Cyclophosphamide–Bortezomib–Dexamethasone Compared with Bortezomib–Dexamethasone in Transplantation-Eligible Patients with Newly Diagnosed Multiple Myeloma
Bibliographic record
Abstract
Introduction: Cyclophosphamide–bortezomib–dexamethasone (CyBorD) is considered a standard induction regimen for transplant-eligible patients with newly diagnosed multiple myeloma (MM). It has not been prospectively compared with bortezomib–dexamethasone (Bor-Dex). We aimed to compare the efficacy of CyBorD and Bor-Dex induction in transplant-eligible patients. Methods: In a retrospective observational study at a single tertiary centre, all patients with transplant-eligible MM who received induction with CyBorD or Bor-Dex between March 2008 and April 2016 were enrolled. Progression-free survival (PFS), response, and stem-cell collection for a first autologous stem-cell transplantation (aHSCT) were compared. Results: Of 155 patients enrolled, 78 (50.3%) had received CyBorD, and 77 (49.7%), Bor-Dex. The patients in the Bor-Dex cohort were younger than those in the CyBorD cohort (median: 57 years vs. 62 years; p = 0.0002) and more likely to have had treatment held, reduced, or discontinued (26% vs. 14.5%, p = 0.11). The stem-cell mobilization regimen for both cohorts was predominantly cyclophosphamide and granulocyte colony–stimulating factor (GCSF). Plerixafor was used more often for the CyBorD cohort (p = 0.009), and more collection failures occurred in the CyBorD cohort (p = 0.08). In patients receiving Bor-Dex, more cells were collected (9.9 × 106 cells/kg vs. 7.7 × 106 cells/kg, p = 0.007). At day +100, a very good partial response or better was achieved in 75% of the CyBorD cohort and in 73% of the Bor-Dex cohort (p = 0.77). Median PFS was 3.2 years in the Bor-Dex cohort and 3.7 years in the CyBorD cohort (p = 0.56). Conclusions: Overall efficacy was similar in our patients receiving CyBorD and Bor-Dex. After aHSCT, no difference in depth of response or PFS was observed. Cyclophosphamide–GCSF seems to increase collection failures and hospitalizations in patients receiving CyBorD. Prospective studies are required to examine that relationship.
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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 | 0.001 |
| 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".