Phase 3 Randomized Study of Daratumumab Monotherapy Versus Active Monitoring in Patients with High-Risk Smoldering Multiple Myeloma: Primary Results of the Aquila Study
Bibliographic record
Abstract
Introduction: High-risk smoldering multiple myeloma (SMM) is an asymptomatic precursor disorder to active multiple myeloma (MM) without approved treatment options. However, recent evidence suggests patients at high risk of progression to MM may benefit from early treatment. Daratumumab (DARA) is a human IgGκ monoclonal antibody targeting CD38 with direct on-tumor and immunomodulatory mechanisms of action. DARA is approved as monotherapy for relapsed/refractory MM (RRMM) and in combination with standard-of-care regimens for RRMM and newly diagnosed MM. Based on the encouraging activity and tolerability observed with DARA monotherapy in patients with intermediate- or high-risk SMM in the phase 2 CENTAURUS study, the phase 3 AQUILA study sought to determine if DARA could delay progression to MM versus active monitoring. Here we report the primary analysis from the AQUILA study. Methods: Eligible patients had a confirmed diagnosis of high-risk SMM for ≤5 years, defined as clonal bone marrow plasma cells (BMPCs) ≥10% and ≥1 risk factor (serum M protein ≥30 g/L, IgA SMM, immunoparesis with reduction of 2 uninvolved Ig isotypes, serum involved:uninvolved free light chain ratio ≥8 and <100, and/or clonal BMPCs >50% to <60%). Focal and lytic lesion assessment was performed in screening by CT and MRI and centrally reviewed prior to study enrollment. Patients were randomized 1:1 to receive DARA SC versus active monitoring. DARA (QW in Cycles 1 and 2, Q2W in Cycles 3-6, and Q4W thereafter) was given in 28-day cycles until cycle 39, 36 months, or disease progression, whichever came first. The primary endpoint was progression-free survival (PFS), defined as progression to active MM as assessed by an independent review committee and according to IMWG diagnostic criteria for MM (SLiM-CRAB) or death. Major secondary endpoints included overall response rate (ORR), PFS on first-line MM treatment (PFS2), and overall survival (OS). Results: A total of 390 patients (DARA, n = 194; active monitoring, n = 196) were randomized. Median (range) age (64 [31-86] years) and time from initial SMM diagnosis to randomization (0.72 [0-5.0] years) were balanced between treatment groups. Median treatment duration in the DARA group was 38 cycles (35.0 months). At a median (range) follow-up of 65.2 (0-76.6) months, PFS was significantly improved with DARA versus active monitoring (HR, 0.49; 95% CI, 0.36-0.67; P <0.0001). Median PFS was not reached in the DARA group versus 41.5 months for active monitoring; estimated 60-month PFS rates were 63.1% versus 40.8%, respectively. Prespecified analyses showed generally consistent PFS improvement with DARA versus active monitoring across subgroups. ORR was 63.4% with DARA versus 2.0% with active monitoring (P <0.0001). As of the clinical cutoff, 64 (33.0%) patients in the DARA group and 102 (52.0%) patients in the active monitoring group had started first-line MM treatment. Median time from randomization to the date of first-line MM treatment was not reached with DARA versus 50.2 months with active monitoring (HR, 0.46; 95% CI, 0.33-0.62; nominal P <0.0001). There was a positive trend in favor of DARA for PFS2 (HR, 0.58; 95% CI, 0.35-0.96) and OS (60-month OS rates: DARA, 93.0%; active monitoring, 86.9%; HR, 0.52; 95% CI, 0.27-0.98). A total of 41 deaths were observed, 15 for the DARA group and 26 for the active monitoring group. Grade 3/4 treatment-emergent adverse events (TEAEs) occurred in 40.4% and 30.1% of patients in the DARA and active monitoring groups, respectively. The most common (≥5% in either group) grade 3/4 TEAE was hypertension (DARA, 5.7%; active monitoring, 4.6%). The frequency of TEAEs leading to DARA discontinuation was low (5.7%), as was the incidence of fatal TEAEs in both groups (DARA, 1.0%; active monitoring, 2.0%). Conclusions: DARA monotherapy was well tolerated and demonstrated a clinically meaningful and significant benefit in preventing or delaying progression to active MM compared with active monitoring in patients with high-risk SMM. ORR was significantly higher and time to first-line MM treatment was prolonged with DARA compared with active monitoring. This was accompanied by positive trends for PFS2 and OS in favor of DARA. These results strongly support the benefit of early intervention with DARA monotherapy versus active monitoring, the current standard of care, in patients with high-risk SMM.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".