Mosunetuzumab for the treatment of follicular lymphoma
Bibliographic record
Abstract
INTRODUCTION: Follicular lymphoma (FL) is an indolent non-Hodgkin lymphoma that shows a progressive increase in relapses and refractory in its natural history and a median survival of approximately 18-20 years. The advent of anti-CD20 monoclonal antibodies has changed the FL therapeutic algorithm, with an increase in progression-free survival. T-cell-dependent bispecific antibodies (BsAbs) represent an emerging drug class against FL. AREAS COVERED: In this review, we selected papers from the principal databases (PubMed, Medline, Medscape, ASCO, ESMO) between January 2021 and June 2024, using the keywords 'mosunetuzumab' and 'follicular lymphoma' to provide an overview of mosunetuzumab-axgb, a pioneering BsAb. Its mechanism of action, efficacy, safety, and future perspectives were analyzed. EXPERT OPINION: Mosunetuzumab grants a directing T-cell mediated cytotoxicity and allows a step-up dosing that reduces adverse events, such as cytokine release syndrome, with promising tolerability. At the same time, it improves outcomes in the evolving landscape of FL management, even in post-CAR-T FL patients. Prognostic factors and targetable mechanisms of resistance need to be explored.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".