Description Of The Hematological Toxicity Of Different Regimens Using Bortezomib In Multiple Myeloma (CyborD, Vel-Dex and VMP)
Bibliographic record
Abstract
Abstract Introduction The use of bortezomib has evolved since the APEX study published in 2005. It remains, however, the only study providing a detailed account of the changes in hematological parameters in response to bortezomib-based chemotherapy. The APEX trial enrolled multiple myeloma patients in relapse. In first-line transplant eligible multiple myeloma patients, we use bortezomib twice weekly with low-dose dexamethasone (VelDex) or bortezomib once weekly with dexamethasone and cyclophosphamide (CyBorD). For patients non-eligible to transplant, we use bortezomib once or twice weekly with melphalan and prednisone (VMP). The goal of this study is to describe changes in platelet counts during these three types of bortezomib-based induction therapys. Methods. We conducted a retrospective chart review to examine the complete blood count (CBC) results during treatment with VelDex, CyBorD or VMP. Neutrophil count, hemoglobin and platelet count were measured before every bortezomib infusion. Patients not receiving the anticipated protocol or less than 3 cycles of VelDex or CyBorD or 6 cycles of VMP were excluded from this review. Results 30 patients were included in this review (VelDex = 11, CyBorD =10, VMP = 9) Results are showed in the following graphs. The use of twice weekly bortezomib is associated with a more pronounced drop in platelets. CyborD once weekly is associated with less severe drop in platelets. Conclusion These findings show that once weekly bortezomib is associated with less severe thrombocytopenia. This suggests that the blood monitoring could be less frequent than at each dose of bortezomib. A biweekly monitoring of blood counts could reduce significantly blood tests and waiting time for patients. 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| 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".