Brentuximab vedotin in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone as frontline treatment for patients with CD30-positive B-cell lymphomas
Bibliographic record
Abstract
We conducted a phase I/II multicenter trial using 6 cycles of brentuximab vedotin (BV) in combination with rituximab, cyclophosphamide, doxorubicin, and prednisone (R-CHP) for treatment of patients with CD30-positive (+) B-cell lymphomas. Thirty-one patients were evaluable for toxicity and 29 for efficacy including 22 with primary mediastinal B-cell lymphoma (PMBCL), 5 with diffuse large B-cell lymphoma (DLBCL), and 2 with gray zone lymphoma (GZL). There were no treatment-related deaths; 32% of patients had non-hematological grade 3/4 toxicities. The overall response rate was 100% (95% CI: 88-100) with 86% (95% CI: 68-96) of patients achieving complete response at the end of systemic treatment. Consolidative radiation following end of treatment response assessment was permissible and used in 52% of all patients including 59% of patients with PMBCL. With a median follow-up of 30 months, the 2-year progression-free survival (PFS) and overall survival (OS) were 85% (95% CI: 66-94) and 100%, respectively. In the PMBCL cohort, 2-year PFS was 86% (95% CI: 62-95). In summary, BV-R-CHP with or without consolidative radiation is a feasible and active frontline regimen for CD30+ B-cell lymphomas (NCT01994850).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".