A phase 1 study of belantamab mafodotin in combination with standard of care in newly diagnosed multiple myeloma: An interim analysis of DREAMM-9.
Bibliographic record
Abstract
8018 Background: Belantamab mafodotin (belamaf) is a B-cell maturation antigen-binding antibody-drug conjugate that eliminates myeloma cells via direct cell killing and anti-myeloma immune responses. DREAMM-9 (NCT04091126) is an ongoing Phase 1, randomized, dose and schedule evaluation study. It aims to evaluate belamaf plus bortezomib, lenalidomide, and dexamethasone (VRd) in adult patients (pts) with transplant-ineligible (TI) newly diagnosed MM (NDMM) and to establish the recommended dose for future development of belamaf combination therapies in the 1st-line setting. Herein, we report updated interim-analysis data. Methods: Belamaf dose cohorts (Co1–7) are shown in the Table. VRd was given every 3 weeks (Q3W) until cycle 8, and Rd Q4W thereafter. Following safety data from Co2–5, Co6–7 were opened in parallel (randomized 1:1) and have shorter follow-up (Table). Safety was the primary endpoint; efficacy and tolerability were secondary endpoints. Minimal residual disease (MRD) was assessed by next-generation sequencing (10-5). Results: As of data cutoff (Oct 20, 2022), 93 pts were treated across Co1–7. Median age (range) was 73 (51–88) years, 55% of pts were male, and 84% were white. The most commonly reported non-ocular adverse events (AEs) across all Co were thrombocytopenia (46%), constipation (36%), diarrhea (34%), and peripheral sensory neuropathy (31%). Overall, belamaf-related Grade ≥3 AEs occurred in 35% of pts and led to belamaf dose reductions in 7% and dose delays in 63% of all treated patients. Grade ≥3 ocular AEs (keratopathy and visual acuity [KVA] scale) occurred in 53% of all pts and led to dose reductions in 12% and dose delays in 52% of overall pts. Fatal AEs occurred in 7 pts, all unrelated to study treatment. Efficacy results and ocular AEs are summarized in the Table: 100% of pts responded in Co1 (1.9 mg/kg Q3/4W) and Co3 (1.9 mg/kg Q6/8W). Median time to very good partial response or better (≥VGPR) ranged from 2.1 to 3.1 months (mo) across cohorts. Highest MRD negativity (MRD[-]) rates (≥VGPR) were seen in Co1 (83%) and Co3 (67%). Conclusions: This updated interim analysis demonstrates that belamaf plus VRd has no new safety signals and provides early and deep anti-myeloma responses in pts with TI NDMM, with high MRD[-] rates. Clinical trial information: NCT04091126 . [Table: see text]
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".