Validation of Postinduction Curie Scores in High-Risk Neuroblastoma: A Children’s Oncology Group and SIOPEN Group Report on SIOPEN/HR-NBL1
Bibliographic record
Abstract
A semiquantitative 123I-metaiodobenzylguanidine (123I-MIBG) scoring method (the Curie score, or CS) was previously examined in the Children’s Oncology Group (COG) high-risk neuroblastoma trial, COG A3973, with a postinduction CS of more than 2 being associated with poor event-free survival (EFS). The validation of the CS in an independent dataset, International Society of Paediatric Oncology European Neuroblastoma/High-Risk Neuroblastoma 1 (SIOPEN/HR-NBL1), is now reported. Methods: A retrospective analysis of 123I-MIBG scans obtained from patients who had been prospectively enrolled in SIOPEN/HR-NBL1 was performed. All patients exhibited 123I-MIBG–avid, International Neuroblastoma Staging System stage 4 neuroblastoma. 123I-MIBG scans were evaluated at 2 time points, diagnosis (n = 345) and postinduction (n = 330), before consolidation myeloablative therapy. Scans of 10 anatomic regions were evaluated, with each region being scored 0–3 on the basis of disease extent and a cumulative CS generated. Cut points for outcome analysis were identified by Youden methodology. CSs from patients enrolled in COG A3973 were used for comparison. Results: The optimal cut point for CS at diagnosis was 12 in SIOPEN/HR-NBL1, with a significant outcome difference by CS noted (5-y EFS, 43.0% ± 5.7% [CS ≤ 12] vs. 21.4% ± 3.6% [CS > 12], P < 0.0001). The optimal CS cut point after induction was 2 in SIOPEN/HR-NBL1, with a postinduction CS of more than 2 being associated with an inferior outcome (5-y EFS, 39.2% ± 4.7% [CS ≤ 2] vs. 16.4% ± 4.2% [CS > 2], P < 0.0001). The postinduction CS maintained independent statistical significance in Cox models when adjusted for the covariates of age and MYCN gene copy number. Conclusion: The prognostic significance of postinduction CSs has now been validated in an independent cohort of patients (SIOPEN/HR-NBL1), with a postinduction CS of more than 2 being associated with an inferior outcome in 2 independent large, cooperative group trials.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".