PO.PS01.05 · 人群科学
运用地理空间方法分析 2000-2019 年马里兰州社区变迁对乳腺癌死亡率的关联
Using geospatial methods to analyze associations of neighborhood change on breast cancer mortality in Maryland, 2000-2019
该海报暂无可下载的资料
AACR 官方页面
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
目的：探讨社区变迁状态（衰退、稳定或提升）是否与乳腺癌（BC）特异性死亡风险相关。
背景：社区层面的健康社会决定因素与 BC 死亡率相关，但很少有研究探讨随时间和地理动态变化的社区状况（即社区轨迹）如何调节 BC 特异性死亡风险。
方法：我们从马里兰州癌症登记处（NPCR）中识别出 2005-2019 年间在年龄 ≥18 岁女性中诊断的原发性 BC 病例，且在诊断时具有有效的人口普查区信息（作为社区的代理指标）。按普查区计算观察到的和预期的 BC 死亡数，使用 2000 年标准女性人口和 2018-2022 年马里兰州参照 BC 死亡率（年龄 <50 岁：4.4 例死亡/10 万；年龄 ≥50 岁：60.8 例死亡/10 万）。普查区与连续性校正版社会脆弱性指数（CA-SVI）相链接，该指数在各年份间对 SVI 组成变量进行了协调。社区变迁定义为连续 5 年期（2000-2004、2005-2009、2010-2014、2015-2019）之间 CA-SVI 百分位的差异。普查区被分类为稳定（低、低-中、中-高、高 CA-SVI）、提升（−25 至 −49 或 ≤−50 百分位；变得中度/显著减少劣势）或衰退（+25 至 +49 或 ≥+50 百分位；变得中度/显著增加劣势）。我们使用捕捉地理聚集和时间趋势效应的贝叶斯负二项时空模型评估社区变迁与 BC 死亡率之间的关系。模型校正了个体层面协变量（年龄、分期、分级、接受治疗情况[手术、化疗、放疗、激素治疗]和肿瘤特征[ER、PR、HER2 状态]）、起始/结束 CA-SVI 类别以及县级农村化程度（2013 年 USDA Beale 城乡连续体代码）。
结果：在 60,388 例 BC 病例中，有 8,946 例因其诊断而死亡。居住在轻度改善（+1 类）社区的女性，与居住在持续低 CA-SVI 地区者相比，BC 死亡风险略有升高（相对风险[RR]Inc=1.11，95% 可信区间[CrI]1.01-1.22）。居住在变得更加劣势社区的女性，其 BC 死亡风险升高 11% 至 24%（RR Decl1 类=1.11[1.01-1.02]，RR Decl2 类=1.24[1.04-1.48]）。
结论：持续的脆弱性和社区状况的变化均与 BC 特异性死亡相关。显著衰退显示出最高的 BC 死亡风险，但持续的脆弱性和轻度提升也表明风险升高。这些结果凸显了社区背景对癌症结局的重要性，强调了开展纵向研究以评估社区轨迹如何影响基于地区的不平等的必要性。
查看英文原文 English abstract
Purpose : To examine whether neighborhood change status (declining, stable, or upgrading) is associated with the risk of breast cancer (BC)-specific mortality.
Background : Neighborhood-level social determinants of health are associated with BC mortality, but few studies have investigated how dynamic neighborhood conditions over time and geography (i.e., neighborhood trajectories) can modulate the risk of BC-specific mortality.
Methods : We identified primary BC cases diagnosed among women age ≥18 in the Maryland Cancer Registry (NPCR) between 2005-2019 with valid census tract information at diagnosis (proxy for neighborhood). Observed and expected BC deaths were calculated by tract using 2000 standard female population and referent BC mortality rates for Maryland from 2018-2022 (age <50: 4.4 deaths/100k; age ≥50: 60.8 deaths/100k). Tracts were linked to a continuity-adjusted version of the Social Vulnerability Index (CA-SVI), which harmonized SVI component variables across years. Neighborhood change was defined as the difference in CA-SVI percentiles between consecutive 5-year periods (2000-2004, 2005-2009, 2010-2014, 2015-2019). Tracts were classified as stable (Low, Low-Medium, Medium-High, High CA-SVI)), upgrading (−25 to −49 or ≤−50 %ile; becoming moderately/substantially less disadvantaged), or declining (+25 to +49 or ≥+50 %ile; becoming moderately/substantially more disadvantaged). We evaluated the relationship between neighborhood change and BC mortality using Bayesian negative binomial space-time models that captured effects for geographic clustering and temporal trends. Models were adjusted for individual-level covariates (age, stage, grade, receipt of treatment [surgery, chemotherapy, radiation, hormone], and tumor characteristics [ER, PR, HER2 status]), starting/ending CA-SVI categories, and county-level rurality (2013 USDA Beale Rural-Urban Continuum Codes).
Results : Among 60,388 BC cases, 8,946 died as a result of their diagnosis. Women residing in neighborhoods that modestly improved (+1 cat.) had a slightly elevated risk of BC mortality compared to those living in areas of stably low CA-SVI (Relative risk [RR] Inc =1.11, 95% Credible Interval [CrI] 1.01-1.22). Women living in neighborhoods that became more disadvantaged had between 11 to 24% higher risk of BC mortality (RR Decl1 cat. =1.11 [1.01-1.02], RR Decl2 cat. =1.24 [1.04-1.48]).
Conclusion: Both sustained vulnerability and shifts in neighborhood conditions were associated with BC-specific mortality. Marked declines showed the highest risk for BC mortality, but sustained vulnerability and modest upgrades also indicated elevated risk. These results highlight the importance of neighborhood contexts on cancer outcomes, emphasizing the need for longitudinal research evaluating how neighborhood trajectories might affect place-based inequities.
利益披露 Disclosure
K. L. Ho, None..
K. I. Alcaraz, None..
M. R. Desjardins, None.