DREAMM-2: Single-agent belantamab mafodotin (GSK2857916) in patients with relapsed/refractory multiple myeloma (RRMM) and high-risk (HR) cytogenetics.
Bibliographic record
Abstract
8541 Background: Patients with RRMM and HR cytogenetics have a poor prognosis and need effective therapies. In DREAMM-2 (NCT03525678), single-agent belantamab mafodotin (an immunoconjugate targeting B-cell maturation antigen) demonstrated clinically meaningful activity and a manageable safety profile in patients with heavily pretreated RRMM ( Lancet Oncol.2020). We present outcomes in patients with HR-cytogenetics (9-month follow-up). Methods: Patients with RRMM received single-agent belantamab mafodotin (2.5 or 3.4 mg/kg). For this post hoc analysis, HR-cytogenetics included t(4;14), t(14;16), 17p13del, or 1q21+ (tested locally). Results: The median number of cycles was 3 (2.5: range: 1–15) and 4 (3.4: range: 1–14). Overall response rate (ORR; ≥partial response [PR] per independent review committee) was 27% in the 2.5 mg/kg group (22% with ≥very good partial response [VGPR]) and 40% in the 3.4 mg/kg group (27% with ≥VGPR). The median duration of response (DoR) was not reached in the 2.5 mg/kg group and was 6.2 months in the 3.4 mg/kg group. The most common adverse events ( > 30% in either group) were consistent with the overall population ( Lancet Oncol.2020): keratopathy (2.5: 59%;3.4: 79%), thrombocytopenia (2.5: 44%; 3.4: 65%), nausea (2.5: 27%; 3.4: 33%), anemia (2.5: 24%; 3.4: 42%), and blurred vision (2.5: 20%; 3.4: 42%). Conclusions: Patients with HR-cytogenetics maintain deep and durable clinical responses with single-agent belantamab mafodotin, comparable to that reported in the overall population. The safety profile remained consistent with previous reports. Funding: GlaxoSmithKline (205678). Drug linker technology licensed from Seattle Genetics; monoclonal antibody produced using POTELLIGENT Technology licensed from BioWa. Clinical trial information: NCT03525678 . [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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".