Daratumumab Plus Lenalidomide and Dexamethasone in Patients with Transplant-Ineligible Newly Diagnosed Multiple Myeloma: Maia Age Subgroup Analysis
Bibliographic record
Abstract
Introduction: Daratumumab (DARA) is a human IgGκ monoclonal antibody targeting CD38 with a direct on-tumor and immunomodulatory mechanism of action. DARA is approved in combination with standard of care in patients (pts) with newly diagnosed multiple myeloma (NDMM) and as monotherapy and in combination with standard of care for pts with relapsed/refractory multiple myeloma. In the randomized, phase 3 MAIA study (NCT02252172), DARA plus lenalidomide and dexamethasone (D-Rd) versus lenalidomide and dexamethasone (Rd) alone was evaluated in transplant-ineligible pts with NDMM. In the primary analysis of MAIA (median follow-up, 28.0 months), D-Rd significantly improved progression-free survival (PFS) versus Rd alone (Facon T, N Engl J Med 2019). Additionally, D-Rd significantly prolonged PFS versus Rd for pts aged ≥75 years (median, not reached [NR] vs 31.9 months; hazard ratio [HR], 0.63; 95% confidence interval [CI], 0.44-0.92; P = 0.0146; Usmani SZ, ASCO 2019). In an analysis of overall survival (OS; median follow-up, 56.2 months), D-Rd showed a significant reduction in the risk of death versus Rd alone (HR, 0.68; 95% CI, 0.53-0.86; P = 0.0013; Facon T, Lancet Oncol 2021). Here, we present a subgroup analysis of MAIA pts aged <75 years, <70 years, and ≥70 to <75 years. Methods: Pts with NDMM ineligible for high-dose chemotherapy with autologous stem cell transplant were randomized 1:1 to receive D-Rd or Rd alone. All pts received 28-day cycles of lenalidomide (R: 25 mg orally on Days 1-21) and dexamethasone (d: 40 mg orally on Days 1, 8, 15, and 22) with or without DARA (16 mg/kg intravenously once weekly in Cycles 1-2, once every 2 weeks in Cycles 3-6, and once every 4 weeks thereafter) until disease progression or unacceptable toxicity. The primary endpoint was PFS. Key secondary endpoints included overall response rate (ORR), OS, and minimal residual disease (MRD)-negativity rate (10-5 sensitivity, clonoSEQ® version 2.0). Results: Of 737 randomized pts (D-Rd, n = 368; Rd, n = 369), 416 (56%) pts were aged <75 years (D-Rd, n = 208; Rd, n = 208), 155 (21%) pts were aged <70 years (D-Rd, n = 78; Rd, n = 77), and 261 (35%) pts were aged ≥70 to <75 years (D-Rd, n = 130; Rd, n = 131). At a median follow-up of 64.5 months, PFS was improved for pts receiving D-Rd versus Rd who were aged <75 years (median, NR vs 37.5 months; HR, 0.52; 95% CI, 0.39-0.68; P <0.0001; Figure A), <70 years (median, NR vs 39.2 months; HR, 0.35; 95% CI, 0.21-0.56; P <0.0001), and ≥70 to <75 years (median, 61.9 vs 37.5 months; HR, 0.64; 95% CI, 0.45-0.89; P = 0.0079; Figure B). The estimated 60-month PFS rates were higher for pts receiving D-Rd versus Rd across all subgroups: <75 years (57.4% vs 33.6%), <70 years (67.2% vs 28.7%), and ≥70 to <75 years (51.6% vs 36.6%). OS was also improved for pts receiving D-Rd versus Rd who were aged <75 years (HR, 0.59; 95% CI, 0.43-0.83; P = 0.0017), <70 years (HR, 0.50; 95% CI, 0.27-0.90; P = 0.0179), and ≥70 to <75 years (HR, 0.64; 95% CI, 0.43-0.96; P = 0.0274). The estimated 60-month OS rates were higher for pts receiving D-Rd versus Rd across all subgroups: <75 years (73.9% vs 58.8%), <70 years (79.9% vs 61.7%), and ≥70 to <75 years (70.3% vs 57.0%). The ORR was higher for D-Rd versus Rd in pts aged <75 years (95.2% vs 81.7%; P <0.0001), <70 years (93.6% vs 80.5%; P = 0.0156), and ≥70 to <75 years (96.2% vs 82.4%; P = 0.0004). Increased rates of MRD negativity (10-5) were observed with D-Rd versus Rd in pts aged <75 years (36.1% vs 12.0%; odds ratio [OR], 4.13; 95% CI, 2.49-6.84; P <0.0001), <70 years (35.9% vs 11.7%; OR, 4.23; 95% CI, 1.84-9.75; P = 0.0006), and ≥70 to <75 years (36.2% vs 12.2%; OR, 4.07; 95% CI, 2.16-7.67; P <0.0001). Conclusions: At a median follow-up of 64.5 months, D-Rd improved efficacy versus Rd alone in subgroups of pts aged <75, <70, and ≥70 to <75 years. D-Rd demonstrated clinically meaningful benefit across all endpoints, including PFS, OS, ORR, and MRD negativity. These results, along with those presented previously (Usmani SZ, ASCO 2019), support the frontline use of DARA-based combination regimens in pts aged <75 years and ≥75 years with transplant-ineligible NDMM. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.013 |
| 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".