Elotuzumab, lenalidomide, and dexamethasone in RRMM: final overall survival results from the phase 3 randomized ELOQUENT-2 study
Bibliographic record
Abstract
Prolonging overall survival (OS) remains an unmet need in relapsed or refractory multiple myeloma (RRMM). In ELOQUENT-2 (NCT01239797), elotuzumab plus lenalidomide/dexamethasone (ERd) significantly improved progression-free survival (PFS) versus lenalidomide/dexamethasone (Rd) in patients with RRMM and 1-3 prior lines of therapy (LoTs). We report results from the pre-planned final OS analysis after a minimum follow-up of 70.6 months, the longest reported for an antibody-based triplet in RRMM. Overall, 646 patients with RRMM and 1-3 prior LoTs were randomized 1:1 to ERd or Rd. PFS and overall response rate were co-primary endpoints. OS was a key secondary endpoint, with the final analysis planned after 427 deaths. ERd demonstrated a statistically significant 8.7-month improvement in OS versus Rd (median, 48.3 vs 39.6 months; hazard ratio, 0.82 [95.4% Cl, 0.68-1.00]; P = 0.0408 [less than allotted α of 0.046]), which was consistently observed across key predefined subgroups. No additional safety signals with ERd at extended follow-up were reported. ERd is the first antibody-based triplet regimen shown to significantly prolong OS in patients with RRMM and 1-3 prior LoTs. The magnitude of OS benefit was greatest among patients with adverse prognostic factors, including older age, ISS stage III, IMWG high-risk disease, and 2-3 prior LoTs.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".