Evidence map›Paper›PMID 40053353›Full record

Trial reportJAMA network open2025

Strategies to Assess Risk for Hereditary Cancer in Primary Care Clinics: A Cluster Randomized Clinical Trial.

Elizabeth M Swisher, Heather M Harris, Sarah Knerr, Tesla N Theoryn, Barbara M Norquist, Jeannine Brant, Brian H Shirts, Faith Beers, DaLaina Cameron, Emerson J Dusic and 6 more

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04746794 (Implementing the Moon), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT04746794 nacompletednot on this map

Implementing the Moon: Getting Genomic Testing to the Public

TypeinterventionalSponsorUniversity of WashingtonRan2020 to 2023Enrolled20,184ConditionsGenetic PredispositionArmsPopulation-level screening
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Trial
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  7. Population health management of human phenotype ontology.Frontiers in artificial intelligence · 2025
    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

16 authors.

Elizabeth M SwisherDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Washington, Seattle.
Heather M HarrisDepartment of Bioethics and Humanities, School of Medicine, University of Washington, Seattle.
Sarah KnerrDepartment of Health Systems and Population Health, School of Public Health, University of Washington, Seattle.
Tesla N TheorynInstitute for Public Health Genetics, School of Public Health, University of Washington, Seattle.
Barbara M NorquistDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, University of Washington, Seattle.
Jeannine BrantCollaborative Science and Innovation, Billings Clinic, Billings, Montana.
Brian H ShirtsInstitute for Public Health Genetics, School of Public Health, University of Washington, Seattle.
Faith BeersDepartment of Bioethics and Humanities, School of Medicine, University of Washington, Seattle.
DaLaina CameronDepartment of Bioethics and Humanities, School of Medicine, University of Washington, Seattle.
Emerson J DusicDepartment of Bioethics and Humanities, School of Medicine, University of Washington, Seattle.
Laurie A RiemannCollaborative Science and Innovation, Billings Clinic, Billings, Montana.
Beth DevineThe Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle.
Michael L RaffMedical Genetics, Mary Bridge Children's, MultiCare Health System, Tacoma, Washington.
Rabindra KadelBiostatistics and Epidemiology Data Analytics Center (BEDAC), Boston University School of Public Health, Boston, Massachusetts.
Howard J CabralDepartment of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.
Catharine WangDepartment of Community Health Sciences, Boston University School of Public Health, Boston, Massachusetts.

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
NCCIH Supplement to NCATS/CTSA Program for KL2 Scholars - M. SoddersKL2TR002317 · NCATS · UNIVERSITY OF WASHINGTON · PI Christy Michelle McKinney · 2017 to 2026
$14.5M
NRSA Training CoreTL1TR002318 · NCATS · UNIVERSITY OF WASHINGTON · PI Megan Moore · 2017 to 2026
$8.4M
Implementing the moon: Getting genomic testing to the publicU01CA232795 · NCI · UNIVERSITY OF WASHINGTON · PI SWISHER, ELIZABETH MARY · 2019 to 2020
$5.8M
NCATS NIH HHS KL2 TR002317NCATS NIH HHS TL1 TR002318NCATS NIH HHS UL1 TR002319NCI NIH HHS U01 CA232795
6 · The paper itself

Abstract

Importance: Best practices for improving access to assessment of hereditary cancer risk in primary care are lacking. Objective: To compare 2 population-based engagement strategies for identifying primary care patients with a family or personal history of cancer and offering eligible individuals genetic testing for cancer susceptibility. Design, Setting, and Participants: The EDGE (Early Detection of Genetic Risk) clinical trial cluster-randomized 12 clinics from 2 health care systems in Montana, Wyoming, and Washington state to 1 of 2 engagement approaches for assessment of hereditary cancer risk in primary care. The study population included 95 623 English-speaking patients at least 25 years old with a primary care visit during the recruitment window between April 1, 2021, and March 31, 2022. Intervention: The intervention comprised 2 risk assessment engagement approaches: (1) point of care (POC), conducted by staff immediately preceding clinical appointments, and (2) direct patient engagement (DPE), where letter and email outreach facilitated at-home completion. Patients who completed risk assessment and met prespecified criteria were offered genetic testing via a home-delivered saliva testing kit at no cost. Main Outcomes and Measures: Primary outcomes were the proportion of patients with a visit who (1) completed the risk assessment and (2) completed genetic testing. Logistic regression models were used to compare the POC and DPE approaches, allowing for overdispersion and including clinic as a design factor. An intention-to-treat analysis was used to evaluate primary outcomes. Results: Over a 12-month window, 95 623 patients had a primary care visit across the 12 clinics. Those who completed the risk assessment (n = 13 705) were predominately female (64.7%) and aged between 65 and 84 years (39.6%). The POC approach resulted in a higher proportion of patients completing risk assessment than the DPE approach (19.1% vs 8.7%; adjusted odds ratio [AOR], 2.68; 95% CI, 1.72-4.17; P < .001) but a similar proportion completing testing (1.5% vs 1.6%; AOR, 0.96; 95% CI, 0.64-1.46; P = .86). Among those eligible for testing, POC test completion was approximately half of that for the DPE approach (24.7% vs 44.7%; AOR, 0.49; 95% CI, 0.37-0.64; P < .001). The proportion of tested patients identified with an actionable pathogenic variant was significantly lower for the POC approach than the DPE approach (3.8% vs 6.6%; AOR, 0.61; 95% CI, 0.44-0.85; P = .003). Conclusions and Relevance: In this cluster randomized clinical trial of risk assessment delivery, POC engagement resulted in a higher rate of assessment of hereditary cancer risk than the DPE approach but a similar rate of genetic testing completion. Using a combination of engagement strategies may be the optimal approach for greater reach and impact. Trial Registration: ClinicalTrials.gov Identifier: NCT04746794.

Indexed as

Early Detection of CancerGenetic Predisposition to DiseaseGenetic TestingNeoplasmsPrimary Health CareAdultAgedFemaleHumansMaleMiddle AgedMontanaRisk AssessmentWashington

Identifiers

PMID40053353
PMCPMC11889468

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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.