Safety and efficacy of belantamab mafodotin with pembrolizumab in patients with relapsed or refractory multiple myeloma
Bibliographic record
Abstract
BACKGROUND: Belantamab mafodotin (belamaf) has shown promising antimyeloma activity in relapsed or refractory multiple myeloma (RRMM) as a single agent. It was hypothesized that its multimodal activity may be enhanced by programmed cell death protein 1 pathway inhibition and activation of T cell-mediated antitumor responses. This study investigated the efficacy and safety of belamaf with pembrolizumab in patients with RRMM. METHODS: DREAMM-4 (NCT03848845) was an open-label, single-arm, phase 1/2 study divided into dose-escalation (part 1) and dose-expansion (part 2) phases. Patients were ≥18 years old with ≥3 prior lines of therapy including a proteasome inhibitor, an immunomodulatory drug, and an anti-CD38 agent. Patients received belamaf (2.5 or 3.4 mg/kg, part 1; 2.5 mg/kg, part 2) and 200 mg pembrolizumab for ≤35 cycles. RESULTS: Of 41 enrolled patients, 34 (n = 6 part 1, n = 28 part 2) who received 2.5 mg/kg belamaf plus pembrolizumab were included in this final analysis. Sixteen patients (47%) achieved an overall response. Minimal residual disease negativity was achieved in three of 10 patients who had very good partial response or better. Five of eight patients who had prior anti-B-cell maturation antigen therapy achieved partial response or better, including two who had B-cell maturation antigen-refractory disease. Common grade ≥3 adverse events were keratopathy (38%) and thrombocytopenia (29%). Despite belamaf-related ocular events, quality-of-life measures remained stable over time. No new safety signals were observed. CONCLUSIONS: The results of DREAMM-4 demonstrated clinical activity and a favorable safety profile of belamaf plus pembrolizumab in patients with RRMM. This trial is registered at www. CLINICALTRIALS: gov as NCT03848845.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".