Phase 3 ELOQUENT-2 study: Extended four year follow-up (FU) of elotuzumab plus lenalidomide/dexamethasone (ELd) vs Ld in relapsed/refractory multiple myeloma (RRMM).
Bibliographic record
Abstract
8028 Background: Elotuzumab, an immunostimulatory monoclonal antibody, has a dual mechanism of action: directly activating NK cells and tagging myeloma cells for recognition/death via antibody-dependent cell-mediated cytotoxicity. In a 3-y FU, ELOQUENT-2 (NCT01239797) showed a sustained 27% reduction in risk of disease progression/death for ELd vs Ld and OS trend in favor of ELd (Dimopoulos et al, ASH 2015). Here we present extended 4-y FU data (median FU 46 mo). Methods: RRMM patients (pts) were randomized 1:1 to ELd or Ld in 28-d cycles until disease progression/unacceptable toxicity. Coprimary endpoints: PFS, ORR. Secondary endpoint: OS. Results: Of 646 RRMM pts, 321 were randomized to ELd, 325 to Ld; ~ twice as many pts remain on therapy in ELd vs Ld (17 vs 9%) at data cut-off (Oct 18, 2016). Discontinuation was mainly due to disease progression (both arms 54%). At 4-y FU, ELd had 29% reduction in risk of progression/death vs Ld (HR 0.71, 95% CI 0.59–0.86) and relative improvement of 50% in PFS (21 vs 14%). Pts with ≥VGPR (ELd 112 [35%], Ld 95 [29%]) had greatest reduction in risk of progression/death (HR 0.65, 95% CI 0.46–0.94). ORR was 79% (ELd) vs 66% (Ld). OS will be presented. G3–4 AEs in ≥5% of pts included second primary malignancies (SPMs), vascular diseases, cardiac disorders and infections (ELd vs Ld: 9 vs 6%, 10 vs 8%, 5 vs 8%, 33 vs 26%). Overall rate (any grade) of infection and SPMs was 84 vs 75% and 17 vs 11% for ELd vs Ld. However, pts had longer exposure to ELd vs Ld (median [Q1, Q3] treatment cycles (19 [9, 42] vs 14 [6, 25]). There were fewer deaths with ELd vs Ld (165 vs 186), mainly due to disease progression and infection in both arms. Conclusions: Elotuzumab in combination with Ld consistently met its efficacy objectives at 4-y FU. ELd showed durable, clinically relevant improvement in PFS, with 29% reduction in risk of progression/death, consistent with 2-y (30%) and 3-y FU (27%). Safety, including rate of SPMs, was consistent with previous findings, with minimal incremental AEs with addition of elotuzumab to Ld. These data represent the longest median FU of an immuno-oncology agent in MM. Study funding: BMS. Writing support: C Tomas, Caudex, funded by BMS. Clinical trial information: NCT01239797.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".