Bortezomib Maintenance After Allogeneic Transplantation in Newly Diagnosed Myeloma Patients Results in Decreased Incidence and Severity of Chronic GVHD
Bibliographic record
Abstract
Allogeneic hematopoietic cell transplantation (HCT) has curative potential in myeloma but remains hampered by high rates of relapse and chronic graft-versus-host disease (GVHD). We hypothesized that bortezomib (BTZ) as maintenance therapy after allo HCT could not only decrease the incidence of relapse but also the incidence and severity of chronic GVHD. The primary endpoint of this study was to determine whether BTZ maintenance decreases the incidence and severity of chronic GVHD using National Institutes of Health (NIH) criteria. The secondary endpoints were to determine the immunosuppression burden, organ involvement and survival (overall survival, progression-free survival) in patients either receiving or not receiving BTZ. In this retrospective study, we compared the outcome of 46 myeloma patients who received BTZ after upfront tandem auto-allo HCT between 2008 and 2020 to 61 patients without maintenance. We explored the impact of BTZ maintenance on incidence and severity of chronic GVHD using the 2014 NIH criteria. At 2 years, incidences of overall (61.2% versus 83.6%; P = .001), and moderate/severe chronic GVHD (44.5% versus 77.0%; P = .001) were significantly lower in BTZ recipients who had less mouth (43% versus 67%; P = .018) and eyes (9% versus 41%; P = .001) involvement at initial diagnosis. We report a lower use of systemic steroids (45.1% versus 76.4%; P < .001), mycophenolate mofetil (15.5% versus 28.2%; P = .031) and tacrolimus (34.5% versus 70.6%; P < .001) in BTZ recipients. Probability of being alive and off systemic immunosuppressants at 3 years was 77% in BTZ recipients and 56% in controls (P = .046). To date, there is no difference in survival between both groups. In summary, BTZ maintenance improved incidence and severity of chronic GVHD and should be considered as a valid option in myeloma patients receiving upfront tandem auto-allo HCT.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".