Social Determinants of Health and Variability in Treatment for Patients with Early-stage Non-small Cell Lung Cancer

Overview

Journal JNCI Cancer Spectr

Publisher Oxford University Press

Specialty Oncology

Date 2024 Nov 25

PMID 39585653

Authors

Molly Scannell Bryan

Xiaohan Hu

Monika A Izano

Hina Mohammed

Marianna Wicks

Thomas Brown

George Simon

Henry Kaplan

Anna Berry

Affiliations

Soon will be listed here.

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusion: When using precise estimates of geospatial SDOH, these measures were associated with treatment and should be considered in analyses of cancer outcomes.

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