Practical management of patients with myelofibrosis receiving ruxolitinib
Bibliographic record
Abstract
Myelofibrosis (MF) is characterized by bone marrow fibrosis, progressive anemia and extramedullary hematopoiesis, primarily manifested as splenomegaly. Patients also experience debilitating constitutional symptoms, including sequelae of splenomegaly, night sweats and fatigue. Ruxolitinib (INC424, INCB18424, Jakafi, Jakavi), a JAK1 and JAK2 inhibitor, was approved in November 2011 by the US FDA for the treatment of intermediate- or high-risk MF, and more recently in Europe and Canada for the treatment of MF-related splenomegaly or symptoms. These approvals were based on data from two randomized Phase III studies: COMFORT-I randomized against placebo, and COMFORT-II randomized against best available therapy. In these studies, ruxolitinib rapidly improved multiple disease manifestations of MF, reducing splenomegaly and improving quality of life of patients and potentially prolonging survival. However, as with other chemotherapies, ruxolitinib therapy is associated with some adverse events, such as anemia and thrombocytopenia. The aims of this article are to provide a brief overview of ruxolitinib therapy, to discuss some common adverse events associated with ruxolitinib therapy and to provide clinical management recommendations to maximize patients' benefit from ruxolitinib.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".