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The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer.

Authors :
Shannon M Lynch
Elizabeth Handorf
Kristen A Sorice
Elizabeth Blackman
Lisa Bealin
Veda N Giri
Elias Obeid
Camille Ragin
Mary Daly
Source :
PLoS ONE, Vol 15, Iss 8, p e0237332 (2020)
Publication Year :
2020
Publisher :
Public Library of Science (PLoS), 2020.

Abstract

IntroductionNeighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment.Materials and methodsThe study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-valuesResultsIn combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with >3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%).DiscussionUtilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
15
Issue :
8
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.87d466559574bf0890135e9e89fabcb
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0237332