Prognostic value of minimal residual disease negativity in myeloma: combined analysis of POLLUX, CASTOR, ALCYONE, and MAIA
Bibliographic record
Abstract
We explored minimal residual disease (MRD) in relapsed/refractory multiple myeloma (RRMM) and transplant-ineligible (TIE) newly diagnosed multiple myeloma (NDMM) using data from 4 phase 3 studies (POLLUX, CASTOR, ALCYONE, and MAIA). Each study previously demonstrated that daratumumab-based therapies improved MRD negativity rates and reduced the risk of disease progression or death by approximately half vs standards of care. We conducted a large-scale pooled analysis for associations between patients achieving complete response or better (≥CR) with MRD-negative status and progression-free survival (PFS). MRD was assessed via next-generation sequencing (10-5 sensitivity threshold). Patient-level data were pooled from all 4 studies and for patients with TIE NDMM and patients with RRMM who received ≤2 prior lines of therapy (≤2 PL). PFS was evaluated by response and MRD status. Median follow-up (months) was 54.8 for POLLUX, 50.2 for CASTOR, 40.1 for ALCYONE, and 36.4 for MAIA. Patients who achieved ≥CR and MRD negativity had improved PFS vs those who failed to reach CR or were MRD positive (TIE NDMM and RRMM hazard ratio [HR] 0.20, P < .0001; TIE NDMM and RRMM ≤2 PL HR 0.20, P < .0001). This benefit occurred irrespective of therapy or disease setting. A time-varying Cox proportional hazard model confirmed that ≥CR with MRD negativity was associated with improved PFS. Daratumumab-based treatment was associated with more patients reaching ≥CR and MRD negativity. These findings represent the first large-scale analysis with robust methodology to support ≥CR with MRD negativity as a prognostic factor for PFS in RRMM and TIE NDMM. These trials were registered at www.clinicaltrials.gov as #NCT02076009, #NCT02136134, #NCT02195479, and #NCT02252172.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".