A large meta-analysis establishes the role of MRD negativity in long-term survival outcomes in patients with multiple myeloma
Bibliographic record
Abstract
The prognostic value of minimal residual disease (MRD) for progression-free survival (PFS) and overall survival (OS) was evaluated in a large cohort of patients with multiple myeloma (MM) using a systematic literature review and meta-analysis. Medline and EMBASE databases were searched for articles published up to 8 June 2019, with no date limit on the indexed database. Clinical end points stratified by MRD status (positive or negative) were extracted, including hazard ratios (HRs) on PFS and OS, P values, and confidence intervals (CIs). HRs were estimated based on reconstructed patient-level data from published Kaplan-Meier curves. Forty-four eligible studies with PFS data from 8098 patients, and 23 studies with OS data from 4297 patients were identified to assess the association between MRD status and survival outcomes. Compared with MRD positivity, achieving MRD negativity improved PFS (HR, 0.33; 95% CI, 0.29-0.37; P < .001) and OS (HR, 0.45; 95% CI, 0.39-0.51; P < .001). MRD negativity was associated with significantly improved survival outcomes regardless of disease setting (newly diagnosed or relapsed/refractory MM), MRD sensitivity thresholds, cytogenetic risk, method of MRD assessment, depth of clinical response at the time of MRD measurement, and MRD assessment premaintenance and 12 months after start of maintenance therapy. The strong prognostic value of MRD negativity and its association with favorable outcomes in various disease and treatment settings sets the stage to adopt MRD as a treatment end point, including development of therapeutic strategies. This large meta-analysis confirms the utility of MRD as a relevant surrogate for PFS and OS in MM.
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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".