Evidence map›Paper›PMID 28661894›Full record

ArticleCancer nursing

Exploring Explanatory Models of Risk in Breast Cancer Risk Counseling Discussions: NSABP/NRG Oncology Decision-Making Project 1.

Christine M Gunn, Barbara Bokhour, Victoria A Parker, Patricia A Parker, Sarah Blakeslee, Hanna Bandos, Christine Holmberg

Abstract read
In one paragraph

Article in Cancer nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. A Validated Risk Prediction Model for Breast Cancer in US Black Women.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021
    Article
  5. Article
  6. Article
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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

7 authors at 2 institutions in 2 countries.

Christine M GunnAuthor Affiliations: Women's Health Unit, Section of General Internal Medicine, Boston University School of Medicine (Dr Gunn); Department of Health Law, Policy and Management, Boston University School of Public Health (Drs Gunn, Bokhour, and V.A. Parker), Massachusetts; Psychiatry & Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, New York (Dr P.A. Parker); NRG Oncology, and The University of Pittsburgh, Pittsburgh, Pennsylvania (Dr Bandos); and Institute of Public Health, Charité-Universitätsmedizin, Berlin, Germany (Dr Holmberg and Ms Blakeslee).
Barbara Bokhour
Victoria A Parker
Patricia A Parker
Sarah Blakeslee
Hanna Bandos
Christine Holmberg
Blakelands Hospital · GBBando Chemical Industries (Japan) · JP

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NRG Oncology Network Group Operations Center - GY9 BIQSFP Reports/BudgetsU10CA180868 · NCI · NRG ONCOLOGY FOUNDATION, INC. · PI NORMAN WOLMARK · 2014 to 2026
$206.8M
Statistics CoreU10CA180822 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI James J. Dignam · 2014 to 2026
$146.4M
NRG Oncology NCORP Research Base-BIQSFPUG1CA189867 · NCI · NRG ONCOLOGY FOUNDATION, INC. · PI Deborah Watkins Bruner, Lisa A. Kachnic · 2014 to 2026
$140.5M
Abramson Cancer Center Support GrantP30CA147859 · NCI · UNIVERSITY OF PENNSYLVANIA · PI LERMAN, CARYN · 2009 to 2010
$1.6M
NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA147859NCI NIH HHS U10 CA180822NCI NIH HHS U10 CA180868NCI NIH HHS UG1 CA189867
6 · The paper itself

Abstract

backgroundExplanatory models represent patient understanding of etiology, pathophysiology, illness, symptoms, and treatments, but little attention has been paid to how they are used by patients "at risk" for future disease.

objectiveThe aims of this study were to elucidate what constitutes an explanatory model of risk and to describe explanatory models of risk related to developing breast cancer.

methodsThirty qualitative interviews with women identified as at an increased risk for breast cancer were conducted. Interviews were coded to identify domains of explanatory models of risk using a priori codes derived from the explanatory model of illness framework. Within each domain, a grounded thematic analysis described participants' explanatory models related to breast cancer risk.

resultsThe domains of treatment and etiology remained similar in a risk context compared with illness, whereas course of illness, symptoms, and pathophysiology differed. We identified a new, integrative concept relative to other domains within explanatory models of risk: social comparisons, which was dominant in risk perhaps due to the lack of physical experiences associated with being "at risk."

conclusionsDeveloping inclusive understandings of risk and its treatment is key to developing a framework for the care of high-risk patients that is both evidence based and sensitive to patient preferences. IMPLICATIONS FOR PRACTICE: The concept of "social comparisons" can assist healthcare providers in understanding women's decision making under conditions of risk. Ensuring that healthcare providers understand patient perceptions of risk is important because it relates to patient decision making, particularly due to an increasing focus on risk assessment in cancer.

Indexed as

CounselingHealth Knowledge, Attitudes, PracticeModels, EducationalAdultBreast NeoplasmsDecision MakingFemaleHumansMiddle AgedQualitative ResearchRisk Assessment

Identifiers

PMID28661894
PMCPMC5745305
OpenAlexW2730066176

What OpenQuestion holds

Textmetadata
LicenceTDM
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.