Increased risk of thrombosis with lenalidomide in combination with dexamethasone and erythropoietin
Bibliographic record
Abstract
7506 Background: Lenalidomide (Len) is a novel, orally administered, immunomodulatory drug (IMiD) that has single-agent activity against multiple myeloma (MM) and additive effects when combined with dexamethasone (Dex). At the interim analysis of MM-009/010, lenalidomide/dexamethasone achieved a significant benefit over dexamethasone, providing a longer median time to progression (TTP), higher response rates, and higher CR rates. Aim: This subgroup analysis of MM-009/010 was performed to evaluate thrombosis in patients receiving Len/Dex vs Dex. Thrombotic events included the following adverse event terms: thrombosis, deep venous thrombosis, thromboembolism, and pulmonary embolism. Methods: Patients (pts) with relapsed or refractory MM were randomized to either receive oral Len (25 mg daily for 3 weeks every 4 weeks) plus Dex (40 mg on Days 1–4, 9–12, 17–20 every 4 weeks for 4 months, then 40 mg on Days 1–4 every cycle thereafter) or placebo plus Dex. Results: Thrombotic events were reported in 39 (11.3%) of 346 pts treated with Len/Dex compared to 13 (3.8%) of 346 pts treated with Dex alone (p < 0.001). Multivariate analysis identified Len/Dex treatment and erythropoietic treatment to be independently correlated with thrombosis (Table). Older age, lower plasma cell percentage in marrow, and better ECOG performance status had a weaker association with thrombosis. Thrombosis occurred more frequently among pts with prior history of thrombosis, although that was not a significant predictor in the multivariate anlaysis. None of 23 pts who used aspirin or salicylate during the first month of treatment developed thrombosis and all events occurred in pts with rising M-paraprotein levels at baseline. Conclusions: The current study findings suggest that the administration of erythropoietic agents should be minimized in MM pts receiving Len/Dex. Prophylactic antithrombotic therapy should also be considered. [Table: see text] [Table: see text]
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".