MabThera (Rituximab) Plus Cyclophosphamide, Vincristine and Prednisone (CVP) Chemotherapy Improves Survival in Previously Untreated Patients with Advanced Follicular Non-Hodgkin’s Lymphoma (NHL).
Bibliographic record
Abstract
Abstract Design/methods: Rituximab added to 8 cycles of CVP (R-CVP) chemotherapy improves time to progression and duration of response in previously untreated patients with stage III/IV CD20 positive follicular NHL compared with CVP alone (Marcus et al Blood2005;105:1417–23). A protocol pre-planned analysis of this study with a median follow-up of 53 months has now been performed. Results: A total of 321 patients (median age 53 years) were recruited. Eighty-three percent of patients in both arms had intermediate to high-risk disease according to the Follicular Lymphoma International Prognostic Index (FLIPI, score 2–5). Median time to progression or death (TTP) in the R-CVP arm was 34 months compared with 15 months in the CVP arm, p<0.0001 (log rank). This increase in TTP was observed in all FLIPI groups with a risk ratio of 0.40 (95% confidence interval 0.27 to 0.60) for good intermediate risk patients and 0.51 (95% confidence interval 0.34 to 0.76) for poor risk patients; overall the risk ratio was 0.44 (95% confidence interval 0.32 to 0.57). In patients achieving a complete response (CR) or CR unconfirmed (CRu), disease-free survival (DFS) was significantly prolonged (p=0.0001, log rank); the estimated 4-years’ DFS rate was 54% for patients receiving R-CVP compared with 17% for CVP. Nineteen percent (31/162) of patients in the R-CVP group have now died compared with 29% (46/159 patients) in the CVP group. Patients receiving R-CVP had a significant improvement in overall survival compared with CVP (p=0.03, log rank; hazard ratio 0.60 [95% confidence interval 0.38 to 0.96]). Conclusion: When added to first-line chemotherapy in patients with follicular NHL, rituximab not only improves TTP and DFS, but also has a favorable effect on overall survival.
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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) | 0.001 | 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 | 0.001 |
| 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".