Section of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.
Department of Population Health Sciences, Weill Cornell Medicine, New York, New York.
Cancer Epidemiol Biomarkers Prev. 2023 Aug 1;32(8):1120-1123. doi: 10.1158/1055-9965.EPI-23-0217.
There is growing evidence that unfavorable neighborhood contexts may influence prostate cancer progression. Whether these associations may be explained in part by differences in tumor-level somatic alterations remain unclear.
Data on tumor markers (PTEN, p53, ERG, and SPINK1) were obtained from 1,157 participants with prostate cancer in the Health Professionals Follow-up Study. Neighborhood greenness, socioeconomic status, and the income Index of Concentration at Extremes were obtained from satellite and census data and linked to participants' address at diagnosis and at study enrollment. Exposures were scaled to an interquartile range and modeled as tertiles. Bivariate associations between tertiles of neighborhood factors and tumor markers were assessed in covariate adjusted logistic regression models to estimate ORs and 95% confidence intervals.
There was no association between any of the neighborhood contextual factors and PTEN, p53, ERG, or SPINK1 in bivariate or multivariable adjusted models. Results were generally consistent when modeling exposure using exposure at diagnosis or at study enrollment.
In this multilevel study of men with prostate cancer, we found no evidence of associations between neighborhood context and tumor tissue markers.
Our results provide some of the first empirical data in support of the hypothesis that prostate cancer risk conferred by tumor tissue markers may arise independently of underlying neighborhood context. Prospective studies in more diverse populations are needed to confirm these findings.
越来越多的证据表明,不利的邻里环境可能会影响前列腺癌的进展。这些关联是否可以部分解释为肿瘤水平的体细胞改变的差异尚不清楚。
从参加健康专业人员随访研究的 1157 名前列腺癌患者中获得了肿瘤标志物(PTEN、p53、ERG 和 SPINK1)的数据。从卫星和人口普查数据中获得了邻里绿化、社会经济地位和极端收入集中指数,并将其与患者的诊断地址和研究入组地址相关联。将暴露量按四分位数间距进行缩放,并按三分位数进行建模。在协变量调整的逻辑回归模型中,评估邻里因素三分位数与肿瘤标志物之间的双变量关联,以估计 OR 和 95%置信区间。
在单变量或多变量调整模型中,没有任何邻里环境因素与 PTEN、p53、ERG 或 SPINK1 之间存在关联。在使用诊断时或研究入组时的暴露量进行建模时,结果基本一致。
在这项针对前列腺癌男性的多层次研究中,我们没有发现邻里环境与肿瘤组织标志物之间存在关联的证据。
我们的结果提供了一些支持肿瘤组织标志物所带来的前列腺癌风险可能独立于潜在邻里环境这一假设的首批经验数据。需要在更多样化的人群中进行前瞻性研究来证实这些发现。