Literature DB >> 8635106

Participation in a women's breast cancer risk counseling trial. Who participates? Who declines? High Risk Breast Cancer Consortium.

B K Rimer1, J M Schildkraut, C Lerman, T H Lin, J Audrain.   

Abstract

BACKGROUND: Little is known about what factors influence women to participate its trials designed for women at high risk for breast cancer. Yet the recruitment phase is of utmost importance in determining whether the trial can achieve its goals. The purpose of this study was to examine predictors of participation in a risk counseling trial for first-degree relatives of breast cancer patients.
METHODS: Subjects were identified by their relatives who had received a diagnosis of breast cancer at one of six institutions. Letters of introduction were sent to potentially eligible, unaffected relatives. They were informed about the risk counseling study and given the opportunity to decline. Letters were sent to 1392 first-degree relatives; of these, 1149 women were contacted for an interview and 14% refused. Of the 987 respondents, 47% accepted and 53% declined to participate. Bivariate and multivariate statistics were used to examine predictors of participation.
RESULTS: In the total sample, there were five significant multivariable predictors of participation: level of education, recent clinical breast examination (CBE), objective and perceived breast cancer risk, and any current use of alcohol. Participation was moderated by time since the relative's diagnosis. There was a statistically significant relationship to education such that women with a higher level of education were significantly more likely to participate if they were approached within 2 months of their relative's diagnosis of breast cancer.
CONCLUSIONS: Like many other kinds of trials, participants in this risk counseling trial were significantly more likely to have more than a high school education and more likely to be nonsmokers than the nonparticipants. They also were significantly more likely to drink alcohol (dichotomous measure), have had a recent CBE, and have higher subjective and objective breast cancer risks. Different types of recruitment strategies may be needed depending on the characteristics of the people being recruited and the timing of the invitation.

Entities:  

Mesh:

Year:  1996        PMID: 8635106     DOI: 10.1002/(SICI)1097-0142(19960601)77:11<2348::AID-CNCR25>3.0.CO;2-W

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  22 in total

1.  Use of a patient-entered family health history tool with decision support in primary care: impact of identification of increased risk patients on genetic counseling attendance.

Authors:  Adam H Buchanan; Carol A Christianson; Tiffany Himmel; Karen P Powell; Astrid Agbaje; Geoffrey S Ginsburg; Vincent C Henrich; Lori A Orlando
Journal:  J Genet Couns       Date:  2014-08-15       Impact factor: 2.537

2.  Consent for genetics studies among clinical trial participants: findings from Action for Health in Diabetes (Look AHEAD).

Authors:  M A Espeland; K Dotson; S A Jaramillo; S E Kahn; B Harrison; M Montez; J P Foreyt; B Montgomery; W C Knowler
Journal:  Clin Trials       Date:  2006       Impact factor: 2.486

3.  The use of family history questionnaires: an examination of genetic risk estimates and genetic testing eligibility in the non-responder population.

Authors:  Susan Randall Armel; Kara Hitchman; Kathryn Millar; Laura Zahavich; Rochelle Demsky; Joan Murphy; Barry Rosen
Journal:  J Genet Couns       Date:  2011-03-30       Impact factor: 2.537

4.  Concerns about inherited risk of breast cancer prior to diagnosis in Japanese patients with breast complaints.

Authors:  Noriko Ando; Yumi Iwamitsu; Masaru Kuranami; Shigemi Okazaki; Kenji Yamamoto; Masahiko Watanabe; Hitoshi Miyaoka
Journal:  Fam Cancer       Date:  2011-12       Impact factor: 2.375

5.  Research recruitment through US central cancer registries: balancing privacy and scientific issues.

Authors:  Laura M Beskow; Robert S Sandler; Morris Weinberger
Journal:  Am J Public Health       Date:  2006-03-29       Impact factor: 9.308

6.  Sociodemographic Characteristics, Distance to the Clinic, and Breast Cancer Screening Results.

Authors:  Seijeoung Kim; Beverly Chukwudozie; Elizabeth Calhoun
Journal:  J Health Dispar Res Pract       Date:  2013

7.  Random allocation or allocation at random? Patients' perspectives of participation in a randomised controlled trial.

Authors:  K Featherstone; J L Donovan
Journal:  BMJ       Date:  1998-10-31

8.  Beliefs of women's risk as research subjects: a four-city study examining differences by sex and by race/ethnicity.

Authors:  Stefanie L Russell; Ralph V Katz; Nancy R Kressin; B Lee Green; Min Qi Wang; Cristina Claudio; Krassimira Tzvetkova
Journal:  J Womens Health (Larchmt)       Date:  2009-02       Impact factor: 2.681

9.  Predictors of decision making in families at risk for inherited breast/ovarian cancer.

Authors:  Suzanne Mellon; James Janisse; Robin Gold; Michelle Cichon; Lisa Berry-Bobovski; Michael A Tainsky; Michael S Simon
Journal:  Health Psychol       Date:  2009-01       Impact factor: 4.267

10.  Women at risk of ovarian cancer: attitudes towards and expectations of the familial ovarian cancer clinic.

Authors:  R Sheppard; A Fry; R Rush; C M Steel; A Cull
Journal:  Fam Cancer       Date:  2001       Impact factor: 2.375

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