Minimal Residual Disease Testing Infrastructure in Multiple Myeloma: Guidance for Clinical Trial and Routine Practice Use in Canada
Bibliographic record
Abstract
Measurable/minimal residual disease (MRD) is 1 of the most powerful prognostic factors for progression-free survival and overall survival in multiple myeloma (MM) and may guide therapeutic approaches. Here, we provide an overview of the current state of MRD testing in MM in Canada, highlighting its current use, approaches, and barriers. Furthermore, we discuss the available MRD assays and address questions on their appropriateness for routine practice and clinical trials. We also provide insights into timepoints for MRD testing and the relevance of achieving durable MRD negativity. The consensus recommendations herein were agreed upon by Canadian hematologists practicing at academic cancer centers and community cancer centers, clinical trial investigators, laboratory personnel, MM patients, and took into consideration the Canadian therapeutic landscape and the impact of anticipated regulatory approvals.
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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 | 0.022 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".