Belantamab Mafodotin to Treat Multiple Myeloma: A Comprehensive Review of Disease, Drug Efficacy and Side Effects
Bibliographic record
Abstract
Multiple myeloma (MM) is a hematologic malignancy characterized by excessive clonal proliferation of plasma cells. The treatment of multiple myeloma presents a variety of unique challenges due to the complex molecular pathophysiology and incurable status of the disease at this time. Given that MM is the second most common blood cancer with a characteristic and unavoidable relapse/refractory state during the course of the disease, the development of new therapeutic modalities is crucial. Belantamab mafodotin (belamaf, GSK2857916) is a first-in-class therapeutic, indicated for patients who have previously attempted four other treatments, including an anti-CD38 monoclonal antibody, a proteosome inhibitor, and an immunomodulatory agent. In November 2017, the FDA designated belamaf as a breakthrough therapy for heavily pretreated patients with relapsed/refractory multiple myeloma. In August 2020, the FDA granted accelerated approval as a monotherapy for relapsed or treatment-refractory multiple myeloma. The drug was also approved in the EU for this indication in late August 2020. Of note, belamaf is associated with the following adverse events: decreased platelets, corneal disease, decreased or blurred vision, anemia, infusion-related reactions, pyrexia, and fetal risk, among others. Further studies are necessary to evaluate efficacy in comparison to other standard treatment modalities and as future drugs in this class are developed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".