Outcome of carfilzomib/pomalidomide‐based regimens after daratumumab‐based treatment in relapsed multiple myeloma: A Canadian Myeloma Research Group Database analysis
Bibliographic record
Abstract
INTRODUCTION: Although daratumumab-containing regimens improve multiple myeloma (MM) outcomes, recurrence is inevitable. METHODS AND OBJECTIVE: We performed a retrospective study using the Canadian Myeloma Research Group Database to benchmark the efficacy of carfilzomib- or pomalidomide-based therapies immediately following progression on daratumumab treatment. RESULTS: We identified 178 such patients; median number of prior lines of therapy was 3, 97% triple-class exposed, and 60% triple-class refractory. In our cohort, 75 received a subsequent carfilzomib-based therapy, 79 received a pomalidomide-based therapy, and 24 received a treatment with both immunomodulatory drug (IMiD) and proteasome inhibitor (PI) using carfilzomib and/or pomalidomide. The median progression-free survival (PFS) and overall survival (OS) for the entire cohort were 4.5 and 14.2 months, respectively. Carfilzomib-based therapy yielded a median PFS and OS of 4.5 and 10.2 months, respectively, compared to 5.2 and 21.7 months for pomalidomide-based therapy. Patients who received both IMiD and PI with carfilzomib and/or pomalidomide had a median PFS and OS of 4.1 and 14.5 months, respectively. CONCLUSION: Our observations demonstrate the poor outcome of MM patients when standard regimens based on carfilzomib and/or pomalidomide are utilized directly after daratumumab-based therapy given in the relapsed setting. Novel therapies, including immune therapies, are urgently needed to improve the outcomes of these daratumumab-exposed patients.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| 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".