First Report of the Myeloma Canada Research Network (MCRN)-001 Trial Utilizing Bortezomib-Based Induction, Enhanced Conditioning with IV Busulfan + Melphalan (BuMel) and Lenalidomide Maintenance: Feasibility of a National Canadian Study Based on Achievement of Minimal Residual Disease (MRD) Negativity
Bibliographic record
Abstract
Abstract Conventional immunoglobulin (Ig) markers have been used to define multiple myeloma (MM) responses, but assessment of marrow for minimal residual disease (MRD) may provide better information on disease status/prognosis (Paiva B, et al. Blood 2008; 112: 4017). We therefore initiated a national multi-center ASCT trial with the goal of producing a high rate of MRD-negativity by using bortezomib (btz)-based induction, enhancing the conditioning regimen and utilizing post-ASCT maintenance. This phase 2 open label-trial was conducted in 10 Canadian centers. After btz-based induction (usually CyBorD) in the absence of disease progression, patients (pts) received BuMel conditioning (IV busulfan 3.2 mg/kg days -5 to -3 or days -6 to -4 + melphalan 140 mg/m2 day -2 or day -3), followed by ASCT on day 0. On day 100 post-ASCT, lenalidomide (len) 10 mg/day was commenced, escalated to 15 mg/day after 3 cycles if appropriate, and continued until disease progression. Bone marrow aspirate (BMA) samples were shipped centrally for MRD analysis by 15-color multiparameter flow cytometry (MFC) before any therapy, prior to ASCT, on day 100 post-ASCT, every 3 mos for the 1st year and every 6 mos thereafter until progression. Between 03/2013 - 07/2014, 99 newly diagnosed MM pts provided untreated BMA samples for MRD analysis. To date, 42 of a planned target of 78 pts have completed induction therapy have undergone ASCT and 39 are evaluable so far. 25 of the 99 (25%) who provided initial marrow samples did not meet criteria for enrollment: 3 (3%) had poor BMA samples; 3 (3%) did not have confirmed MM; 6 (6%) did not proceed with ASCT (1 due to progression); 1 (1%) had received dexamethasone prior to MRD analysis; 1 (1%) died during induction and 11 (11%) withdrew consent/opted for standard conditioning. Median age of the 39 evaluable pts is 53 (39-67); 64% are male. Median serum β2-microglobulin level is 3.64 mg/L (1.7-20) and albumin 37 g/L (2.8-48.1); 17 pts have ISS stage I; 9 have stage II; 9 have stage III MM and 4 have missing data. Ig subtype includes IgGκ in 16 (40%), IgGλ in 4 (10%), IgAκ in 5 (13%), IgAλ in 8 (21%), IgMλ in 1 (3%), κ in 1 (3%); non-secretory in 2 (5%) and no data in 2 pts (5%). Post-ASCT, only 4 SAEs have occurred: atrial fibrillation (2), acute kidney injury (1) and sepsis (1). There have been no ASCT-related deaths, and no pt has progressed at a median follow-up of 7.8 mos (range: 4.8-10.1). The best Ig response post-induction in the 31 pts with available restaging data is CR in 5 (16%), VGPR in 9 (29%), PR in 13 (42%), and SD in 1 (3%). 27 pts have reached day 100 post-ASCT and 8 pts have been formally evaluated. In these 8, the Ig response is CR in 2 (25%), VGPR in 5 (63%) and PR in 1 (12%). Table 1 summarizes MRD results to date. Table 1. Comparison of conventional Ig response rates and achievement of MRD negativity # Conventional Ig Responses [# MRD negative] Time point of assessment #Evaluable Total # MRD negative CR VGPR PR MR After btz-based induction 31 6 5 [3] 9 [1] 13 [2] 0 Day 100 post-ASCT 8 2 2 [2] 5[0] 1[0] 0 During len maintenance 5 1 0 5 [1] 0 0 Conclusions: 1) MFC performed on pre-therapy marrow samples to allow subsequent evaluation for MRD was successful in 97% of pts using a central lab; 2) IV BuMel was well-tolerated with few SAEs and no ASCT-related deaths; 3) MRD and conventional Ig responses may not correlate well; 4) Further F/U is required to determine the dynamics of MRD achievement and long term outcomes with this approach. Disclosures Reece: Novartis: Honoraria, Research Funding; BMS: Research Funding; Merck: Research Funding; Millennium: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Amgen: Honoraria. Off Label Use: Lenalidomide maintenance after ASCT. Venner:Celgene: Honoraria, Research Funding; Janssen: Honoraria. White:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Sebag:Novartis: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Song:Celgene: Honoraria; Otsuka: Honoraria; janssen: Honoraria. Tay:Celgene: Honoraria; Janssen: Honoraria. Kukreti:Celgene: Honoraria. Trudel:Glaxo Smith Kline: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Honoraria; Oncoethix: Research Funding. Tiedemann:Celgene: Honoraria; Janssen: Honoraria. Chen:Millennium: Research Funding; Janssen: Honoraria; Celgene: Honoraria, Research Funding.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".