Excellent real‐world outcomes of adults with Burkitt lymphoma treated with <scp>CODOX</scp>‐M/<scp>IVAC</scp> plus or minus rituximab
Bibliographic record
Abstract
Treatment of Burkitt lymphoma (BL) with intensive, multi-agent chemotherapy with aggressive central nervous system (CNS) prophylaxis results in high cure rates, although no regimen is standard of care. We examined population-based survival outcomes of adults with BL treated with a modified combination of cyclophosphamide, vincristine, doxorubicin, prednisone and systemic high-dose methotrexate (MTX) (CODOX-M) with IVAC (ifosfamide, mesna, etoposide, cytarabine and intrathecal MTX) (CODOX-M/IVAC) ± rituximab over a 15-year period in British Columbia. For the 81 patients identified (including 8 with CNS involvement and 18 with human immunodeficiency virus-associated BL), 5-year progression-free survival (PFS) and overall survival (OS) were 75% [95% confidence interval (CI): 63-83%] and 77% (95% CI: 66-85%), respectively, with no treatment-related deaths. Those who completed the regimen per protocol (n = 38) had significantly improved 5-year PFS 86% (P = 0·04) and OS 92% (P = 0·008), as did those under 60 years with 5-year PFS 82% (P = 0·005) and OS 86% (P = 0·002), which remained significant in multivariate analysis [PFS: hazard ratio (HR) 3·36, P = 0·018; OS HR 4·03, P = 0·012]. Incorporation of high-dose systemic methotrexate also significantly affected multivariate survival outcomes (OS HR 0·28, P = 0·025). Stem cell transplant in first remission had no effect on OS or PFS. This large, real-world analysis of BL patients treated with CODOX-M/IVAC ± rituximab demonstrates excellent survival outcomes comparable to clinical trials. These results help to serve as a benchmark when comparing curative therapies for BL patients as novel regimens are incorporated into clinical practice.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".