P09 DARATUMUMAB PLUS LENALIDOMIDE AND DEXAMETHASONE (D-RD) VERSUS LENALIDOMIDE AND DEXAMETHASONE (RD) ALONE IN TRANSPLANT-INELIGIBLE PATIENTS WITH NEWLY DIAGNOSED MULTIPLE MYELOMA (NDMM): UPDATED ANALYSIS OF THE PHASE 3 MAIA STUDY
Bibliographic record
Abstract
Introduction: Daratumumab is a human IgGκ monoclonal antibody that is approved as monotherapy and in combination with standard-of-care regimens for relapsed/refractory multiple myeloma and in combination with standard-of-care regimens for NDMM. In the primary analysis of the phase 3 MAIA study (median follow-up, 28.0 months), D-Rd significantly improved progression-free survival (PFS) and the minimal residual disease (MRD)–negativity rate (10–5 sensitivity) versus Rd alone in transplant-ineligible patients with NDMM. With longer follow-up (median follow-up, 56.2 months), D-Rd significantly improved overall survival (OS) versus Rd. Here, we present an analysis of MAIA after a median follow-up of 64.5 months. Patients and methods: Patients with NDMM ineligible for high-dose chemotherapy and autologous stem cell transplant were randomized 1:1 to Rd ± D. Randomization was stratified by International Staging System disease stage (I vs II vs III), region (North America vs other), and age (<75 vs ≥75 years). All patients received 28-day cycles of Rd (R: 25 mg PO on Days 121; d: 40 mg PO on Days 1, 8, 15, and 22). In the D-Rd arm, D (16 mg/kg IV) was given once weekly in Cycles 12, once every 2 weeks in Cycles 3-6, and once every 4 weeks thereafter. In both groups, patients were treated until disease progression or unacceptable toxicity. PFS was the primary endpoint; key secondary endpoints included MRDnegativity rate (10–5 sensitivity, clonoSEQ® version 2.0), overall response rate (ORR), OS, and safety. Results: A total of 737 patients were randomized (D-Rd, n=368; Rd, n=369). At a median follow-up of 64.5 months, PFS was improved with D-Rd versus Rd (median, 61.9 vs 34.4 months; hazard ratio [HR], 0.55; 95% confidence interval [CI], 0.45-0.67; P<0.0001). D-Rd reduced the risk of death by 34% versus Rd. Median OS was not reached with D-Rd versus 65.5 months with Rd (HR, 0.66; 95% CI, 0.53-0.83; P=0.0003), with estimated 60-month OS rates of 66.6% and 53.6%, respectively. ORR was higher for D-Rd versus Rd (92.9% vs 81.6%; P<0.0001), as were rates of MRD negativity (32.1% vs 11.1%; P<0.0001) and sustained MRD negativity lasting ≥12 months (18.8% vs 4.1%; P<0.0001). The most common (≥15% of patients in either arm) grade 3/4 treatment-emergent adverse events (TEAEs; D-Rd/Rd) were neutropenia (54.1%/37.0%), anemia (17.0%/21.6%), pneumonia (19.5%/10.7%), and lymphopenia (16.5%/11.2%); grade 3/4 infection rates were 42.6%/29.6%. Pneumonia was the most common serious TEAE in both groups (18.7%/10.7%). Rates of treatment discontinuation due to TEAEs were lower with D-Rd (14.6%) versus Rd (23.8%). Conclusions: In this analysis of MAIA after a median follow-up of >5 years, the addition of DARA to Rd continued to demonstrate PFS and OS benefits in transplant-ineligible patients with NDMM. D-Rd also achieved higher MRD-negativity and ≥12-month sustained MRD-negativity rates versus Rd alone. No new safety concerns were observed with longer follow-up. These results continue to support the frontline use of D-Rd in transplant-ineligible patients with NDMM. Additional OS results based on extended follow-up will be presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".