A Comparison of Cyclophosphamide, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Transplant Eligible Patients with Newly Diagnosed Multiple Myeloma
Bibliographic record
Abstract
Abstract Introduction Cyclophosphamide, bortezomib, and dexamethasone (CyBor-D) is considered a standard induction regimen for transplant eligible patients with newly diagnosed multiple myeloma (MM) based primarily on phase 2 data. It has not been directly compared to bortezomib and dexamethasone (Bor-Dex) alone. Therefore, we sought to compare the efficacy CyBor-D and Bor-Dex induction in transplant eligible patients treated at a tertiary care center. Methods A retrospective observational study was performed from a single tertiary care center between January 1, 2008 and April 30, 2016. All transplant eligible patients with MM who received induction chemotherapy with CyBor-D or Bor-Dex and were included. The primary outcome was progression free survival (PFS). Secondary outcomes were response to induction, toxicity, stem cell collection yield and failures, and response to autologous stem cell transplant (autoSCT). Continuous variables were reported as median and compared using Mann-Whitney test. Categorical variables were compared using Pearson's chi-square test. PFS was estimated with Kaplan-Meier. Results One hundred and fifty nine patients were included, 82 (51.6%) treated with CyBor-D and 77 (48.4%) treated with Bor-Dex. The relative proportion of patients treated with CyBor-D increased annually: 1/23 (4%) in 2012, 20/30 (66%) in 2013, 33/34 (97%) in 2014, and 28/28 (100%) in 2015. Patient demographics and disease characteristics were similar between all groups for sex, subtype of MM and stage by the International Staging System. The Bor-Dex group was significantly younger than the CyBor-D group (mean age 56 vs. 61 years, p < 0.001). Median number of cycles was the same for both groups (4, p= 0.73); however, the Bor-Dex group was more likely to have treatment held, reduced or discontinued than the CyBor-D group (19.7% vs. 6.4%, p=0.017). The overall response rate (ORR) was similar between both groups, 88.5% for CyBor-D and 82.7% for Bor-Dex (p=0.36), but patients treated with CyBor-D had deeper responses to induction with 57.5% achieving ≥VGPR whereas 38.7% in the Bor-Dex group achieved ≥ VGPR (p=0.02). The stem cell mobilization regimen was predominantly Cyclophosphamide and GCSF for both groups. Plerixafor use was more common in the CyBor-D cohort, 14.6% vs. 1.3% in Bor-Dex (p=0.002), and there were more collection failures in the CyBor-D group compared to Bor-Dex (6.1% vs. 0%, p=0.03). The median number of CD34 cells collected was higher in the Bor-Dex compared to CyBor-D (9.88 x 106 cells/kg vs. 7.66 x 106cells/kg, p=0.004), however median collection days was similar (1 in both groups, p=0.175). The mobilization toxicity was similar between both groups with a trend towards increased hospitalizations in the CyBor-D group (26% vs. 14%, p=0.075). The conditioning regimen was the same in both groups, predominantly Melphalan 200 mg/m2. Day 100 response was similar, with 76.7% of CyBor-D patients achieving ≥ VGPR vs. 71.21% for Bor-Dex (p= 0.25). The median PFS was 36.5 months in the Bor-Dex group and not yet reached in the CyBor-D group, due to shorter follow up time. However, the percentage of patients free from relapse was similar at 1 year (92.8% for CyBorD vs 98.7% for Bor-Dex) and at 2 years (69.4% for CyBor-D vs 72.9% for Bor-Dex). Conclusions CyBor-D and Bor-Dex appear to have similar overall efficacy for newly diagnosed transplant eligible patients with multiple myeloma in our cohort. CyBor-D was associated with deeper response to induction, but after autoSCT there was no difference in the depth of response between the two cohorts. Longer follow up is required to detect if the deeper response to induction with CyBor-D leads to differences in PFS. When used with Cyclophosphamide-GCSF mobilization, CyBor-D appears to result in more collection failures and a trend towards increased hospitalizations. Further prospective studies are required to examine this relationship. Disclosures Kew: Celgene: Honoraria. McCurdy:Celgene: 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".