Efficacy of Daratumumab-Containing Regimens Among Patients With Multiple Myeloma Progressing on Lenalidomide Maintenance: Retrospective Analysis
Bibliographic record
Abstract
BACKGROUND: Daratumumab, a monoclonal antibody directed against CD38 is a recent class of drugs introduced into the multiple myeloma therapeutic landscape. While clinical trial data have shown a remarkable impact on outcomes, the efficacy of daratumumab combination therapies in specific clinically relevant subgroups including among patients refractory to lenalidomide maintenance remains unknown. METHODS: In this study, retrospective data were reviewed from the Canadian Myeloma Research Group and the German Munster Myeloma databases to identify patients that received daratumumab in combination with pomalidomide (DPd), lenalidomide (DRd), and bortezomib (DVd) in a population that had relapsed on lenalidomide maintenance postautologous stem cell transplant. The primary aim of the study was to look at outcomes of these patients in different daratumumab combinations. RESULTS: = 18) with DPd regimen. The median progression-free survival (PFS) of the entire cohort was 15.8 months (95% CI, 12.9-37.1 months). The median PFS of the individual regimens was as follows: DPd 18.9 months (95% CI, 13.7-not reached), DRd 21.7 months (95% CI, 11.6-not reached), and DVd 12.9 months (95% CI, 3.1-not reached). CONCLUSIONS: Daratumumab-containing therapies are effective regimens in patients progressing on lenalidomide maintenance. Additional studies are required to decide the optimal regimen post-lenalidomide maintenance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".