EBV May Be Expressed in the LP Cells of Nodular Lymphocyte–predominant Hodgkin Lymphoma (NLPHL) in Both Children and Adults
Bibliographic record
Abstract
Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) and classical Hodgkin lymphoma (CHL) are classified separately because of their distinct clinical and pathologic features. Whereas Epstein-Barr virus (EBV) is detected in the neoplastic cells of 25% to 70% of CHL, NLPHL is generally considered to be EBV(-). We assessed EBV status in 302 pediatric and adult cases of NLPHL. A total of 145 pediatric (age 18 y or younger) and 157 adult cases of NLPHL were retrieved from 3 North American centers and tested for EBV by in situ hybridization (EBV-encoded small RNA). Clinical and pathologic features were analyzed. Five (3.4%) pediatric and 7 (4.5%) adult NLPHL cases contained EBV(+) lymphocyte-predominant (LP) cells. Although all 12 cases met the criteria for diagnosis of NLPHL, atypical features were present, including capsular fibrosis, atrophic germinal centers, and pleomorphic or atypical LP cells. CD20 and OCT-2 were strongly and diffusely positive in all except 1 case. However, PAX5 and CD79a were weak and/or variable in 7/8 and 6/6 cases tested, respectively. EBV(+) cases were more likely to be CD30(+) (75%) compared with EBV(-) cases (25%) (P=0.0007); CD15 was negative in all cases. Our results show that EBV(+) LP cells may occur in NLPHL. Distinguishing EBV(+) NLPHL from CHL can be challenging, as EBV(+) NLPHL can have partial expression of CD30 and weak PAX5 staining as well as pleomorphic-appearing LP cells. However, the overall appearance and maintenance of B-cell phenotype, with strong and diffuse CD20 and OCT-2 expression, support the diagnosis of NLPHL in these cases.
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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 | 0.001 | 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) | 0.001 | 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".