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Record W2152275695 · doi:10.1038/leu.2015.310

Efficacy of ruxolitinib on hepatomegaly in patients with myelofibrosis

2015· letter· en· W2152275695 on OpenAlexaff
Srđan Verstovšek, Ehab Atallah, John Mascarenhas, Haowei Sun, Michael T. Montgomery, Vikas Gupta, Ruben A. Mesa, Jason Gotlib

Bibliographic record

VenueLeukemia · 2015
Typeletter
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer InstituteUniversity of Texas MD Anderson Cancer CenterNational Institutes of HealthIncyte
KeywordsRuxolitinibMyelofibrosisMedicineInternal medicineHematologyOncologyIntensive care medicineBone marrow

Abstract

fetched live from OpenAlex

The Janus kinase 1/2 inhibitor ruxolitinib has been shown in a pivotal placebo-controlled phase III study (Controlled Myelofibrosis Study with Oral JAK Inhibitor Treatment I (COMFORT-I)) to significantly reduce splenomegaly and symptoms in patients with intermediate-2 or high-risk myelofibrosis (MF). Although splenomegaly is the most common manifestation of MF-associated extramedullary hematopoiesis, up to 65% of patients may also have hepatomegaly, 1 , 2 which is often highly symptomatic and can lead to serious complications. 3 Here, we present the results from a COMFORT-I post hoc analysis that assessed changes in liver volume and their relationship with concomitant changes in splenomegaly and measures of metabolic status.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations10
Published2015
Admission routes1
Has abstractyes

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