Risk stratification of high‐risk metastatic neuroblastoma: A report from the HR‐NBL‐1/SIOPEN study
Bibliographic record
Abstract
BACKGROUND: Risk stratification is crucial to treatment decision-making in neuroblastoma. This study aimed to explore factors present at diagnosis affecting outcome in patients aged ≥18 months with metastatic neuroblastoma and to develop a simple risk score for prognostication. PROCEDURE: Data were derived from the European high-risk neuroblastoma 1 (HR-NBL1)/International Society for Paediatric Oncology European Neuroblastoma (SIOPEN) trial with analysis restricted to patients aged ≥18 months with metastatic disease and treated prior to the introduction of immunotherapy. Primary endpoint was 5-year event-free survival (EFS). Prognostic factors assessed were sex, age, tumour MYCN amplification (MNA) status, serum lactate dehydrogenase (LDH)/ferritin, primary tumour and metastatic sites. Factors significant in univariate analysis were incorporated into a multi-variable model and an additive scoring system developed based on estimated log-cumulative hazard ratios. RESULTS: The cohort included 1053 patients with median follow-up 5.5 years and EFS 27 ± 1%. In univariate analyses, age; serum LDH and ferritin; involvement of bone marrow, bone, liver or lung; and >1 metastatic system/compartment were associated with worse EFS. Tumour MNA was not associated with worse EFS. A multi-variable model and risk score incorporating age (>5 years, 2 points), serum LDH (>1250 U/L, 1 point) and number of metastatic systems (>1, 2 points) were developed. EFS was significantly correlated with risk score: EFS 52 ± 9% for score = 0 versus 6 ± 3% for score = 5 (P < 0.0001). CONCLUSIONS: A simple score can identify an "ultra-high risk" (UHR) cohort (score = 5) comprising 8% of patients with 5-year EFS <10%. These patients appear not to benefit from induction therapy and could potentially be directed earlier to alternative experimental therapies in future trials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".