Isatuximab plus carfilzomib and dexamethasone in patients with relapsed multiple myeloma according to prior lines of treatment and refractory status: IKEMA subgroup analysis.
Bibliographic record
Abstract
8034 Background: Patients (pts) with multiple myeloma (MM) often relapse and become refractory to successive lines of therapy, warranting better treatment options. The Phase 3 IKEMA study (NCT03275285) demonstrated that isatuximab (Isa) plus carfilzomib and dexamethasone (Kd) significantly improved progression-free survival (PFS) compared with Kd in pts with relapsed MM (RMM) (HR 0.53; 99% CI 0.32–0.89; P= 0.0007). We evaluated the efficacy and/or safety of Isa-Kd by number of prior lines of therapy (1 vs > 1) and refractoriness to lenalidomide (Len) or bortezomib (Bor). Methods: Pts were randomized (3:2) to Isa-Kd (n = 179) or Kd (n = 123). Isa (10 mg/kg IV) was given weekly for 4 weeks, then every 2 weeks. K (20 mg/m² days 1-2, then 56 mg/m²) was given twice-weekly 3 of 4 weeks, and d (20 mg) twice-weekly. The primary endpoint was PFS; key secondary endpoints were very good partial response or better (≥VGPR), minimal residual disease negativity (MRD-), and complete response (CR) rates. Results: Of the 302 randomized pts, 44.7% had 1 prior line, 55.3% had > 1 prior line, 32.8% were Len-refractory, and 30.1% were Bor-refractory. PFS was improved with Isa-Kd vs Kd in pts who received 1 prior line and > 1 prior line, as well as in pts refractory to Len, Len at last regimen, Bor, or Bor at last regimen (Table). The addition of Isa to Kd improved depth of response (≥VGPR, MRD-, and CR rates) in all subpopulations analyzed by prior treatment. Grade ≥3 treatment-emergent adverse events (TEAEs) were generally similar between the prior line subgroups (77.2% [Isa-Kd] vs 64.8% [Kd], 1 prior line; 76.5% [Isa-Kd] vs 69.1% [Kd], > 1 prior line) and the overall safety population (76.8% [Isa-Kd] vs 67.2% [Kd]). Serious AEs were 62.0% vs 48.1% in the 1 prior line subgroup, and 57.1% vs 64.7% in the > 1 prior line subgroup; TEAEs leading to discontinuations were 8.9% vs 11.1%, 1 prior line and 8.2% vs 16.2%, > 1 prior line. Conclusions: The addition of Isa to Kd improved PFS and depth of response, irrespective of prior lines of therapy or refractory status, consistent with the benefit observed in the overall IKEMA study population. Isa-Kd had a manageable safety profile regardless of number of prior lines. Isa-Kd is a potential new treatment option for pretreated pts with RMM. Clinical trial information: NCT03275285. [Table: see text]
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| 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) | 0.003 | 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".