younger than 460 days, and 57% were > or = 460 days old (4-year EFS rate +/- SE: 82% +/- 1% [n = 1,589] and 42% +/- 1% [n = 2,077], respectively; P < .0001). Using a 460-day cutoff (assuming stage 4, MYCN-amplified patients remain high-risk), 5% of patients (365 to 460 days: 4-year EFS 92% +/- 3%; n = 135) fell into a lower risk group. CONCLUSION: The prognostic contribution of age to outcome is continuous in nature. Within clinically relevant risk stratification, statistical support exists for an age cutoff of 460 days.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".