Social networks, social support, and survival after breast cancer diagnosis
Open accessAbstract
PURPOSE: We prospectively examined social ties and survival after breast cancer diagnosis. PATIENTS AND METHODS: Participants included 2,835 women from the Nurses' Health Study who were diagnosed with stages 1 to 4 breast cancer between 1992 and 2002. Of these women, 224 deaths (107 of these related to breast cancer) accrued to the year 2004. Social networks were assessed in 1992, 1996, and 2000 with the Berkman-Syme Social Networks Index. Social support was assessed in 1992 and 2000 as the presence and availability of a confidant. Cox proportional hazards models were used in prospective analyses of social networks and support, both before and following diagnosis, and subsequent survival. RESULTS: In multivariate-adjusted analyses, women who were socially isolated before diagnosis had a subsequent 66% increased risk of all-cause mortality (HR = 1.66; 95% CI, 1.04 to 2.65) and a two-fold increased risk of breast cancer mortality (HR = 2.14; 95% CI, 1.11 to 4.12) compared with women who were socially integrated. Women without close relatives (HR = 2.65; 95% CI, 1.03 to 6.82), friends (HR = 4.06; 95% CI, 1.40 to 11.75), or living children (HR = 5.62; 95% CI, 1.20 to 26.46) had elevated risks of breast cancer mortality and of all-cause mortality compared with those with the most social ties. Neither participation in religious or community activities nor having a confidant was related to outcomes. Effect estimates were similar in analyses of postdiagnosis networks. CONCLUSION: Socially isolated women had an elevated risk of mortality after a diagnosis of breast cancer, likely because of a lack of access to care, specifically beneficial caregiving from friends, relatives, and adult children.
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Social support is linked with higher rates of cancer survivorship.
“and social support is linked with higher rates of cancer survivorship.71”
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The Discussion reports prior studies linking greater emotional support with lower mortality among cancer patients. But this study found that social ties, not its measure of social-emotional support (having a confidant), were associated with survival after breast cancer diagnosis. The claim blurs that distinction and extends a breast-cancer finding to cancer generally. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSDoH which are less commonly targeted for extraction have been shown to impact healthcare.
“In addition to our technical innovations, our work adds to prior efforts by investigating SDoH which are less commonly targeted for extraction but nonetheless have been shown to impact healthcare43–51.”
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Background
- Authors
- Kroenke, C. H., Kubzansky, L. D., Schernhammer, E. S., Holmes, M. D., & Kawachi, I.
- Affiliations
- Brigham and Women's Hospital (US)
- Corresponding author
- Kroenke, Candyce H.
- Venue
- Journal of Clinical Oncology
- Published
- 2006-03-01
- Volume
- 24
- Issue
- 7
- Pages
- 1105-1111
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2168825005
- Cited by
- 792
- References
- 29
- Citations by year
- 2026: 30 · 2025: 36 · 2024: 25 · 2023: 85 · 2022: 41 · 2021: 61 · 2020: 37 · 2019: 48 · 2018: 39 · 2017: 39 · 2016: 48 · 2015: 37 · 2014: 49 · 2013: 52 · 2012: 31
- FWCI
- 11.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Clinical Oncology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (CA 87969)
- National Cancer Institute (CA-87969, P01CA087969)
- Topics
- Health Sciences › Medicine › Oncology › Cancer survivorship and care
- Social Sciences › Health › Health disparities and outcomes
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Keywords
- breast cancer, social networks, social support, social isolation, survival, mortality, confidants, social ties, caregiving, health care access, Nurses' Health Study
- MeSH terms
- Adult, Aged, Breast Neoplasms, Female, Humans, Middle Aged, Prospective Studies, Social Isolation, Social Support, United States, Confounding Factors, Epidemiologic, Survival Rate, Multivariate Analysis, Proportional Hazards Models, Survival Analysis, Risk Assessment, Community Networks
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