CYBOR-D Induction Therapy In Clinical Practice
Bibliographic record
Abstract
Abstract Abstract 5136 Introduction: CyBorD is a highly active three-drug induction regimen for multiple myeloma (MM) patients preparing for autologous stem cell transplant (ASCT). In initial phase 2 testing, CyBorD (bortezomib 1.3mg/m2 on days 1,4,8,11, weekly cyclophosphamide 300mg/m2 orally days 1,8,15,22, and dexamethasone 40mg orally days 1–4, 9–12, and 17–20, given for four 28-day cycles) achieved an overall response rate (ORR) of 88% (≥VGPR 61%)(Reeder et al. Leukemia 2009). In an expanded cohort (30 patients) of the original phase 2 trial, a modified dosing schedule using a higher bortezomib dose of 1.5mg/m2 but given only weekly (days 1,8,15,22) and DEX 40mg dropped to once weekly (days 1,8,15,22) for cycles 3 and 4, demonstrated similar responses to the twice weekly cohort (ORR 93%, ≥VGPR 60%) with less toxicity (Reeder et al. Blood 2010). Based on these promising study results, our institution adopted the weekly CyBorD regimen as our standard induction regimen. Given that clinical trial efficacy can significantly overestimate real-life effectiveness of a treatment regimen, we reviewed our institutional clinical practice with CyBorD in a non-clinical trial setting. Methods: As a referral transplant center, Princess Margaret Hospital (PMH) performs over 100 ASCTs per year, but most patients receive their induction therapy at community institutions. From April 2007-July 2010, 55 MM patients who received CyBorD induction therapy at our institution were reviewed. Patient demographics, disease characteristics, and details of induction therapy and ASCT were obtained from retrospective chart and transplant database review. Statistical analyses of survival outcomes were performed using the Kaplan-Meier method. To obtain additional CyBorD experience from community institutions, an on-line survey of referring physicians was performed. Results: Fifty-five MM patients receiving weekly CyBorD induction in preparation for ASCT were reviewed. Median age was 58 years (range 36–71); 32 male (58%); 6 patients with high-risk FISH cytogenetics [3 with t(4;14), 3 with del17p]. MM subtypes included: IgG 40%, IgA 16%, light chains only 33%, and other 11%. A median of 4 cycles of CyBorD (range 1–10) were administered. Response rates after induction, before ASCT, were comparable to phase 2 data with an overall response of 91% (3VGPR 65%). Although responses were rapid in onset, the median number of cycles required to achieve best response was 4 (range 1–10). Dose delays or reductions of any agents were required in 10 patients (18%): 5.4% of cyclophophosphamide, 11% bortezomib, 9% dexamethasone. Grade 3–4 toxicities were reported in 13 patients (24%). Grade 3–4 neutropenia and/or thrombocytopenia were uncommon (7 and 2%, respectively) and no grade 3–4 peripheral neuropathy was seen. The median number of stem cells collected was 10.3 × 106/kg over a median of one day (range 1–5) of leukapheresis. All patients, except 4, proceeded to ASCT after CyBorD induction with a median PFS 21 months, OS not reached, at a median follow-up 31.5 mos. On-line survey responses were obtained from 20 physicians at 11 referring institutions describing their experience with CyBorD. Induction regimens used by the surveyed sites included: CyBorD 90%, biweekly bortezomib plus dexamethasone 35%, high-dose dexamethasone alone 10%, and other 5%. Weekly CyBorD was ranked highly for convenience, ease of administration and patient tolerance, but restricted bortezomib drug access was cited as the main cause for delay in initiating therapy. Conclusions: Weekly CyBorD as induction therapy prior to ASCT is highly effective in the non-clinical trial setting, with similar response and toxicity profiles to phase 2 trial data. CyBorD does not appear to impair stem cell mobilization. Given its high activity and excellent toxicity profile, CyBorD has been adopted widely in our community referral base and remains our institutional induction standard. Disclosures: Chen: Ortho: Honoraria; Millennium: Honoraria, Research Funding. Jimenez-Zepeda:Ortho: Honoraria. Reece:Bristol, Meyers, Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Johnson&Johnson: Research Funding; Merck: Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Millennium: Research Funding; Amgen: Honoraria. Trudel:Ortho: Honoraria. Kukreti:Celgene: Honoraria; Ortho Biotech: Honoraria; Roche: Honoraria.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".