Addition of Lenalidomide to Melphalan in the Treatment of Newly Diagnosed Multiple Myeloma: The National Cancer Institute of Canada Clinical Trials Group MY.11 Trial
Bibliographic record
Abstract
Oral melphalan and prednisone remain an effective and tolerable treatment for patients with multiple myeloma. For approximately 40 years, this combination has been the standard of care for patients not proceeding to stem cell transplant. Within the last 10 years, new agents have been found to be efficacious in the relapsed/refractory setting. Within the last year, two trials of added thalidomide in the newly diagnosed setting have demonstrated outcomes superior to those achieved with melphalan and prednisone alone. This improved outcome comes at the cost of increased toxicity.The National Cancer Institute of Canada Clinical Trials Group (NCIC CTG) has recently developed a randomized phase ii trial (MY.11) that uses a combination of lenalidomide with melphalan for patients with newly diagnosed multiple myeloma. Lenalidomide is a thalidomide analogue and, like thalidomide, is thought to work through immunomodulatory effects. It was shown to have activity in patients with relapsed or refractory disease and, in combination with dexamethasone, is superior to dexamethasone alone. Lenalidomide holds promise as a more effective and potentially less toxic derivative of thalidomide. Experience with lenalidomide in combination with chemotherapy is very limited, and the purpose of MY.11 is to establish tolerability and to gain knowledge about efficacy. The information gained from MY.11 is expected to help inform dosing levels and schedules for a large phase iii trial being developed by the Eastern Cooperative Oncology Group that will include participation by the NCIC CTG.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".