PO.PS01.09 · 人群科学

HOUSES as a screening tool for cancer screening: Patient-level housing-based socioeconomic status and breast and cervical cancer screening adherence

编号 7599 展板 19 时间 4/22 09:00–12:00 区域 Section 35 主讲 Eunice Park, PhD
分会场 Risk Prediction Modeling, Screening, Early Detection, and Preneoplastic and Tumor Markers
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作者与单位

Eunice Y. Park1, Madison Beenken2, Dave Watson2, Chung Il Wi3, Tufia Haddad4, Gladys Asiedu5, Karla BALLMAN2, James R. Cerhan2, Carolyn Flock6, Brian Lynch3, Folakemi T. Odedina4, Scott H. Okuno4, Young J Juhn3

1Radiation Oncology, Mayo Clinic, Rochester, MN,2Quantitative Health Sciences, Mayo Clinic, Rochester, MN,3Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN,4Oncology, Mayo Clinic, Rochester, MN,5Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN,6Mayo Clinic Health System Research, Mayo Clinic, Rochester, MN

摘要 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.

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