PO.PS01.09 · 人群科学
HOUSES作为癌症筛查的筛选工具:基于患者层面住房的社会经济地位与乳腺癌和宫颈癌筛查依从性
HOUSES as a screening tool for cancer screening: Patient-level housing-based socioeconomic status and breast and cervical cancer screening adherence
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摘要 Abstract
中文摘要
引言:美国国家癌症研究所估计2025年将有近317,000例新发乳腺癌和超过13,000例新发宫颈癌病例。尽管国家乳腺癌和宫颈癌早期检测项目在过去二十年中已服务了数百万女性,但癌症筛查中的不平等,及随之而来的延迟诊断以及及时和适当的治疗,在美国仍是一项公共卫生挑战。尽管健康的社会决定因素(SDOH)对癌症筛查有重大影响,但在评估乳腺癌和宫颈癌筛查依从性时,很少有研究在个体层面考虑SDOH。本研究的主要目的是探讨采用基于住房的社会经济地位(HOUSES)指数测量的个体层面SDOH,是否与乳腺癌和宫颈癌筛查不依从(未按各自的USPSTF关于年龄和频率的推荐进行)相关。
方法:在这项回顾性研究中,患者被识别为在Mayo Clinic Health System和Mayo Clinic(明尼苏达州罗切斯特)接受初级保健的人群。随后使用中西部质量指标面板评估2023年7月应接受乳腺癌或宫颈癌筛查的患者。HOUSES利用家庭住址和有关住所的公开可用数据,测量住房状况并将其归类为四分位数,通过可与电子健康记录(EHR)关联的患者层面信息获得。进行了逻辑回归分析,控制了来自区域剥夺指数的普查区块组层面的不利社会暴露组、年龄和共病。结果以比值比(OR)及相应的95%置信区间(CI)呈现。
结果:对于乳腺癌,在128,462名符合条件的患者中,20.1%(n=25,857)不依从。与最高HOUSES四分位数(Q4)相比,较低的HOUSES组显示出显著更高的不依从比值:Q3 OR=1.20(95% CI=1.15, 1.25),Q2 OR=1.45(95% CI=1.40, 1.53),Q1 OR=1.90(95% CI=1.81, 1.99)。对于宫颈癌,在175,712名符合条件的患者中,29.9%(n=52,533)不依从。与最高HOUSES四分位数(Q4)相比,较低的HOUSES组显示出显著更高的不依从比值:Q3 OR=1.07(95% CI=1.03, 1.10),Q2 OR=1.16(95% CI=1.12, 1.20),Q1 OR=1.36(95% CI=1.31, 1.41)。
结论:观察到HOUSES指数与癌症筛查依从性之间存在具有临床意义的关联。较低的HOUSES指数与乳腺癌和宫颈癌筛查更高的不依从比值相关,即使在考虑了社区层面风险、年龄和共病之后仍然如此。将HOUSES纳入EHR可成为一种实用的“筛查前筛查”工具,能够在不增加额外调查负担的情况下密切监测高风险患者。
查看英文原文 English abstract
Introduction: The National Cancer Institute estimated almost 317,000 new breast cancer and over 13,000 new cervical cancer cases in 2025. While the National Breast and Cervical Cancer Early Detection Program has served millions of women over the past two decades, inequities in cancer screening, subsequently delayed diagnosis, and timely and appropriate treatment remain a public health challenge in the United States. Despite the substantial impact of social determinants of health (SDOH) on cancer screening, few studies have accounted for SDOH at the individual level when assessing breast and cervical cancer screening adherence. The primary objective of this study is to examine whether the individual-level SDOH, measured using HOU sing-based S ocio E conomic S tatus (HOUSES) index, is associated with breast and cervical cancer screening non-adherence (not current on respective USPSTF recommendations for age and frequency).
Methods: In this retrospective study, patients were identified as those receiving primary care in the Mayo Clinic Health System and Mayo Clinic (Rochester, MN). The Midwest Quality Metrics panel was then used to assess patients due for screening for breast or cervical cancer in July 2023. The HOUSES, using home address and publicly available data on the residence which measures and categorizes housing status into quartiles, was obtained using the electronic health records (EHRs)-linkable patient-level information. Logistic regression analyses were conducted, controlling for Census block group-level adverse social exposome from the Area Deprivation Index, age, and comorbidities. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (CI).
Results: For breast cancer, among 128,462 eligible patients, 20.1% (n= 25,857) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.20 (95% CI=1.15, 1.25), Q2 OR=1.45; (95% CI=1.40, 1.53), and Q1 OR=1.90 (95% CI=1.81, 1.99). For cervical cancer, among 175,712 eligible patients, 29.9% (n=52,533) were non-adherent. Compared to the highest HOUSES quartile (Q4), lower HOUSES groups showed significantly higher odds of non-adherence: Q3 OR=1.07 (95% CI=1.03, 1.10), Q2 OR=1.16; (95% CI=1.12, 1.20), and Q1 OR=1.36 (95% CI=1.31, 1.41).
Conclusions: A clinically meaningful association between the HOUSES index and cancer screening adherence was observed. A lower HOUSES index was associated with higher odds of non-adherence for both breast and cervical cancer screening, even after accounting for neighborhood-level risk, age, and comorbidities. Incorporating HOUSES into EHRs can be a practical “screening-for-screening” tool that enables close monitoring of higher-risk patients without additional burden of surveys.
利益披露 Disclosure
E. Y. Park, None..
M. Beenken, None..
D. Watson, None..
C. Wi, None..
T. Haddad, None..
G. Asiedu, None..
K. Ballman, None..
J. R. Cerhan, None..
C. Flock, None..
B. Lynch, None..
F. T. Odedina, None..
S. H. Okuno, None..
Y. Juhn, None.