Evidence map›Paper›PMID 32236960›Full record

ArticleClinical pharmacology and therapeutics2020

Pharmacogenomic-Based Decision Support to Predict Adherence to Medications.

Carlton Christian, Brittany A Borden, Keith Danahey, Kiang-Teck J Yeo, Xander M R van Wijk, Mark J Ratain, Peter H O'Donnell

Abstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Review
  8. Article
  9. Moving Pharmacogenetics Into Practice: It's All About the Evidence!Clinical pharmacology and therapeutics · 2021
    Review
  10. 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.

Carlton ChristianThe University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.
Brittany A BordenThe University of Chicago Center for Personalized Therapeutics, Chicago, Illinois, USA.
Keith DanaheyThe University of Chicago Center for Personalized Therapeutics, Chicago, Illinois, USA.
Kiang-Teck J YeoThe University of Chicago Center for Personalized Therapeutics, Chicago, Illinois, USA.
Xander M R van WijkThe University of Chicago Department of Pathology, Chicago, Illinois, USA.
Mark J RatainThe University of Chicago Center for Personalized Therapeutics, Chicago, Illinois, USA.
Peter H O'DonnellThe University of Chicago Center for Personalized Therapeutics, Chicago, Illinois, USA.

Funding

Short Term Training: Health Professional StudentsT35DK062719 · NIDDK · UNIVERSITY OF CHICAGO · PI CHANG, EUGENE B · 2003 to 2017
$2.9M
The 1200 Patients Project: Studying Clinical Implementation of PharmacogenomicsK23GM100288 · NIGMS · UNIVERSITY OF CHICAGO · PI O'DONNELL, PETER HUGH · 2013 to 2016
$751k
NIDDK NIH HHS T35 DK062719NIGMS NIH HHS K23 GM100288
6 · The paper itself

Abstract

Poor adherence is associated with worse disease outcomes. Pharmacogenomics provides a possible intervention to address adherence. We hypothesized that pharmacogenomic-informed care could increase adherence. Patients in a prospective case-control study underwent preemptive pharmacogenomic genotyping with results available for provider use at the point of care; controls (not genotyped) were treated by the same providers. Over 6,000 e-prescriptions for 39 medications with actionable pharmacogenomic information were analyzed. Composite adherence, measured by modified proportion of days covered (mPDC), was compared between cases/controls and genomically concordant vs. genomically higher-risk medications. Overall, 536 patients were included. No difference in mean mPDC was observed due to availability of pharmacogenomic guidance. However, case patients prescribed high-risk pharmacogenomic medications were more than twice as likely to have low mPDC for these medications compared with genomically concordant prescriptions (odds ratio = 2.4 (1.03-5.74), P < 0.05). This study is the first to show that composite pharmacogenomic information predicts adherence.

Indexed as

Decision Support TechniquesMedication AdherencePharmacogeneticsPrecision MedicineAgedAged, 80 and overCase-Control StudiesClinical Decision-MakingDrug PrescriptionsFemaleGenotypeHumansMaleMiddle AgedPharmacogenomic VariantsProspective Studies

Identifiers

PMID32236960
PMCPMC7363565

What OpenQuestion holds

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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.