Clinical efficacy of daratumumab monotherapy in patients with heavily pretreated relapsed or refractory multiple myeloma
Bibliographic record
Abstract
The efficacy and favorable safety profile of daratumumab monotherapy in multiple myeloma (MM) was previously reported. Here, we present an updated pooled analysis of 148 patients treated with daratumumab 16 mg/kg. Data were combined from part 2 of a first-in-human phase 1/2 study of patients who relapsed after or were refractory to ≥2 prior therapies and a phase 2 study of patients previously treated with ≥3 prior lines of therapy (including a proteasome inhibitor [PI] and an immunomodulatory drug [IMiD]) or were double refractory. Among the pooled population, patients received a median of 5 prior lines of therapy (range, 2 to 14 prior lines of therapy), and 86.5% were double refractory to a PI and an IMiD. Overall response rate was 31.1%, including 13 very good partial responses, 4 complete responses, and 3 stringent complete responses. The median duration of response was 7.6 months (95% confidence interval [CI], 5.6 to not evaluable [NE]). The median progression-free survival (PFS) and overall survival (OS) were 4.0 months (95% CI, 2.8-5.6 months) and 20.1 months (95% CI, 16.6 months to NE), respectively. When stratified by responders vs stable disease/minimal response vs progressive disease/NE, median PFS was 15.0 months (95% CI, 7.4 months to NE) vs 3.0 months (95% CI, 2.8-3.7 months) vs 0.9 months (95% CI, 0.9-1.0 months), respectively, and median OS was NE (95% CI, NE to NE) vs 18.5 months (95% CI, 15.1-22.4 months) vs 3.7 months (95% CI, 1.7-7.6 months), respectively. No new safety signals were identified. In this pooled data set, daratumumab 16 mg/kg monotherapy demonstrated rapid, deep, and durable responses, with a clinical benefit that extended to patients with stable disease or better.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".