Long-term outcomes of R-CEOP show curative potential in patients with DLBCL and a contraindication to anthracyclines
Bibliographic record
Abstract
Doxorubicin plays an integral role in the treatment of patients with diffuse large B-cell lymphoma (DLBCL) but can be associated with significant toxicity. Treatment guidelines of British Columbia (BC) Cancer recommend the substitution of etoposide for doxorubicin in standard-dose R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) (R-CEOP) for patients who have a contraindication to anthracyclines; however, it is unknown if this compromises treatment outcome. We identified all patients with newly diagnosed DLBCL who were treated in BC with curative intent with R-CEOP (n = 70) within the study period. Outcome in this population was compared with a 2:1 case-matched control group (n = 140) treated with R-CHOP and matched for age, clinical stage, and International Prognostic Index score. The 10-year time to progression and disease-specific survival were not significantly different for patients treated with R-CEOP compared with patients in the R-CHOP control group (53% vs 62% [P = .089] and 58% vs 67% [P = .251], respectively). The 10-year overall survival was lower in the R-CEOP group (30% vs 49%, P = .002), reflecting the impact of underlying comorbidities and frailty of this population. R-CEOP represents a useful treatment alternative for patients with DLBCL and an absolute contraindication to the use of anthracyclines, with curative potential.
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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".