Lenalidomide (Revlimid), bortezomib (Velcade) and dexamethasone for heavily pretreated relapsed or refractory multiple myeloma
Bibliographic record
Abstract
The combination of lenalidomide, bortezomib and dexamethasone (RVD) has shown excellent efficacy in patients with relapsed or refractory multiple myeloma (RRMM). The aim of our study was to assess the efficacy and toxicity profile of RVD for patients with advanced RRMM. We retrospectively reviewed the records of all patients with RRMM treated with RVD between March 2009 and December 2011. Thirty patients received ≥ 1 full cycle of RVD. Primary endpoints were overall response rate (ORR), progression-free survival (PFS) and overall survival (OS). After a median of 5 cycles (1-16), a very good partial response (VGPR) was seen in 10%, partial response (PR) in 36.7% and stable disease (SD) in 13.3% (ORR of 46.7%). Disease progression occurred in 21 patients at a median of 3 months (range 1.41-4.59). Eight patients (26%) experienced grade 3/4 adverse events, including anemia, neutropenia, muscle weakness and pneumonia. No patient experienced worsening peripheral neuropathy. Although RVD has been previously shown to be effective in RRMM, the ORR and PFS we observed were affected by very advanced disease status and heavy prior exposure to novel agents. Nevertheless, six of these patients with RRMM experienced a benefit of ≥ 6 months, suggesting synergism of this immunomodulatory derivative/proteasome inhibitor combination and/or re-establishment of drug sensitivity by an emergent myeloma clone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".