Phase III Study of R-CVP Compared With Cyclophosphamide, Vincristine, and Prednisone Alone in Patients With Previously Untreated Advanced Follicular Lymphoma
Bibliographic record
Abstract
PURPOSE: To compare the long-term outcome of patients with previously untreated follicular lymphoma (FL) needing therapy, after treatment with cyclophosphamide, vincristine and prednisone (CVP) versus CVP plus rituximab (R-CVP) and to evaluate the predictive value of known prognostic factors after treatment with R-CVP. PATIENTS AND METHODS: Patients with previously untreated CD20-positive stage III/IV FL were randomly assigned to eight cycles of R-CVP (n = 159) or CVP alone (n = 162). The median follow-up period was 53 months. RESULTS: The primary end point-time to treatment failure (TTF), which included patients without a response after four cycles as an event-was significantly prolonged in patients receiving R-CVP versus CVP (P < .0001). Improvements in all other end points, including overall and complete response rates (P < .0001), time to progression (TTP; P < .0001), response duration (P < .0001), time to next antilymphoma treatment (P < .0001), and overall survival (OS; P = .029; 4-year OS: 83% v 77%;) were achieved with R-CVP versus CVP alone. Univariate analyses demonstrated an improvement in TTP with R-CVP versus CVP irrespective of the Follicular Lymphoma International Prognostic Index (FLIPI) subgroup, the International Prognostic Index (IPI) subgroup, baseline histology, and the presence or absence of B symptoms or bulky disease. By multivariate analysis, FLIPI retains a strong predictive power for TTP in the presence of the trial treatment effect. CONCLUSION: Analysis of all outcome measures, including OS, confirm the benefit of adding R to CVP in the front-line treatment of FL.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".