Brentuximab Vedotin Combination for Relapsed Diffuse Large B-Cell Lymphoma
Bibliographic record
Abstract
PURPOSE In patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL), brentuximab vedotin (BV) as monotherapy or combined with either lenalidomide (Len) or rituximab (R) has demonstrated efficacy with acceptable safety. We evaluated the efficacy and safety of BV + Len + R versus placebo + Len + R in patients with R/R DLBCL. METHODS ECHELON-3 is a randomized, double-blind, placebo-controlled, multicenter, phase 3 trial comparing BV + Len + R with placebo + Len + R in patients with R/R DLBCL. Patients received BV or placebo once every 3 weeks, Len once daily, and R once every 3 weeks. The primary end point was overall survival (OS), and secondary end points included investigator-assessed progression-free survival (PFS) and objective response rate (ORR). A prespecified interim analysis was performed after 134 OS events, with two-sided P = .0232 as the efficacy boundary. RESULTS Patients (N = 230) were randomly assigned to receive BV + Len + R (n = 112) or placebo + Len + R (n = 118). Two patients in the placebo arm did not receive treatment. With a median follow-up of 16.4 months, the median OS was 13.8 months with BV + Len + R versus 8.5 months with placebo + Len + R (hazard ratio, 0.63 [95% CI, 0.45 to 0.89]; two-sided P = .009). The median PFS was 4.2 months with BV + Len + R versus 2.6 months with placebo + Len + R (hazard ratio, 0.53 [95% CI, 0.38 to 0.73]; two-sided P < .001). The ORR was 64% ([95% CI, 55 to 73]; two-sided P < .001) with BV + Len + R and 42% (95% CI, 33 to 51) with placebo + Len + R; complete response rates were 40% and 19%, respectively. Treatment-emergent adverse events (AEs) occurred in 97% of patients in both arms. In both arms, the most common treatment-emergent AEs were neutropenia, thrombocytopenia, diarrhea, and anemia. CONCLUSION BV + Len + R demonstrated a statistically significant survival benefit with a manageable safety profile in heavily pretreated patients with R/R DLBCL.
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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 | 0.000 |
| 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".