Efficacy and safety of daratumumab in intermediate/high-risk smoldering multiple myeloma: final analysis of CENTAURUS
Bibliographic record
Abstract
ABSTRACT: Early intervention in smoldering multiple myeloma (SMM) may delay progression to MM. Here, we present the final analysis of the phase 2 CENTAURUS study. In total, 123 patients with intermediate/high-risk SMM were randomized to IV daratumumab 16 mg/kg after a long-intense (n = 41), intermediate (n = 41), or short-intense (n = 41) dosing schedule. At a combined median follow-up of 85.2 months, in the long-intense, intermediate, and short-intense arms complete response or better rates were 4.9%, 9.8%, and 0%; overall response rates were 58.5%, 53.7%, and 37.5%; progressive disease/death rates were 0.096, 0.102, and 0.109 (P < .0001 for all arms); and median progression-free survival was not reached, 84.4, and 74.1 months, respectively. Median overall survival was not reached in any arm. Thirty-six patients in the long-intense or intermediate arms continued daratumumab in an optional extension phase after completing 20 cycles of per-protocol treatment. The median duration of study treatment was 44.0 (range, 1.0-91.6), 35.2 (range, 1.9-90.6), and 1.6 (range, 0.1-1.9) months in the long-intense, intermediate, and short-intense arms, respectively. No new safety signals were observed. With extended follow-up (median, ∼7 years), these data highlight the tolerability of daratumumab and support ongoing trials investigating daratumumab as an early intervention for SMM. This trial was registered at www.ClinicalTrials.gov as #NCT02316106.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".