Social determinants of health and variability in treatment for patients with early-stage Non-Small Cell Lung Cancer.

Abstract

Background: In non-small cell lung cancer (NSCLC), social determinants of health (SDOHs) influence treatment, but SDOHs with geographic precision are infrequently used in real-world research due to privacy considerations. This research aims to characterize the influence of census-tract level SDOHs on treatment for stage I and IIa NSCLC.

Methods: Patients diagnosed between 1/1/17 and 9/30/22 with stages I and IIa NSCLC in the Syapse Learning Health Network had their addresses geocoded and linked to five census tract-level indicators of SDOH (social vulnerability index (SVI), percent (%) housing burden, % 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 SDOHs and initial treatment using two-sided Wald tests. The collective statistical significance of SDOHs was assessed with a likelihood ratio test (LRT) 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 ratios (RRR) for radiation therapy compared to surgery: living in primary care shortage areas (RRR 1.61, 95% CI: (1.23-2.10)) and living in non-metropolitan areas (RRR 1.45 (1.02-2.07)). The LRT suggested that the five SDOH variables collectively improved the treatment model. Further, patients in areas with high SVI, low internet access, and high housing-burden initiated treatment later.

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