Randomized Phase II Trial Comparing Obinutuzumab (GA101) With Rituximab in Patients With Relapsed CD20<sup>+</sup> Indolent B-Cell Non-Hodgkin Lymphoma: Final Analysis of the GAUSS Study
Bibliographic record
Abstract
PURPOSE: Obinutuzumab (GA101), a novel glycoengineered type II anti-CD20 monoclonal antibody, demonstrated responses in single-arm studies of patients with relapsed/refractory non-Hodgkin lymphoma. This is the first prospective, randomized study comparing safety and efficacy of obinutuzumab with rituximab in relapsed indolent lymphoma. The primary end point of this study was the overall response rate (ORR) in patients with follicular lymphoma after induction and safety in patients with indolent lymphoma. PATIENTS AND METHODS: A total of 175 patients with relapsed CD20(+) indolent lymphoma requiring therapy and with previous response to a rituximab-containing regimen were randomly assigned (1:1) to four once-per-week infusions of either obinutuzumab (1,000 mg) or rituximab (375 mg/m(2)). Patients without evidence of disease progression after induction therapy received obinutuzumab or rituximab maintenance therapy every 2 months for up to 2 years. RESULTS: Among patients with follicular lymphoma (n = 149), ORR seemed higher for obinutuzumab than rituximab (44.6% v 33.3%; P = .08). This observation was also demonstrated by a blinded independent review panel that measured a higher ORR for obinutuzumab (44.6% v 26.7%; P = .01). However, this difference did not translate into an improvement in progression-free survival. No new safety signals were observed for obinutuzumab, and the incidence of adverse events was balanced between arms, with the exception of infusion-related reactions and cough, which were higher in the obinutuzumab arm. CONCLUSION: Obinutuzumab demonstrated a higher ORR without appreciable differences in safety compared with rituximab. However, the clinical benefit of obinutuzumab in this setting remains unclear and should be evaluated within phase III trials.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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) | 0.004 | 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".