Evidence map›Paper›PMID 35412592›Full record

Trial reportCancer prevention research (Philadelphia, Pa.)2022

Strategies to Identify and Recruit Women at High Risk for Breast Cancer to a Randomized Controlled Trial of Web-based Decision Support Tools.

Julia E McGuinness, Gauri Bhatkhande, Jacquelyn Amenta, Thomas Silverman, Jennie Mata, Ashlee Guzman, Ting He, Jill Dimond, Tarsha Jones, Rita Kukafka and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Cancer prevention research (Philadelphia, Pa.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Temporal Ensemble Logic for Integrative Representation of the Entirety of Clinical Trials.LIPIcs : Leibniz international proceedings in informatics · 2025
    Article
  6. Observational
  7. Article
  8. User Comprehension and EHR Integration of theAMIA ... Annual Symposium proceedings. AMIA Symposium · 2024
    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

11 authors.

Julia E McGuinnessDivision of Hematology and Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York.ORCID 0000-0001-5292-1440
Gauri BhatkhandeDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.ORCID 0000-0001-7972-9598
Jacquelyn AmentaDivision of Hematology and Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York.ORCID 0000-0002-3039-1386
Thomas SilvermanDepartment of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York.
Jennie MataDivision of Hematology and Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York.
Ashlee GuzmanDivision of Hematology and Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York.
Ting HeDepartment of Biomedical Informatics and Data Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Jill DimondSassafras Tech Collective, Ann Arbor, Michigan.
Tarsha JonesChristine E Lynn College of Nursing, Florida Atlantic University, Boca Raton, Florida.
Rita KukafkaHerbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, New York.
Katherine D CrewDivision of Hematology and Oncology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University Irving Medical Center, New York, New York.ORCID 0000-0002-9637-2962

Funding

Tumor Biology and Microenvironment ProgramP30CA013696 · NCI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Anil K Rustgi · 1985 to 2026
$115.3M
Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Increasing breast cancer chemoprevention in the primary care settingR01CA177995 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CREW, KATHERINE D, KUKAFKA, RITA · 2014 to 2018
$3.5M
Multicenter trial of decision support for breast cancer chemopreventionR01CA226060 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CREW, KATHERINE D, KUKAFKA, RITA · 2019 to 2023
$3.3M
CAPRI: Columbia Cancer Training Program for Resident-InvestigatorsR38CA231577 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI CREW, KATHERINE D, SCHWARTZ, GARY K · 2018 to 2021
$1.4M
Decision Support for Multigene Panel Testing and Family Risk Communication among Racially/Ethnically Diverse Young Breast Cancer SurvivorsK01CA241393 · NCI · FLORIDA ATLANTIC UNIVERSITY · PI JONES, TARSHA · 2021 to 2025
$773k
NCATS NIH HHS UL1 TR001873NCI NIH HHS K01 CA241393NCI NIH HHS P30 CA013696NCI NIH HHS R01 CA177995NCI NIH HHS R01 CA226060NCI NIH HHS R38 CA231577
6 · The paper itself

Abstract

We evaluated strategies to identify and recruit a racially/ethnically diverse cohort of women at high-risk for breast cancer to a randomized controlled trial (RCT). We enrolled 300 high-risk women and 50 healthcare providers to a RCT of standard educational materials alone or in combination with web-based decision support tools. We implemented five strategies to identify high-risk women: (i) recruitment among patients previously enrolled in a study evaluating breast cancer risk; (ii) automated breast cancer risk calculation using information extracted from the electronic health record (EHR); (iii) identification of women with atypical hyperplasia or lobular carcinoma in situ (LCIS) using International Classification of Diseases (ICD)-9/10 diagnostic codes; (iv) clinical encounters with enrolled healthcare providers; (v) recruitment flyers/online resources. Breast cancer risk was calculated using either the Gail or Breast Cancer Surveillance Consortium (BCSC) models. We identified 6,229 high-risk women and contacted 3,459 (56%), of whom 17.2% were identified from prior study cohort, 37.5% through EHR risk information, 14.8% with atypical hyperplasia/LCIS, 29.0% by clinical encounters, and 1.5% through recruitment flyers. Women from the different recruitment sources varied by age and 5-year invasive breast cancer risk. Of 300 enrolled high-risk women, 44.7% came from clinical encounters and 27.3% from prior study cohort. Comparing enrolled with not-enrolled participants, there were significant differences in mean age (57.2 vs. 59.1 years), proportion of non-Whites (41.5% vs. 54.8%), and mean 5-year breast cancer risk (3.0% vs. 2.3%). We identified and successfully recruited diverse high-risk women from multiple sources. These strategies may be implemented in future breast cancer chemoprevention trials. PREVENTION RELEVANCE: We describe five strategies to identify and successfully recruit a large cohort of racially/ethnically diverse high-risk women from multiple sources to a randomized controlled trial evaluating interventions to increase chemoprevention uptake. Findings could inform recruitment efforts for future breast cancer prevention trials to increase recruitment yield of high-risk women.

Indexed as

Breast Carcinoma In SituBreast NeoplasmsBreastChild, PreschoolFemaleHumansHyperplasiaInternet

Identifiers

PMID35412592
PMCPMC9167698

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.