Elotuzumab Therapy for Relapsed or Refractory Multiple Myeloma
Bibliographic record
Abstract
BACKGROUND: Elotuzumab, an immunostimulatory monoclonal antibody targeting signaling lymphocytic activation molecule F7 (SLAMF7), showed activity in combination with lenalidomide and dexamethasone in a phase 1b-2 study in patients with relapsed or refractory multiple myeloma. METHODS: In this phase 3 study, we randomly assigned patients to receive either elotuzumab plus lenalidomide and dexamethasone (elotuzumab group) or lenalidomide and dexamethasone alone (control group). Coprimary end points were progression-free survival and the overall response rate. Final results for the coprimary end points are reported on the basis of a planned interim analysis of progression-free survival. RESULTS: Overall, 321 patients were assigned to the elotuzumab group and 325 to the control group. After a median follow-up of 24.5 months, the rate of progression-free survival at 1 year in the elotuzumab group was 68%, as compared with 57% in the control group; at 2 years, the rates were 41% and 27%, respectively. Median progression-free survival in the elotuzumab group was 19.4 months, versus 14.9 months in the control group (hazard ratio for progression or death in the elotuzumab group, 0.70; 95% confidence interval, 0.57 to 0.85; P<0.001). The overall response rate in the elotuzumab group was 79%, versus 66% in the control group (P<0.001). Common grade 3 or 4 adverse events in the two groups were lymphocytopenia, neutropenia, fatigue, and pneumonia. Infusion reactions occurred in 33 patients (10%) in the elotuzumab group and were grade 1 or 2 in 29 patients. CONCLUSIONS: Patients with relapsed or refractory multiple myeloma who received a combination of elotuzumab, lenalidomide, and dexamethasone had a significant relative reduction of 30% in the risk of disease progression or death. (Funded by Bristol-Myers Squibb and AbbVie Biotherapeutics; ELOQUENT-2 ClinicalTrials.gov number, 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".