Review Article Practical Approaches to the Use of Lenalidomide in Multiple Myeloma: A Canadian Consensus
Bibliographic record
Abstract
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In Canada, lenalidomide combined with dexamethasone (Len/Dex) is approved for use in relapsed or refractory multiple myeloma (RRMM). Our expert panel sought to provide an up-to-date practical guide on the use of lenalidomide in the managing RRMM within the Canadian clinical setting, including management of common adverse events (AEs). The panel concluded that safe, effective administration of Len/Dex treatment involves the following steps: (1) lenalidomide dose adjustment based on creatinine clearance and the extent of neutropenia or thrombocytopenia, (2) dexamethasone administered at 20–40mg/week, and (3) continuation of treatment until disease progression or until toxicity persists despite dose reduction. Based on available evidence, the following precautions should reduce the risk of common Len/Dex AEs: (1) all patients treated with Len/Dex should receive thromboprophylaxis, (2) erythropoiesis-stimulating agents (ESAs) should be used cautiously, and (3) females of child-bearing potential and males in contact with such females must use multiple contraception methods. Finally, while Len/Dex can be administered irrespective of prior therapy and in all prognostic subsets, patients with chromosomal deletion 17(p13) have
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".