Scannell Bryan Molly, Hu Xiaohan, Izano Monika A, Mohammed Hina, Wicks Marianna, Brown Thomas, Simon George, Kaplan Henry, Berry Anna
Syapse Holdings, Inc, West Chester, PA, United States.
Merck & Co, Inc, Rahway, NJ, United States.
JNCI Cancer Spectr. 2025 Mar 3;9(2). doi: 10.1093/jncics/pkae117.
In non-small cell lung cancer, social determinants of health (SDOH) influence treatment, but SDOH with geographic precision are infrequently used in real-world research because of privacy considerations. This research aims to characterize the influence of census tract-level SDOH on treatment for stage I and IIa non-small cell lung cancer.
Patients diagnosed between January 1, 2017, and September 30, 2022, with stage I or IIa non-small cell lung cancer in the Syapse Learning Health Network had their addresses geocoded and linked to 6 census tract-level indicators of SDOH (the Centers for Disease Control and Prevention and Agency for Toxic Substances and Disease Registry Social Vulnerability Index, percentage housing burden, percentage broadband internet access, primary care shortage area, and rurality). Clinical and demographic characteristics were ascertained from medical records. Nested multinomial logistic regression models estimated associations between SDOH and initial treatment using 2-sided Wald tests. The collective statistical significance of SDOH was assessed using a likelihood ratio test comparing nested models. Descriptive statistics described time to treatment initiation.
Among 3595 patients, 58% were initially treated with surgery, 29% with radiation, and 12% with "other." Two SDOH variables were associated with increased relative risk for radiation therapy compared with surgery: living in primary care shortage areas (relative risk = 1.61, 95% CI = 1.23 to 2.10) and living in nonmetropolitan areas (relative risk = 1.45, 95% CI = 1.02 to 2.07). The likelihood ratio test suggested that the 5 SDOH variables collectively improved the treatment model. Further, patients in areas with high Social Vulnerability Index, low internet access, and high housing burden initiated treatment later.
When using precise estimates of geospatial SDOH, these measures were associated with treatment and should be considered in analyses of cancer outcomes.
在非小细胞肺癌中，健康的社会决定因素（SDOH）会影响治疗，但出于隐私考虑，具有地理精确性的SDOH在现实世界研究中很少被使用。本研究旨在描述普查区层面的SDOH对I期和IIa期非小细胞肺癌治疗的影响。
2017年1月1日至2022年9月30日期间在Syapse学习健康网络中被诊断为I期或IIa期非小细胞肺癌的患者，其地址被地理编码，并与6个普查区层面的SDOH指标相关联（疾病控制和预防中心以及有毒物质和疾病登记局社会脆弱性指数、住房负担百分比、宽带互联网接入百分比、初级保健短缺地区和农村地区）。临床和人口统计学特征通过病历确定。嵌套多项逻辑回归模型使用双侧Wald检验估计SDOH与初始治疗之间的关联。使用比较嵌套模型的似然比检验评估SDOH的总体统计显著性。描述性统计描述了开始治疗的时间。
在3595名患者中，58%最初接受手术治疗，29%接受放疗，12%接受“其他”治疗。与手术相比，两个SDOH变量与放疗相对风险增加相关：生活在初级保健短缺地区（相对风险=1.61，95%CI=1.23至2.10）和生活在非都市地区（相对风险=1.45，95%CI=1.02至2.07）。似然比检验表明，5个SDOH变量共同改善了治疗模型。此外，社会脆弱性指数高、互联网接入率低和住房负担重地区的患者开始治疗的时间较晚。
当使用地理空间SDOH的精确估计时，这些指标与治疗相关，在癌症结局分析中应予以考虑。
