Elotuzumab plus lenalidomide/dexamethasone for relapsed or refractory multiple myeloma: <scp>ELOQUENT</scp>‐2 follow‐up and <i>post‐hoc</i> analyses on progression‐free survival and tumour growth
Bibliographic record
Abstract
The randomized phase III ELOQUENT-2 study (NCT01239797) evaluated the efficacy and safety of elotuzumab + lenalidomide/dexamethasone (ELd) versus lenalidomide/dexamethasone (Ld) in relapsed/refractory multiple myeloma. ELd reduced the risk of disease progression/death by 30% versus Ld (hazard ratio [HR] 0·70). Median time from diagnosis was 3·5 years. We present extended 3-year follow-up data. Endpoints included progression-free survival (PFS), overall response rate (ORR) and interim overall survival (OS). Exploratory post-hoc analyses included impact of time from diagnosis and prior lines of therapy on PFS, and serum M-protein dynamic modelling. ORR was 79% (ELd) and 66% (Ld) (P = 0·0002). ELd reduced the risk of disease progression/death by 27% versus Ld (HR 0·73; P = 0·0014). Interim OS demonstrated a trend in favour of ELd (P = 0·0257); 1-, 2- and 3-year rates with ELd versus Ld were: 91% versus 83%, 73% versus 69% and 60% versus 53%. In patients with ≥ median time from diagnosis and one prior therapy, ELd resulted in a 53% reduction in the risk of progression/death versus Ld (HR 0·47). Serum M-protein dynamic modelling showed slower tumour regrowth with ELd. Adverse events were comparable between arms. ELd provided a durable and clinically relevant improvement in efficacy, with minimal incremental toxicity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".