Evaluation of Image-Defined Risk Factor (IDRF) Assessment in Patients With Intermediate-risk Neuroblastoma: A Report From the Children's Oncology Group Study ANBL0531
Bibliographic record
Abstract
BACKGROUND: The International Neuroblastoma Risk Group (INRG) classifier utilizes a staging system based on pretreatment imaging criteria in which image-defined risk factors (IDRFs) are used to evaluate the extent of locoregional disease. Children's Oncology Group (COG) study ANBL0531 prospectively examined institutional determination of IDRF status and compared that to a standardized central review. METHODS: Between 9/2009-6/2011, patients with intermediate-risk neuroblastoma were enrolled on ANBL0531 and had IDRF assessment at treating institutions. Paired COG pediatric surgeons and radiologists performed blinded central review of diagnostic imaging for the presence or absence of IDRFs. Second blinded review was performed in cases of discordance. Comparison of local and central review was performed using the Kappa coefficient to determine concordance in IDRF assessment. RESULTS: 211 patients enrolled in ANBL0531 underwent IDRF assessment; 3 patients were excluded due to poor image quality. Central reviewer pairs agreed on the presence or absence of any IDRF in 170/208 (81.7%; κ = 0.48) cases. Thirteen (6.3%) cases could not be adjudicated after second blinded review. Radiologists were more likely to identify IRDFs as present than surgeons (p < 0.001). Local and central reviewers agreed on the presence or absence of any IDRF in only108/208 (51.9%; κ = 0.06) cases. CONCLUSIONS: Among experienced pediatric surgeons and radiologists participating in central review, concordance was moderate, with agreement in 81.7% of cases. On comparison of local and central assessment of IDRFs, concordance was poor. These data indicate that greater standardization, education, technology, and training are needed to improve the assessment of IDRFs in children with neuroblastoma. LEVEL OF EVIDENCE: Treatment Study, Level III.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| 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 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".