Practical Management of Aggressive B-Cell Lymphomas with CD20×CD3 Bispecific Antibodies
Bibliographic record
Abstract
CD20×CD3 bispecific antibodies (BsAbs) have transformed the therapeutic landscape of relapsed or refractory large B-cell lymphoma (LBCL). By redirecting T cells to target CD20-expressing lymphoma cells, these off-the-shelf agents offer high response rates and durable remissions in patients who previously had limited options, including those who relapse after chimeric antigen receptor T-cell therapy. In Canada, epcoritamab and glofitamab are now approved for patients with LBCL after at least two prior lines of treatment. The combination of glofitamab, gemcitabine, and oxaliplatin has been recently approved for patients with relapsed/refractory diffuse large B-cell lymphoma not otherwise specified LBCL after at least 1 line of therapy and who are ineligible for autologous hematopoietic stem cell transplant. This review provides a practical framework for Canadian hematologists: identifying eligible patients, implementing pretreatment evaluation, safely delivering therapy in inpatient and outpatient settings, and managing toxicities such as cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome. We will also discuss infection prophylaxis, sequencing with cellular therapies, and future directions for BsAbs in earlier treatment lines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".