Vieira Verónica M, Villanueva Carolina, Chang Jenny, Ziogas Argyrios, Bristow Robert E
Program in Public Health, College of Health Sciences, University of California, Irvine, CA, United States; Chao Family Comprehensive Cancer Center, University of California, Irvine, CA, United States.
Program in Public Health, College of Health Sciences, University of California, Irvine, CA, United States.
Environ Res. 2017 Jul;156:388-393. doi: 10.1016/j.envres.2017.03.057. Epub 2017 Apr 10.
Ovarian cancer survival varies geographically throughout California. The objective of this study is to determine the impact of living in disadvantaged communities on spatial patterns of survival disparities. Including a bivariate spatial smooth of geographic location within the Cox proportional hazard models is an effective approach for spatial analyses of cancer survival. Women diagnosed with advanced Stage IIIC/IV epithelial ovarian cancer (1996-2006) were identified from the California Cancer Registry. The impact of living in disadvantaged communities, as measured by the California Office of Environmental Health Hazard Assessment cumulative CalEnviroScreen 2.0 score, on geographic disparities in survival was assessed while controlling for age, tumor characteristics, quality of care, and race. Community-level air quality indicators and socioeconomic status (SES) were also independently examined in secondary analyses. The Cox proportional hazard spatial methods are available in the MapGAM package implemented in R. An increase in the community disadvantage from the 5th (less disadvantage) to the 95th percentile (more disadvantage) was significantly associated with poorer ovarian cancer survival (hazard ratio [HR], 1.16; 95% confidence interval [CI], 1.07-1.26). Ozone levels and SES were the most influential indicators on geographic disparities that warrant further investigation. The use of a bivariate smoother of location within the survival model allows for more advanced spatial analyses for exploring potential air quality-related predictors of geographic disparities.
卵巢癌患者的生存率在加利福尼亚州各地存在地域差异。本研究的目的是确定生活在弱势社区对生存差异空间模式的影响。在Cox比例风险模型中纳入地理位置的双变量空间平滑是癌症生存空间分析的有效方法。从加利福尼亚癌症登记处识别出1996 - 2006年被诊断为晚期IIIC/IV期上皮性卵巢癌的女性。在控制年龄、肿瘤特征、医疗质量和种族的同时，评估了以加利福尼亚环境卫生危害评估办公室累积CalEnviroScreen 2.0评分衡量的生活在弱势社区对生存地理差异的影响。在二次分析中还独立检查了社区层面的空气质量指标和社会经济地位（SES）。Cox比例风险空间方法可在R语言中实现的MapGAM包中使用。社区劣势从第5百分位数（劣势较小）增加到第95百分位数（劣势较大）与卵巢癌生存率较差显著相关（风险比[HR]，1.16；95%置信区间[CI]，1.07 - 1.26）。臭氧水平和SES是地理差异最有影响力的指标，值得进一步研究。在生存模型中使用位置的双变量平滑器允许进行更高级的空间分析，以探索与地理差异潜在的空气质量相关预测因素。
