Grant Details
Grant Number: |
5R03CA171771-02 Interpret this number |
Primary Investigator: |
Kroenke, Candyce |
Organization: |
Kaiser Foundation Research Institute |
Project Title: |
Social Networks & Breast Cancer Prognosis in the Chinese and Us Evaluation Study |
Fiscal Year: |
2013 |
Abstract
DESCRIPTION (provided by applicant): Each year, more than 200,000 women are diagnosed with, and nearly 40,000 die from their breast cancer (BC) but variations in treatment and tumor characteristics explain only a fraction of breast cancer deaths. It is important to determine those
factors that may help prolong survival given the aging of the population and the greater incidence of breast cancer in older women. Social networks are defined as the web of social relationships that surround an individual. Previous literature demonstrates that women with larger social networks have longer survival after a BC diagnosis, but the mechanisms through which social networks influence prognosis and in what populations are unknown. The aims of this grant are to examine associations between social network size, network members (presence of a spouse/partner, number of first-degree relatives, community participation, religious participation), and 1) major behavioral risk factors for survival including physical activity, diet, smoking, and body weight, as well as 2) breast cancer-specific mortality and all-cause mortality. We will consider the modifying influence of relationship quality, (i.e., levels of
social support and social burden) on BC outcomes. Associations will also be examined in different populations of women defined by socioeconomic status, race/ethnicity, cancer severity, and extensiveness of treatment. Aims will be addressed in a pooled analysis of 10,239 breast cancer survivors in the Chinese and US Evaluation (CAUSE) Cohort which includes women from the Life After Cancer Epidemiology (LACE), the Women's Healthy Eating and Living (WHEL) and the Shanghai Breast Cancer Cohort (SBCC) studies. Multiple linear and logistic regression will be used to evaluate associations with behavioral factors, and Cox models will be used to evaluate associations with mortality, after evaluating heterogeneity. Associations will be examined by sociodemographic factors, disease severity and treatment, and levels of social support and burden, testing for effect modification. The proposed study is the first to examine associations with lifestyle factors and weight. It is the first pooled study of social networks and
breast cancer outcomes, the largest of its kind, and represents a new generation of studies to examine in a more nuanced way how and in what populations social networks influence BC outcomes, including the possible costs and burdens, and not just benefits of social relationships. We expect that influences on behavioral factors will in part explain associations with mortality. I we demonstrate these findings, family interventions previously employed to improve lifestyle factors in persons with cardiovascular conditions might inform possible new strategies to improve health and survival in women with BC. Previous social interventions in BC survivors have largely focused on social-emotional supports, but these have failed to improve survival. It is hoped that addressing gaps in the literature will help point to potential avenues through which relationships with network members might be augmented to promote survival, or managed to mitigate costs of social relationships.
Publications
Postdiagnosis Social Networks And Breast Cancer Mortality In The After Breast Cancer Pooling Project
Authors: Kroenke C.H.
, Michael Y.L.
, Poole E.M.
, Kwan M.L.
, Nechuta S.
, Leas E.
, Caan B.J.
, Pierce J.
, Shu X.O.
, Zheng Y.
, et al.
.
Source: Cancer, 2016-12-12 00:00:00.0; , .
PMID: 27943274
Related Citations
Post-diagnosis Social Networks, And Lifestyle And Treatment Factors In The After Breast Cancer Pooling Project
Authors: Kroenke C.H.
, Michael Y.L.
, Shu X.O.
, Poole E.M.
, Kwan M.L.
, Nechuta S.
, Caan B.J.
, Pierce J.P.
, Chen W.Y.
.
Source: Psycho-oncology, 2016-01-08 00:00:00.0; , .
PMID: 26749519
Related Citations