Isatuximab plus carfilzomib and dexamethasone in patients with early <i>versus</i> late relapsed multiple myeloma: IKEMA subgroup analysis
Bibliographic record
Abstract
Patients with multiple myeloma (MM) who experience early relapse within 12 months of therapy initiation are considered functional high-risk and represent an unmet need, needing better therapies to improve outcomes. The final IKEMA (clinicaltrials gov. identifier: NCT03275285) progression-free survival (PFS) analysis confirmed the significant PFS improvement reported at interim analysis with isatuximab (Isa) plus carfilzomib and dexamethasone (Kd; Isa-Kd) versus Kd in patients with relapsed MM (updated median PFS: 35.7 vs. 19.2 months; hazard ratio [HR] =0.58, 95% confidence interval [CI]: 0.42- 0.79). This IKEMA subgroup analysis examined efficacy and safety of Isa-Kd versus Kd in patients who experienced early (n=61 [Isa-Kd], n=46 [Kd]) vs. late relapse (n=104 [Isa-Kd], n=72 [Kd]). As expected, more aggressive features in baseline characteristics were observed in early relapse patients. Consistent with IKEMA overall population results, median PFS (early relapse: 24.7 vs. 17.2 months, HR=0.662, 95% CI: 0.407-1.077; late relapse: 42.7 vs. 21.9 months, HR=0.542, 95% CI: 0.355- 0.826), minimal residual disease negativity (MRD-) (early relapse: 24.6% vs. 15.2%; late relapse: 37.5% vs. 16.7%), and MRD- complete response (≥CR) rates (early relapse: 18.0% vs. 10.9%; late relapse: 30.8% vs. 13.9%) were higher with Isa-Kd versus Kd, respectively, in both early and late relapse patients. Grade ≥3, serious treatment-emergent adverse events, and death rates were higher in the late relapse Isa-Kd arm. However, the numbers of deaths were low and treatment exposure was significantly longer in Isa-Kd versus Kd late relapse patients. These results support the addition of Isa to Kd as standardof- care therapy for relapsed and/or refractory MM regardless of relapse timing.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".