Pomalidomide, dexamethasone, and daratumumab immediately after lenalidomide-based treatment in patients with multiple myeloma: updated efficacy, safety, and health-related quality of life results from the phase 2 MM-014 trial
Bibliographic record
Abstract
Patients with relapsed/refractory multiple myeloma (RRMM) need proven subsequent therapies after early-line lenalidomide treatment failure. The phase 2 MM-014 trial (NCT01946477) investigated pomalidomide, dexamethasone, and daratumumab after 1 to 2 prior treatment lines (62.5%, 1 prior line) in patients with RRMM and prior lenalidomide (75.0%, lenalidomide refractory). With a median follow-up of 28.4 months, overall response rate was 77.7% (52.7% achieved very good partial response or better) and median progression-free survival was 30.8 months. For patients with lenalidomide-refractory disease, these outcomes were 76.2%, 47.6%, and 23.7 months, respectively. No new safety signals were observed; 64.3% experienced grade 3/4 neutropenia. Health-related quality of life was preserved or trended toward improvement through 12 treatment cycles. Pomalidomide, dexamethasone, and daratumumab given immediately after early-line lenalidomide-based treatment continues to demonstrate safety and efficacy, supporting pomalidomide-dexamethasone as a foundation of combination therapy in RRMM and providing evidence that the immunomodulatory agent class delivers benefit after lenalidomide treatment failure.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 |
| 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".