Pomalidomide/Daratumumab/Dexamethasone in Relapsed or Refractory Multiple Myeloma: Final Overall Survival From MM-014
Bibliographic record
Abstract
BACKGROUND: Patients with relapsed or refractory multiple myeloma (RRMM) who have exhausted lenalidomide benefits require improved therapies. The 3-cohort phase 2 MM-014 trial (NCT01946477) explored pomalidomide in early lines of treatment for lenalidomide-exposed RRMM. In cohort B, pomalidomide plus daratumumab and dexamethasone (DPd) showed promising efficacy (median follow-up 28.4 months), as previously reported. Here, we report final overall survival (OS) in cohort B. METHODS: Patients aged ≥ 18 years were treated in 28-day cycles: pomalidomide 4 mg orally daily from days 1 to 21; daratumumab 16 mg/kg intravenously on days 1, 8, 15, and 22 (cycles 1-2), days 1 and 15 (cycles 3-6), and day 1 (cycle ≥ 7); and dexamethasone 40 mg (age ≤ 75 years) or 20 mg (age > 75 years) orally on days 1, 8, 15, and 22. The primary endpoint was ORR. OS and safety were secondary endpoints. RESULTS: Among 112 patients enrolled, 85 (75.9%) had lenalidomide-refractory disease and 27 (24.1%) had lenalidomide-relapsed disease. At a median follow-up of 41.9 months (range, 0.4-73.1), median OS was 56.7 months (95% confidence interval, 46.5-not reached). Treatment-emergent adverse events related to, and leading to discontinuation of, pomalidomide, dexamethasone, or daratumumab occurred in 7 (6.3%), 9 (8.0%), and 6 (5.4%) patients, respectively. CONCLUSION: With long-term follow-up, our results show favorable OS with DPd. The safety profile was consistent with previous reports, with no new safety signals identified. IMiD agent-based therapy can still be considered in patients with RRMM who experience progressive disease on or after lenalidomide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".