Treatment approach and outcomes of patients with accelerated/blast-phase myeloproliferative neoplasms in the current era
Bibliographic record
Abstract
ABSTRACT: Progression of myeloproliferative neoplasms (MPNs) to accelerated or blast phase is associated with poor survival outcomes. Since 2017 there have been several therapies approved for use in acute myeloid leukemia (AML); these therapies have been incorporated into the management of accelerated/blast-phase MPNs (MPN-AP/BP). We performed a multicenter analysis to investigate outcomes of patients diagnosed with MPN-AP/BP in 2017 or later. In total, 202 patients were identified; median overall survival (OS) was 0.86 years. We also analyzed patients based on first-line treatment; the 3 most common approaches were intensive chemotherapy (n = 65), DNA methyltransferase inhibitor (DNMTi)-based regimens (n = 65), and DNMTi + venetoclax-based regimens (n = 54). Median OS was not significantly different by treatment type. In addition, we evaluated response by 2017 European LeukemiaNet AML criteria and 2012 MPN-BP criteria in an effort to understand the association of response with survival outcomes. We also analyzed outcomes in 65 patients that received allogeneic hematopoietic stem cell transplant (allo-HSCT); median OS was 2.30 years from time of allo-HSCT. Our study demonstrates that survival among patients with MPN-AP/BP is limited in the absence of allo-HSCT even in the current era of therapeutics and underscores the urgent need for new agents and approaches.
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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) | 0.000 | 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".