Evidence map›Paper›PMID 22481132›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2012

Patients' understanding of and responses to multiplex genetic susceptibility test results.

Kimberly A Kaphingst, Colleen M McBride, Christopher Wade, Sharon Hensley Alford, Robert Reid, Eric Larson, Andreas D Baxevanis, Lawrence C Brody

2 registry-linked trialsAbstract read
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 96 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
96citing papers in PubMed, 4 pooled it
–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.

NCT03130569 nacompletednot on this mapstarted 2015, after this paper: background citation

Personalized Genomic Testing for Skin Cancer - Maximizing Utility and Reach

TypeinterventionalSponsorUniversity of New MexicoRan2015 to 2017Enrolled600ConditionsMelanoma (Skin)ArmsWeb-based Module Group
NCT03640234 completednot on this mapstarted 2016, after this paper: background citation

Return of Actionable Variants Empirical (RAVE) Study

TypeobservationalSponsorMayo ClinicRan2016 to 2022Enrolled418ConditionsFamilial Hypercholesterolemia
3 · Its place in the literature

Who cites it

96 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  7. Predictors of genetic risk recall among the participants of a randomized controlled precision prevention trial against melanoma.Genetics in medicine : official journal of the American College of Medical Genetics · 2023
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  9. Impact of personal genomic risk information on melanoma prevention behaviors and psychological outcomes: a randomized controlled trial.Genetics in medicine : official journal of the American College of Medical Genetics · 2021
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  14. Shared decision-making following disclosure of coronary heart disease genetic risk: results from a randomized clinical trial.Journal of investigative medicine : the official publication of the American Federation for Clinical Research · 2017
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36 more citing papers are in PubMed but not listed here.

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

8 authors.

Kimberly A KaphingstDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA. kkaphingst@gwbmail.wustl.edu
Colleen M McBride
Christopher Wade
Sharon Hensley Alford
Robert Reid
Eric Larson
Andreas D Baxevanis
Lawrence C Brody

Funding

The HMO Cancer Research Network (CRN)U19CA079689 · NCI · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI WAGNER, EDWARD H · 1999 to 2011
$62.6M
The contribution folate and vitamin B12 genes to disease.ZIAHG000167 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BRODY, LAWRENCE C · 2009 to 2025
$17.6M
Multiplex InitiativeZIAHG200344 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI MC BRIDE, COLLEEN M · 2009 to 2013
$3.9M
Intramural NIH HHS ZIA HG200344NCI NIH HHS U19 CA 079689NCI NIH HHS U19 CA079689NHGRI NIH HHS HHSN268200782096C
6 · The paper itself

Abstract

purposeExamination of patients' responses to direct-to-consumer genetic susceptibility tests is needed to inform clinical practice. This study examined patients' recall and interpretation of, and responses to, genetic susceptibility test results provided directly by mail.

methodsThis observational study had three prospective assessments (before testing, 10 days after receiving results, and 3 months later). Participants were 199 patients aged 25-40 years who received free genetic susceptibility testing for eight common health conditions.

resultsMore than 80% of the patients correctly recalled their results for the eight health conditions. Patients were unlikely to interpret genetic results as deterministic of health outcomes (mean = 6.0, s.d. = 0.8 on a scale of 1-7, 1 indicating strongly deterministic). In multivariate analysis, patients with the least deterministic interpretations were white (P = 0.0098), more educated (P = 0.0093), and least confused by results (P = 0.001). Only 1% talked about their results with a provider.

conclusionFindings suggest that most patients will correctly recall their results and will not interpret genetics as the sole cause of diseases. The subset of those confused by results could benefit from consultation with a health-care provider, which could emphasize that health habits currently are the best predictors of risk. Providers could leverage patients' interest in genetic tests to encourage behavior changes to reduce disease risk.

Indexed as

ComprehensionGenetic CounselingGenetic Predisposition to DiseaseAdultFemaleGenetic TestingHealth Knowledge, Attitudes, PracticeHumansLinear ModelsMaleMental RecallMultivariate AnalysisProspective Studies

Identifiers

PMID22481132
PMCPMC3417078

What OpenQuestion holds

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Read underepoch 390

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.