Variant histology, IgD and CD30 expression in low‐risk pediatric nodular lymphocyte predominant Hodgkin lymphoma: A report from the Children's Oncology Group
Bibliographic record
Abstract
BACKGROUND: Histologic prognostic factors have been described for nodular lymphocyte predominant Hodgkin lymphoma (NLPHL). This study examines histologic and immunophenotypic variants in a clinical trial for pediatric NLPHL. PROCEDURE: One hundred sixty-eight cases of localized NLPHL were examined for histologic variants, CD30 and immunoglobulin D (IgD) expression, and outcome. Histologic types were scored categorically as 0 = 0, 1 ≤ 25%, and 2 > 25% of the sample. RESULTS: Fifty-eight (35.1%) cases showed only typical nodular with or without serpiginous histology (types A and B). The remainder showed mixtures of histologies. The numbers of patients with score 2 are 85 (50.6%) type A, 21 (12.5%) type B, 46 (27.4%) with extranodular large B cells (type C), 3 with T-cell-rich nodular pattern (type D), 55 (32.7%) with diffuse T-cell-rich (type E) pattern, and 2 (1.2%) with diffuse B-cell pattern (type F). Higher level of types C (P = 0.048) and D (P = 0.033) resulted in lower event-free survival (EFS). Cytoplasmic IgD was found in 65 of 130 tested (50%), did not significantly associate with EFS but positively correlated with types C and E histology (P < 0.0001) and negatively correlated with types A (P = 0.0003) and B (P = 0.006). Seventeen (10%) expressed CD30, with no adverse effect. CONCLUSIONS: Variant histology is common in pediatric NLPHL, especially types C and E, which are associated with IgD expression. Type C variant histology and possibly type D are associated with decreased EFS, but neither IgD nor CD30 are adverse features. Variant histology may warrant increased surveillance, but did not affect overall survival.
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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 | 0.000 | 0.001 |
| 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 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".