Implementing Cybord As First-Line Therapy For Transplant-Eligible Multiple Myeloma Patients : A Single-Center Preliminary Comparaison
Bibliographic record
Abstract
Abstract Introduction The best induction regimen for first-line therapy in multiple myeloma patients who are eliglible for autologous stem cell transplant (ASCT) is still unknown. In 2009, we started to use CyBorD and gradually changed our first-line therapy from Vel-Dex to CyBorD based on published work from Princess Margaret Hospital in Toronto. Here, we describe the first 10 patients to have received CyBorD and compare them to an historical cohort from the same institution. Methods We conducted a retrospective review of patient’s charts and transplant database from 2009/10/02 to 2013/04/19. We collected information on blood labs, cytogenetics, immunofixation, response rates, adverse events and graft collection. Patients not receiving the anticipated protocol or less than 3 cycles of treatment arm were excluded from this review. Results All patients (100%) in both cohorts received an ASCT (CyBorD, n=10 and Vel-Dex, n=11). The 2 groups were comparable and there was 1 patient in each arm with unfavorable cytogenetics. The response rates pre ASCT were CR = 20%, >VGPR = 90% compared to CR = 0%, >VGPR = 81,8% in CyBorD and Vel-Dex patients respectively. Response rates at 100 days post-ASCT was CR = 60%, >VGPR = 100% compared to CR = 36.4%, >VGPR = 90.9% in CyBorD and Vel-Dex patients respectively. Patients in CyBorD had a median of 1 (1-2) day for graft collection and a median number of graft cells of 5,01 x 109(2,06-6,48) compared to 1 (1-2) and 4,46 x 109 (3-6,82) in the Vel-Dex group. The rate of grade 3/4 thrombocytopenia was 0%(n=0) vs 9%(n=1) in CyborD and Vel-Dex patients respectively. No case of neuropathy grade 3 or 4 was observed in the CyBorD arm. Conclusion CyBorD is an effective and safe induction regimen for first-line therapy in ASCT eligible multiple myeloma patients. It produces less neuropathy and has an easier schedule to administer. It is now our standard protocol for these patients but dexamethasone has been reduced to once weekly for every cycle since then. NB: CyBorD (Cyclophosphamide 300 mg/m2 PO days 1,8,15,22; Bortezomib 1,5 mg/m2 SC days 1,8,15,22, Dexamethasone 20 mg PO bid days 1-4, 9-12, 17-20 for cycles 1-2, 20 mg PO bid once weekly for cycles 3-4.) Disclosures: Duquette: Janssen: Consultancy, Honoraria. Off Label Use: CyborD is a widely accepted regimen but has not been accepted by the FDA.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".