Management of Myelofibrosis during Treatment with Ruxolitinib: A Real-World Perspective in Case of Resistance and/or Intolerance
Bibliographic record
Abstract
The development and approval of ruxolitinib, the first JAK1/2 inhibitor indicated to treat myelofibrosis, has improved patient outcomes, with higher spleen and symptoms responses, improved quality of life, and overall survival. Despite this, several unmet needs remain, including the absence of resistance criteria, suboptimal response, the timing of allogeneic transplant, and the management of patients in case of intolerance. Here, we report the results of the second survey led by the "MPN Lab" collaboration, which aimed to report physicians' perspectives on these topics. As in our first survey, physicians were selected throughout Italy, and we included those with extensive experience in treating myeloproliferative neoplasms and those with less experience representing clinical practice in the real world. The results presented here, summarized using descriptive analyses, highlight the need for a clear definition of response to ruxolitinib as well as recommendations to guide the management of ruxolitinib under specific conditions including anemia, thrombocytopenia, infections, and non-melanoma skin cancers.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".