MétaCan
Menu
← Back to cohort

Thrombotic Complications and Risk of Myeloid Transformation in 164 Elderly Patients with Essential Thrombocythemia.

2009· article· en· W2588698611 on OpenAlexaffabout
Erica A. Peterson, Leslie Zypchen, Janet Nitta, Jonathan Berkowitz, Lynda Foltz

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineEssential thrombocythemiaMyelofibrosisThrombosisInternal medicineVenous thrombosisSurgeryMyeloid leukemiaMyeloproliferative neoplasmPolycythemia veraPediatricsBone marrow

Abstract

fetched live from OpenAlex

Abstract Abstract 2916 Poster Board II-892 Introduction: Essential thrombocythemia (ET) is a myeloproliferative neoplasm associated with increased risk of both venous and arterial thrombosis, hemorrhage and transformation to other myeloid disorders such as myelofibrosis (MF), myelodysplastic syndrome (MDS), and acute myeloid leukemia (AML). Although age greater than 60 years has been shown to be an independent risk factor for thrombosis, data regarding disease outcome and optimal therapy in the very elderly diagnosed with ET is limited. Our aim was to assess rates of thrombo-hemorrhagic complications and transformation in very elderly patients with ET at two tertiary care centers in Vancouver, British Columbia. Patients and methods: A retrospective chart review was conducted of all patients diagnosed with ET at age 60 years or older from 1982 to 2008. Data collected included baseline patient characteristics, arterial and venous thrombosis at diagnosis, cardiac risk factors, antiplatelet and cytoreductive therapy throughout the course of the disease, and thrombo-hemorrhagic complications or transformation to AML, MDS or MF during the follow-up period. The patients were separated into three age groups: 60 to 69 years, 70 to 79 years, and 80+ years. Chi-squared tests were used to compare the age groups in terms of baseline characteristics, treatment, thrombotic and hemorrhagic complications, and myeloid transformation. Kaplan-Meier curves for thrombosis and transformation-free survival were generated to follow rates of thrombosis and transformation over time. Results: We identified 164 patients diagnosed with ET at age 60 years or older, of which 68 were 60-69 years, 66 were 70-79 years and 30 patients were 80+ years. The median duration of follow-up was 2576 days for the 60-69 group, 1903 days for the 70-79 group, and 453 days for the 80+ group. The three groups were similar in baseline characteristics, including cardiac risk factors, baseline levels of haemoglobin, white blood cells and platelets, as well as the rates of thrombotic or hemorrhagic events at diagnosis. Treatment including the use of ASA (91% 60-69y, 80.3% 70-79y and 75.9% 80+y, p=0.10) and hydroxyurea therapy (67.2% 60-69y, 80.3% 70-79y and 73.3% 80+y, p=0.23) was comparable amongst the three age groups. The number of patients developing thrombotic events during follow up (30.9% 60-69y, 16.7% 70-79y and 13.3% 80+y, p=0.063) and the risk of thrombosis over time (Figure 1A) was similar across the three age groups (p=0.68). The number of patients with myeloid transformation during follow up was greater in the 60-69 age group (25% 60-69y, 9.1% 70-79y and 6.7% 80+y, p=0.013), but the risk of transformation over time was not significantly different (p=0.29) (Figure 1B). Conclusions: Age over 60 years has previously been shown to be a risk factor for thrombosis in patients with ET. The current study found no differences in the rates of thrombotic complications, nor myeloid transformation amongst three subgroups of elderly patients with ET. We also note that physicians' treatment approach does not seem to differ amongst these elderly subgroups. Although our data is limited by a small number of very elderly patients, we conclude that the disease course is not different amongst various age groups of elderly patients with ET. With currently available information, there is no reason to consider the disease differently in such patients. Disclosures: No relevant conflicts of interest to declare.

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)0.000
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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".

Quick stats

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueBlood→Same topicMyeloproliferative Neoplasms: Diagnosis and Treatment→French-language works237,207→