Bortezomib Added to R-CVP Is Safe and Effective for Previously Untreated Advanced-Stage Follicular Lymphoma: A Phase II Study by the National Cancer Institute of Canada Clinical Trials Group
Bibliographic record
Abstract
PURPOSE: Bortezomib has demonstrated promising activity in patients with follicular lymphoma (FL). This is the first study to evaluate the safety and efficacy of bortezomib added to rituximab, cyclophosphamide, vincristine, and prednisone (R-CVP) in previously untreated advanced-stage FL. PATIENTS AND METHODS: This is a phase II multicenter trial adding bortezomib (1.3 mg/m(2) days 1 and 8) to standard-dose R-CVP (BR-CVP) for up to eight cycles in patients with newly diagnosed stage III/IV FL requiring therapy. Two co-primary end points, complete response rate (complete response [CR]/CR unconfirmed [CRu]) and incidence of grade 3 or 4 neurotoxicity, were assessed. RESULTS: Between December 2006 and March 2009, 94 patients were treated with BR-CVP. Median patient age was 57 years (range, 29 to 84 years), and the majority had a high (47%) or intermediate (43%) Follicular Lymphoma International Prognostic Index score. BR-CVP was extremely well tolerated, with 90% of patients completing the intended eight cycles. No patients developed grade 4 neurotoxicity, and only five of 94 patients (5%; 95% CI, 0.8% to 9.9%) developed grade 3 neurotoxicity, which was largely reversible. On the basis of an intention-to-treat analysis, 46 of 94 patients (49%; 95% CI, 38.8% to 59.0%) achieved a CR/CRu, and 32 of 94 patients (34%) achieved a partial response, for an overall response rate of 83% (95% CI, 75.4% to 90.6%). CONCLUSION: The addition of bortezomib to standard-dose R-CVP for advanced-stage FL is feasible and well tolerated with minimal additional toxicity. The complete response rate in this high-risk population compares favorably to historical results of patients receiving R-CVP. Given these results, a phase III trial comparing BR-CVP with R-CVP is planned.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".