Gray zone lymphoma with features intermediate between classical<scp>H</scp>odgkin lymphoma and diffuse large<scp>B</scp>‐cell lymphoma:<scp>C</scp>haracteristics, outcomes, and prognostication among a large multicenter cohort
Bibliographic record
Abstract
Gray zone lymphoma (GZL) with features between classical Hodgkin lymphoma and diffuse large B-cell lymphoma (DLBCL) is a recently recognized entity reported to present primarily with mediastinal disease (MGZL). We examined detailed clinical features, outcomes, and prognostic factors among 112 GZL patients recently treated across 19 North American centers. Forty-three percent of patients presented with MGZL, whereas 57% had non-MGZL (NMGZL). NMGZL patients were older (50 versus 37 years, P = 0.0001); more often had bone marrow involvement (19% versus 0%, P = 0.001); >1 extranodal site (27% versus 8%, P = 0.014); and advanced stage disease (81% versus 13%, P = 0.0001); but they had less bulk (8% versus 44%, P = 0.0001), compared with MGZL patients. Common frontline treatments were cyclophosphamide-doxorubicin-vincristine-prednisone +/- rituximab (CHOP+/-R) 46%, doxorubicin-bleomycin-vinblastine-dacarbazine +/- rituximab (ABVD+/-R) 30%, and dose-adjusted etoposide-doxorubicin-cyclophosphamide-vincristine-prednisone-rituximab (DA-EPOCH-R) 10%. Overall and complete response rates for all patients were 71% and 59%, respectively; 33% had primary refractory disease. At 31-month median follow-up, 2-year progression-free survival (PFS) and overall survival rates were 40% and 88%, respectively. Interestingly, outcomes in MGZL patients seemed similar compared with that of NMGZL patients. On multivariable analyses, performance status and stage were highly prognostic for survival for all patients. Additionally, patients treated with ABVD+/-R had markedly inferior 2-year PFS (22% versus 52%, P = 0.03) compared with DLBCL-directed therapy (CHOP+/-R and DA-EPOCH-R), which persisted on Cox regression (hazard ratio, 1.88; 95% confidence interval, 1.03-3.83; P = 0.04). Furthermore, rituximab was associated with improved PFS on multivariable analyses (hazard ratio, 0.35; 95% confidence interval, 0.18-0.69; P = 0.002). Collectively, GZL is a heterogeneous and likely more common entity and often with nonmediastinal presentation, whereas outcomes seem superior when treated with a rituximab-based, DLBCL-specific regimen.
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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 | 0.000 |
| 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) | 0.001 | 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".