Ruxolitinib Therapy Followed by Reduced-Intensity Conditioning for Hematopoietic Cell Transplantation for Myelofibrosis: Myeloproliferative Disorders Research Consortium 114 Study
Bibliographic record
Abstract
We evaluated the feasibility of ruxolitinib therapy followed by a reduced-intensity conditioning (RIC) regimen for patients with myelofibrosis (MF) undergoing transplantation in a 2-stage Simon phase II trial. The aims were to decrease the incidence of graft failure (GF) and nonrelapse mortality (NRM) compared with data from the previous Myeloproliferative Disorders Research Consortium 101 Study. The plan was to enroll 11 patients each in related donor (RD) and unrelated donor (URD) arms, with trial termination if ≥3 failures (GF or death by day +100 post-transplant) occurred in the RD arm or ≥6 failures occurred in the URD. A total of 21 patients were enrolled, including 7 in the RD arm and 14 in the URD arm. The RD arm did not meet the predetermined criteria for proceeding to stage II. Although the URD arm met the criteria for stage II, the study was terminated owing to poor accrual and a significant number of failures. In all 19 transplant recipients, ruxolitinib was tapered successfully without significant side effects, and 9 patients (47%) had a significant decrease in symptom burden. The cumulative incidences of GF, NRM, acute graft-versus-host disease (GVHD), and chronic GVHD at 24 months were 16%, 28%, 64%, and 76%, respectively. On an intention-to-treat basis, the 2-year overall survival was 61% for the RD arm and 70% for the URD arm. Ruxolitinib can be integrated as pretransplantation treatment for patients with MF, and a tapering strategy before transplantation is safe, allowing patients to commence conditioning therapy with a reduced symptom burden. However, GF and NRM remain significant.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".