Safety and efficacy of glofitamab for relapsed/refractory large B-cell lymphoma in a multinational real-world study
Bibliographic record
Abstract
ABSTRACT: Glofitamab, a bispecific antibody targeting CD20 and CD3, is approved for relapsed/refractory diffuse large B-cell lymphoma (r/r DLBCL) after at least 2 prior treatment lines, but real-world data are scarce. In this retrospective, multicenter, multinational study, we evaluated the outcomes of 70 patients with r/r DLBCL treated with glofitamab as part of the compassionate use patient program in Germany, Austria, and Switzerland. The median number of prior treatment lines was 4, with 71% of patients refractory to their last treatment. Cytokine release syndrome was observed in 40% of patients (grade 3-4 in 2%), immune effector cell-associated neurotoxicity syndrome in 10% (grade 3 in 1%), and infections in 31% (grade 5 in 3%). The overall response rate was 46%, with 27% achieving complete responses (CR) and 19% partial responses. The median progression-free survival (PFS) was 3.6 months, whereas the median overall survival was 5.7 months. Notably, 13 patients (19%) were in CR 6 months after initiating glofitamab and exhibited durable responses. Elevated lactate dehydrogenase is the most robust predictor of inferior outcome. Patients pretreated with bendamustine within 6 months prior to glofitamab initiation exhibited significantly reduced PFS, suggesting that bendamustine may impair T-cell fitness and hence glofitamab efficacy. In summary, glofitamab demonstrates promising efficacy and a manageable safety profile in heavily pretreated patients with r/r DLBCL in a real-world scenario and the optimal sequence of treatments should use T-cell-depleting agents before glofitamab with caution.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".