Radiotherapy in younger patients with advanced aggressive B-cell lymphoma—long-term results from the phase 3 R-MegaCHOEP trial
Bibliographic record
Abstract
The role of consolidative radiotherapy (RT) for patients with aggressive B-cell lymphoma has not been fully elucidated. The R-MegaCHOEP trial investigated the use of high-dose chemotherapy and rituximab with subsequent autologous stem cell transplantations compared to conventional immunochemotherapy (R-CHOEP) for high-risk patients up to 60 years. The study protocol included RT for patients with bulky (maximum diameter ≥7.5 cm) or extranodal disease. Two-hundred sixty-one patients were analyzed, 120 of whom underwent RT. The most frequently irradiated regions were mediastinum (n = 50) and paraaortic (n = 27). Median RT dose was 36 Gray in median fractions of 1.8 Gray. Acute toxicities were mostly mild to moderate, with only 24 and 8 grade 3 and 4 toxicities reported during RT. Patients with bulky disease who received RT showed significantly better 10-year EFS, PFS and OS (EFS: 64% vs. 35%; p < 0.001; PFS 68% vs. 47%; p = 0.003; OS: 72% vs. 59%; p = 0.011). There was no significant increase in secondary malignancies with the use of RT. RT administered for consolidation of bulky disease after immunochemotherapy improved the prognosis of young high-risk patients with aggressive B-cell lymphoma and should be considered part of first-line therapy. The trial was registered with ClinicalTrials.gov, number NCT00129090.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".