Lenalidomide (Revlimid), Bortezomib (Velcade) and Dexamethasone (RVD) for Heavily Pretreated Relapsed or Refractory Multiple Myeloma
Bibliographic record
Abstract
Abstract Abstract 5028 Lenalidomide (len) and bortezomib (btz) are active in multiple myeloma (MM). In preclinical studies, lenalidomide sensitized MM cells to bortezomib and dexamethasone (Mitsiades N, et al). The combination of lenalidomide (Revlimid), bortezomib (velcade), and dexamethasone (RVD) has shown excellent efficacy in relapsed/refractory (rel/ref) multiple myeloma (MM) patients (pts), with an overall response rate (ORR) of 84% and a partial response (PR) rate of 68%, including 21% complete/near complete responses (CR/nCR), median duration of response was 24 weeks in responding patients and median number of cycles was 6 (Anderson KC, et al. ASCO 2009: abstract 8536). The aim of this study is to assess the efficacy and toxicity profile when len is used in combination with btz and dexamethasone (dex) for pts with relapsed/refractory (rel/ref) disease outside the setting of clinical trials. Patients and Methods We retrospectively reviewed the records of all pts with rel/ref MM who were treated with RVD at Princess Margaret Hospital between March 2009 and March 2010. Eighteen pts were treated with at least 1 full cycle of RVD therapy given as len 10 mg/d on days 1–14, btz 1.0 or 1.3 mg/m2 on days 1, 4, 8, and 11 of 21-day cycles and dex (20 mg or 40 mg on days of and after btz). Pts routinely received concomitant antithrombotic and antiviral prophylaxis. Primary endpoints were response rate, time to progression (TTP) and toxicity. Responses were assessed according to modified EBMT and Uniform criteria. Toxicity was assessed using NCI-CTC, version 3.0. Results Clinical characteristics are seen in Table 1. Median age was 57 (37-71) years; 55% were female. The median number of prior therapies was 3 (2-6), and the majority of pts had already been treated with len (83%) and btz (78%) separately, and 77% had received both drugs previously but not in combination. In many instances, pts previously treated with len had len added to btz + dex at progression (n=5), or pts previously treated with btz had btz added to len + dex, at progression (n=4). After a median of 4.9 cycles (range 1–14), PR was observed in 7 (39%) and stable disease (SD) in 2 (11%) pts, for an ORR of 39%. Disease progression was seen in 14 pts at a median TTP of 4 months (1-13.6 months). Currently, 6 pts (33%) remain alive at a median F/U of 6.83 months (1.4-18.6 months). Median overall survival was 6.88 months (1-18.6 months) and six patients had a greater than 6 month response. Six pts have experienced grade 3/4 adverse events, including anemia, neutropenia, muscle weakness, hyperglycemia, and pneumonia. No deep vein thrombosis was observed. The side effect profile was manageable; importantly no patient experienced worsening of peripheral neuropathy. Conclusions The ORR for our heavily treated patient population was 39% which is lower than that reported by Anderson et al (ASCO, 2009). The median TTP was also short at 4 months. These differences can be partly explained by the fact the majority of our pts had previously received all the agents in RVD, while only 8% of the pts in the Anderson series had prior len exposure. These data suggest that the RVD combination can be effective in rel/ref MM, but responses/duration are affected by very advanced disease stage at relapse and the extent of prior treatment. Disclosures: Reece: Celgene: Honoraria, Research Funding. Chen:Celgene Corporation: Consultancy, Honoraria, Research Funding. Kukreti:Celgene: Honoraria.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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".