Bibliographic record
Abstract
INTRODUCTION: We analyse data for the use of obinutuzumab in the treatment of CD20(+) lymphoproliferative disorders with a focus on chronic lymphocytic leukaemia (CLL). Targeted therapy against CD20 with the mAb rituximab led to significant improvements in survival for patients with B-cell non-Hodgkin lymphoma (NHL) and is the current mainstay of treatment for CD20(+) malignancies. Despite this, many patients relapse or become refractory after rituximab-containing therapies, so efforts have been made to develop better anti-CD20 mAbs. Obinutuzumab recently demonstrated superiority over rituximab in the only published Phase III study comparing the two antibodies. AREAS COVERED: Obinutuzumab is a humanised, anti-CD20 mAb being compared to rituximab in several Phase III studies. An overview of obinutuzumab, its mechanisms of action and results of Phase I-III studies are presented. EXPERT OPINION: The demonstration of superiority of obinutuzumab over rituximab in the CLL11 Phase III study is potentially practice-changing. Obinutuzumab has also proven safe and efficacious in CD20(+) NHL in Phase I/II studies and results of Phase III studies in NHL are eagerly awaited. The potential implications of improved outcomes for CLL and NHL with the introduction of this more potent anti-CD20 antibody are tremendous given the impressive results obtained after the introduction of rituximab over a decade ago.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".