Outcomes of bispecific antibody therapy after CAR T-cell failure in relapsed/refractory large B-cell lymphoma
Bibliographic record
Abstract
ABSTRACT: Patients with large B-cell lymphoma (LBCL) who experience relapsed disease after CD19-directed chimeric antigen receptor (CAR) T-cell (CAR-T) therapy have a poor prognosis. Bispecific antibodies (BsAbs) induce complete remissions in ∼35% of these cases. Hypothesizing overlapping LBCL-intrinsic resistance mechanisms as well as common poor prognosis predictors to CAR-T and BsAb therapy, we conducted a multicenter retrospective analysis including 92 patients with relapsed/refractory (R/R) LBCL treated with BsAbs after CAR-T failure. Overall response rate (ORR) was 43%, with a progression-free survival (PFS) of 2.8 months. Patients receiving BsAbs during early relapse (≤3 months) achieved a significantly worse outcome (ORR, 29%; PFS, 2.2 months) compared with patients with an intermediate (4-6 months; ORR, 54%; PFS, 3.7 months) or a late relapse (>6 months; ORR, 60%; PFS, 10.5 months). The benefit of later relapse was particularly notable in patients receiving BsAbs as first salvage therapy compared with those receiving a BsAb in subsequent lines (PFS not reached vs 2.7 months; overall survival not reached vs 9.1 months, respectively). In addition to early R/R state before BsAbs, elevated lactate dehydrogenase and higher International Prognostic Index score were significant predictors of poor outcomes to BsAb in multivariate Cox regression analyses. The finding that patients with early relapse after CAR-T respond particularly poorly to BsAb highlights the necessity for alternative treatment options in this high-risk patient cohort.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".