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Record W4381855175 · doi:10.1177/20406207231177282

Treating accelerated and blast phase myeloproliferative neoplasms: progress and challenges

2023· review· en· W4381855175 on OpenAlexfundno aff
Helen Ajufo, Julian A. Waksal, John Mascarenhas, Raajit K. Rampal

Bibliographic record

VenueTherapeutic Advances in Hematology · 2023
Typereview
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsnot available
FundersSierra OncologyNational Cancer InstituteGalectoIncyteServierCelgene
KeywordsMedicineMyelofibrosisEssential thrombocythemiaPolycythemia veraBone marrowInternal medicineMyeloid leukemiaMyeloproliferative neoplasmOncologyPopulationMyeloidAcute leukemiaHaematopoiesisLeukemiaImmunologyStem cell

Abstract

fetched live from OpenAlex

Myeloproliferative neoplasms (MPNs) are a group of clonal hematologic malignancies that include polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF). MPNs are characterized by activating mutations in the JAK/STAT pathway and an increased risk of transformation to an aggressive form of acute leukemia, termed MPN-blast phase (MPN-BP). MPN-BP is characterized by the presence of ⩾20% blasts in the blood or bone marrow and is almost always preceded by an accelerated phase (MPN-AP) defined as ⩾10–19% blasts in the blood or bone marrow. These advanced forms of disease are associated with poor prognosis with a median overall survival (mOS) of 3–5 months in MPN-BP and 13 months in MPN-AP. MPN-AP/BP has a unique molecular landscape characterized by increased intratumoral complexity. Standard therapies used in de novo acute myeloid leukemia (AML) have not demonstrated improvement in OS. Allogeneic hematopoietic stem cell transplant (HSCT) remains the only curative therapy but is associated with significant morbidity and mortality and infrequently utilized in clinical practice. Therefore, an urgent unmet need persists for effective therapies in this advanced phase patient population. Here, we review the current management and future directions of therapy in MPN-AP/BP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.171
GPT teacher head0.445
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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