ArticlePublic health genomics2021
Impact of Previous Genetic Counseling and Objective Numeracy on Accurate Interpretation of a Pharmacogenetics Test Report.
Article in Public health genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Ethical, Legal, and Social Implications of Gene-Environment Interaction Research.Genetic epidemiology · 2025Review
- Telephone versus in-person genetic counseling for hereditary cancer risk: Patient predictors of differential outcomes.Journal of telemedicine and telecare · 2024Article
- Variability in conceptualizations and measurement of genetic literacy.PEC innovation · 2023Article
- Development and Validation of the Minnesota Assessment of Pharmacogenomic Literacy (MAPL).Journal of personalized medicine · 2022Article
- A Scoping Review of Attitudes and Experiences with Pharmacogenomic Testing among Patients and the General Public: Implications for Patient Counseling.Journal of personalized medicine · 2022Article
- Moving Pharmacogenetics Into Practice: It's All About the Evidence!Clinical pharmacology and therapeutics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
introductionPharmacogenetic (PGx) testing can be useful for providing information about a patient's drug response by increasing drug efficacy and decreasing the incidence of adverse drug events. While PGx tests were previously only offered to patients under healthcare provider supervision, they are now available as direct to consumer (DTC) tests. This study aimed to assess how accurately individuals from the general population were able to interpret a sample PGx test report and if accuracy differed based on individuals' numeracy or prior genetic counseling (GC).
methodsWe surveyed 293 individuals from the general population, ascertained through ResearchMatch. The survey included questions about PGx test interpretation, numeracy, and genetic literacy.
resultsIn our cohort, numeracy level impacted PGx result interpretation, with those of high numeracy performing statistically significantly better on both the table format and graphical format (p value = 0.002 and p value <0.001, respectively) and genetic knowledge questions (p value <0.001) than those with low/average numeracy. In addition, previous GC did not impact test interpretation or genetic knowledge, but the number of individuals with prior GC was small (n = 26). DISCUSSION/
conclusionWe found that numeracy had a significant impact on correct interpretation of PGx test reports. Because many individuals in the USA have low numeracy levels, it is extremely important that patients do not make their own medication management decision based on the test results and that they consult with their physicians about their PGx testing. The importance of consultation and discussion with providers about results should be emphasized on the test report.
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Registered trials
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.