Evidence map›Paper›PMID 28203101›Full record

ArticlePharmacogenomics and personalized medicine2017

Prevalence of clinically actionable genotypes and medication exposure of older adults in the community.

Nilofar Daneshi, Elizabeth Holliday, Stephen Hancock, Jennifer J Schneider, Rodney J Scott, John Attia, Elizabeth A Milward

Abstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Nilofar DaneshiFaculty of Health and Medicine, School of Biomedical Sciences and Pharmacy; Faculty of Health and Medicine, Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan.
Elizabeth HollidayClinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle.
Stephen HancockClinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle.
Jennifer J SchneiderFaculty of Health and Medicine, School of Biomedical Sciences and Pharmacy; Faculty of Health and Medicine, Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan.
Rodney J ScottFaculty of Health and Medicine, School of Biomedical Sciences and Pharmacy; Faculty of Health and Medicine, Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan; Hunter Area Pathology Service, John Hunter Hospital, Newcastle, NSW, Australia.
John AttiaClinical Research Design, IT and Statistical Support Unit, Hunter Medical Research Institute; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle.
Elizabeth A MilwardFaculty of Health and Medicine, School of Biomedical Sciences and Pharmacy; Faculty of Health and Medicine, Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study analyzed clinically actionable pharmacogenotypes for clopidogrel, warfarin, statins, thiopurines, and tacrolimus using microarray data for 2121 participants (55-85 years) from the Australian Hunter Community Study (HCS). At least 74% of participants (95% confidence interval [CI]: 72%-76%) had strong level evidence for at least one medium- or high-risk actionable genotype that would trigger a change in standard therapy under current international recommendations. About 14% of these participants (95% CI: 12%-16%) were taking medication potentially affected by the genotype in question. Furthermore, ~2.6% of all participants with medication data (95% CI: 1.4%-3.8%) had a high-risk clinically actionable genotype for a medication to which they were exposed. This represents a considerable number of people at the population level. Although relationships between genotype and health outcomes remain contentious, pharmacogenotyping of multiple variants simultaneously may have considerable potential to improve medication safety and efficacy for older people in the community.

Indexed as

actionable genotypecommunityolder adultspharmacogenomicspre-emptive genotypingsingle-nucleotide polymorphism

Identifiers

PMID28203101
PMCPMC5293498

What OpenQuestion holds

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LicenceCC BY-NC
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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.