Pomalidomide, bortezomib, and dexamethasone for multiple myeloma previously treated with lenalidomide (OPTIMISMM): outcomes by prior treatment at first relapse
Bibliographic record
Abstract
In the phase 3 OPTIMISMM trial, pomalidomide, bortezomib, and dexamethasone (PVd) demonstrated superior efficacy vs bortezomib and dexamethasone (Vd) in patients with relapsed or refractory multiple myeloma previously treated with lenalidomide, including those refractory to lenalidomide. This analysis evaluated outcomes in patients at first relapse (N = 226) by lenalidomide-refractory status, prior bortezomib exposure, and prior stem cell transplant (SCT). Second-line PVd significantly improved PFS vs Vd in lenalidomide-refractory (17.8 vs 9.5 months; P = 0.0276) and lenalidomide-nonrefractory patients (22.0 vs 12.0 months; P = 0.0491), patients with prior bortezomib (17.8 vs 12.0 months; P = 0.0068), and patients with (22.0 vs 13.8 months; P = 0.0241) or without (16.5 vs 9.5 months; P = 0.0454) prior SCT. In patients without prior bortezomib, median PFS was 20.7 vs 9.5 months (P = 0.1055). Significant improvement in overall response rate was also observed with PVd vs Vd in lenalidomide-refractory (85.9% vs 50.8%; P < 0.001) and lenalidomide-nonrefractory (95.7% vs 60.0%; P < 0.001) patients, with similar results regardless of prior bortezomib or SCT. No new safety signals were observed. These data demonstrate the benefit of PVd at first relapse, including immediately after upfront lenalidomide treatment failure and other common first-line treatments.
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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) | 0.001 | 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 | 0.000 |
| 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".