Evidence map›Paper›PMID 19752777›Full record

Trial reportPharmacogenetics and genomics2009

Genetic and environmental factors determining clinical outcomes and cost of warfarin therapy: a prospective study.

Andrea L Jorgensen, Sameh Al-Zubiedi, Jieying Eunice Zhang, Andrew Keniry, Anita Hanson, Dyfrig A Hughes, Diane van Eker, Lisa Stevens, Karen Hawkins, Cheng H Toh and 8 more

Abstract readClinical Trial
In one paragraph

Trial report in Pharmacogenetics and genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
7.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 65 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Drug Response Pharmacogenetics for 200,000 UK Biobank Participants.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Effect of Genetic Variability in theFrontiers in pharmacology · 2017
    Article
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  17. Review
  18. What is the Best Treatment for a Cancer Patient with Thrombosis?Clinical Medicine Insights. Oncology · 2014
    Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 6 institutions in 1 country.

Andrea L JorgensenDepartment of Pharmacology, Centre for Medical Statistics and Health Evaluation, The University of Liverpool, UK.
Sameh Al-Zubiedi
Jieying Eunice Zhang
Andrew Keniry
Anita Hanson
Dyfrig A Hughes
Diane van Eker
Lisa Stevens
Karen Hawkins
Cheng H Toh
Farhad Kamali
Ann K Daly
David Fitzmaurice
Alison Coffey
Paula R Williamson
Brian Kevin Park
Panos Deloukas
Munir Pirmohamed
University of Liverpool · GBWellcome Sanger Institute · GBNewcastle University · GBBangor University · GBRoyal Liverpool and Broadgreen University Hospital NHS Trust · GBUniversity of Birmingham · GB

Funding

Department of HealthWellcome Trust 077011
6 · The paper itself

Abstract

backgroundIn this prospective cohort study, we have undertaken a comprehensive evaluation of clinical parameters along with variation in 29 genes (including CYP2C9 and VKORC1) to identify factors determining interindividual variability in warfarin response.

methodsConsecutive patients (n=311) were followed up prospectively for 26 weeks. Several outcomes chosen to capture both warfarin efficacy and toxicity were assessed. Univariate and multiple regression analyses were undertaken to assess the combined effect of clinical and genetic factors.

resultsCYP2C9 was the most important gene determining initial anticoagulant control, whereas VKORC1 was more important for stable anticoagulation. Novel associations with some clinical outcomes were found with single nucleotide polymorphisms in the cytochrome 450 genes CYP2C18 and CYP2C19, which were independent of the associations observed with CYP2C9 and in genes encoding CYP3A5, protein S and clotting factor V, although the variability explained by these genes was small. On the basis of the results of microcosting, adverse events were shown to be a significant predictor of total cost.

conclusionAccurate prediction of warfarin dose requirement needs to take into account multiple genetic and environmental factors, the contributions of which vary in the induction and maintenance phases of treatment.

Indexed as

Genetic VariationAdultAgedAged, 80 and overAnticoagulantsAryl Hydrocarbon HydroxylasesCytochrome P-450 CYP2C19Cytochrome P-450 CYP2C9Cytochrome P-450 CYP3AEnvironmentFemaleGenotypeHumansMaleMiddle AgedMixed Function OxygenasesAnticoagulantsAryl Hydrocarbon HydroxylasesCYP2C18 protein, humanCYP2C19 protein, humanCYP2C9 protein, humanCYP3A5 protein, humanCytochrome P-450 CYP2C19Cytochrome P-450 CYP2C9Cytochrome P-450 CYP3AMixed Function OxygenasesVitamin K Epoxide ReductasesVKORC1 protein, humanWarfarin

Identifiers

PMID19752777
PMCPMC3330749
OpenAlexW2101384748

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.