Evidence map›Paper›PMID 22488460›Full record

Trial reportPublic health genomics2012

Efficient identification and referral of low-income women at high risk for hereditary breast cancer: a practice-based approach.

G Joseph, C Kaplan, J Luce, R Lee, S Stewart, C Guerra, R Pasick

Erratum issuedOpen access · bronzeAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Public health genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
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

25 citing papers in PubMed, 30 citations in OpenAlex.

  1. Trial
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  4. Article
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  12. Article
  13. Racial/Ethnic Disparities in BRCA Counseling and Testing: a Narrative Review.Journal of racial and ethnic health disparities · 2019
    Review
  14. Article
  15. Factors Associated with False Positive Results on Screening Mammography in a Population of Predominantly Hispanic Women.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2018
    Article
  16. Article
  17. An Applied Framework in Support of Shared Decision Making aboutAMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

G JosephDepartments of Anthropology, History and Social Medicine, University of California-San Francisco, 1450 3rd Street, San Francisco, CA 94158, USA. gjoseph@cc.ucsf.edu
C Kaplan
J Luce
R Lee
S Stewart
C Guerra
R Pasick
Pancreatic Cancer Action Network · USUCSF Helen Diller Family Comprehensive Cancer Center · USUniversity of California, Davis · USUniversity of California, San Francisco · US

Funding

Statewide Communication to Reach Diverse Low Income WomenR01CA129096 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PASICK, RENA JOY · 2007 to 2011
$1.9M
NCI NIH HHS 1R01CA129096NCI NIH HHS R01 CA129096
6 · The paper itself

Abstract

backgroundIdentification of low-income women with the rare but serious risk of hereditary cancer and their referral to appropriate services presents an important public health challenge. We report the results of formative research to reach thousands of women for efficient identification of those at high risk and expedient access to free genetic services. External validity is maximized by emphasizing intervention fit with the two end-user organizations who must connect to make this possible. This study phase informed the design of a subsequent randomized controlled trial.

methodsWe conducted a randomized controlled pilot study (n = 38) to compare two intervention models for feasibility and impact. The main outcome was receipt of genetic counseling during a two-month intervention period. Model 1 was based on the usual outcall protocol of an academic hospital genetic risk program, and Model 2 drew on the screening and referral procedures of a statewide toll-free phone line through which large numbers of high-risk women can be identified. In Model 1, the risk program proactively calls patients to schedule genetic counseling; for Model 2, women are notified of their eligibility for counseling and make the call themselves. We also developed and pretested a family history screener for administration by phone to identify women appropriate for genetic counseling.

resultsThere was no statistically significant difference in receipt of genetic counseling between women randomized to Model 1 (3/18) compared with Model 2 (3/20) during the intervention period. However, when unresponsive women in Model 2 were called after 2 months, 7 more obtained counseling; 4 women from Model 1 were also counseled after the intervention. Thus, the intervention model that closely aligned with the risk program's outcall to high-risk women was found to be feasible and brought more low-income women to free genetic counseling. Our screener was easy to administer by phone and appeared to identify high-risk callers effectively. The model and screener are now in use in the main trial to test the effectiveness of this screening and referral intervention. A validation analysis of the screener is also underway.

conclusionIdentification of intervention strategies and tools, and their systematic comparison for impact and efficiency in the context where they will ultimately be used are critical elements of practice-based research.

Indexed as

PovertyAlgorithmsBreast NeoplasmsFemaleGenes, BRCA1Genetic CounselingGenetic Predisposition to DiseaseGenetic TestingHumansOvarian NeoplasmsPilot ProjectsReferral and ConsultationRisk

Identifiers

PMID22488460
PMCPMC3362189
OpenAlexW2004397807

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.