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Record W4405049461 · doi:10.1182/blood-2024-202565

Inflammation in Myeloproliferative Philadelphia Chromosome Negative Neoplasms - Relationship with Biomarkers of Disease Activity

2024· article· en· W4405049461 on OpenAlexaffabout
Shreyash Dalmia, Christopher Hillis, Michael Chong, Aurélien Delluc, Caroline Hamm, Sarah Karampatos, Peter A. Kavsak, Miriam Kimpton, Maha Mushtaha, Deborah Siegal, Darryl P. Leong

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsWindsor Regional HospitalOttawa HospitalUniversity of OttawaJuravinski Cancer CentrePopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsInflammationDiseasePhiladelphia chromosomeMedicinePolycythemia veraInternal medicineImmunologyPathologyOncologyGeneticsBiologyChromosomal translocation

Abstract

fetched live from OpenAlex

Introduction Myeloproliferative neoplasms (MPN) are characterized by activating somatic mutations, most commonly in the Janus kinase 2 (JAK2) gene, and are associated with increased risk of thrombosis. Inflammation, measured by biomarkers such as high sensitivity C-reactive protein (hs-CRP), may be seen in patients with MPN (Barbui et. al. Haematologica 2011). Inflammation has also been associated with cardiovascular events. In ambulatory patients with cancer, elevated cardiac troponin levels may indicate a higher risk of major adverse cardiovascular events (Kavsak et. al. JACC CardioOncology 2024). The relationship between the genetic characteristics of MPN and biochemical phenotype - specifically, markers of inflammation and cardiovascular risk - has not been well established. Objectives This study evaluated associations between JAK2 V617F variant allele frequency (VAF) and the presence of additional somatic mutations, with biomarkers of inflammation (hs-CRP) and biomarkers of cardiovascular risk including high sensitivity troponin T (hs-TnT), D-Dimer, amino-terminal pro-brain natriuretic peptide (NT-proBNP), in patients with MPN. Methods A cross-sectional study of adult patients with a diagnosis of Philadelphia chromosome negative MPN (based on 2016 World Health Organization or British Committee for Standards criteria) was conducted across three Canadian centres. Participants were prospectively enrolled from clinical lists or databases. Patient characteristics were documented. Peripheral blood study samples were collected and processed for hs-CRP, hs-TnT, NT-proBNP, D-Dimer, and JAK2 V617F VAF. A custom targeted gene sequencing panel was employed for detection of other somatic mutations and their corresponding allele frequencies, with a lower bound detection limit of 2%. Log transformation of biomarker data was conducted due to skewed distributions. Target recruitment was 100 patients. Results A total of 109 patients were recruited, of whom 62% were female. 57 patients had a diagnosis of polycythemia vera (PV), 38 patients had essential thrombocythemia (ET), and 14 had primary myelofibrosis. Mean ± standard deviation (SD) for age was 67 ± 14 years. A history of cardiovascular disease was identified in 28% of patients. JAK2 V617F (n=80) was present in 89% of PV, 58% of ET, and 50% of primary myelofibrosis cases. Somatic mutations were characterized with one mutation in 42% of patients, two in 36%, and three in 6%. 17% of patients had no recognized mutation. A sample size of 109 has 86% power to detect an R2 value of 0.08 or greater. There was no clear association between JAK2 V617F VAF and age, relative to mean cohort age (mean ± SD VAF 0.31 ± 0.30 in older patients versus 0.26 ± 0.27 in younger patients, p=0.40), nor with a history of cardiovascular disease (mean ± SD VAF 0.29 ± 0.28 with a history versus 0.28 ± 0.31 in those without, p=0.87). There was also no relationship between JAK2 V617F VAF and hs-CRP, hs-TnT, D-Dimer, or NT-proBNP concentrations. There was a trend towards higher hs-TnT levels in patients with more than one somatic mutation, compared to patients with one mutation or less (mean ± SD hs-TnT 13 ± 13ng/L versus 10 ± 7ng/L, p=0.053). These patients were also older (mean ± SD age 71 ± 9 years versus 64 ± 16 years, p=0.007). 20% of patients (n=21) were on ruxolitinib at the time of the study. Findings were consistent after excluding these participants. Conclusions Our study demonstrates no association between JAK2 V617 VAF and biomarker parameters in patients with MPN. Inflammation and cardiovascular risk in MPN may be mediated by factors beyond VAF alone. More research is needed to understand the mechanisms of increased thrombotic risk seen in patients with MPN. Additional considerations that may have influenced study findings include frequency of homozygous JAK2 V617F variants (> 50% VAF), and participant disease subtype at time of study enrolment, notably prevalence of myelofibrosis (13%, n=14). There was a trend toward higher hs-TnT levels in patients with multiple somatic mutations, as well as with advanced age. This supports the hypothesis that multiple somatic mutations comprise a biomarker phenotype associated with adverse cardiovascular outcomes in patients with MPN.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.265
Teacher spread0.248 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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