Use of empiric methods to inform prostate cancer health disparities: Comparison of neighborhood-wide association study “hits” in black and white men

Background: Black men are more likely to die of prostate cancer (PCa) compared with white men. Factors ranging from genetics to neighborhood environment contribute to these disparities. However, unlike genetics, agnostic investigations that identify candidate variables from large-scale data, and that allow for empiric investigations into differential associations between neighborhood and PCa by race/ethnicity, to the authors' knowledge have not been well explored. Thus, herein, the authors built on their previously developed, empiric neighborhood-wide association study (NWAS) in white men and conducted a NWAS in black men to determine whether findings differed by race. Methods: Pennsylvania Cancer Registry data were linked to US Census data. For the NWAS in non-Hispanic black men, the authors evaluated the association between 14,663 neighborhood census variables and advanced PCa (11 high-stage and/or high-grade cases and 8632 low-stage and/or low-grade cases), adjusting for age, diagnosis year, spatial correlation, and multiple testing. Odds ratios and 95% credible intervals were reported. Replication of NWAS findings across black and white races was assessed using Bayesian mixed effects models. Results: Five variables related to housing (3 variables), education (1 variable), and employment and/or transportation (1 variable) were found to be significantly associated with advanced PCa in black men compared with 17 socioeconomic variables (mostly related to poverty and/or income) in white men. The top hit in black men was related to crowding in renter-occupied housing (odds ratio, 1.10; 95% credible interval, 1.001-1.12). Nine of 22 NWAS hits (4 of 5 hits in black men) were replicated across racial/ethnic groups. Conclusions: Different neighborhood variables, or “candidates,” were identified across race-specific NWASs. These findings and empiric approaches warrant additional study and may inform PCa racial disparities, particularly future gene-environment studies aimed at identifying patients and/or communities at risk of advanced PCa.