Faculty, Staff and Student Publications
Publication Date
3-9-2023
Journal
Journal of the National Cancer Institute
Abstract
BACKGROUND: There is a lack of evidence from nationwide samples on the disparity of initiating immune checkpoint inhibitors (ICIs) after metastatic lung cancer diagnosis.
METHODS: We identified metastatic lung cancer patients diagnosed between 2015 and 2020 from a large, nationwide commercial claims database. We analyzed the time from metastatic lung cancer diagnosis to ICI therapy using Cox proportional hazard models. Independent variables included county-level measures (quintiles of percentage of racialized population, quintiles of percentage of population below poverty, urbanity, and density of medical oncologists) and patient characteristics (age, sex, Charlson comorbidity index, Medicare Advantage, and year of diagnosis). All tests were 2-sided.
RESULTS: A total of 17 022 patients were included. Counties with a larger proportion of racialized population appeared to be more urban, have a greater percentage of its residents in poverty, and have a higher density of medical oncologists. In Cox analysis, the adjusted hazard ratio of the second, third, fourth, and highest quintile of percentage of racialized population were 0.89 (95% confidence interval [CI] = 0.82 to 0.98), 0.85 (95% CI = 0.78 to 0.93), 0.78 (95% CI = 0.71 to 0.86), and 0.71 (95% CI = 0.62 to 0.81), respectively, compared with counties in the lowest quintile. The slower ICI therapy initiation was driven by counties with the highest percentage of Hispanic population and other non-Black racialized groups.
CONCLUSIONS: Commercially insured patients with metastatic lung cancer who lived in counties with greater percentage of racialized population had slower initiation of ICI therapy after lung cancer diagnosis, despite greater density of oncologists in their neighborhood.
Keywords
Humans, Adult, Aged, United States, Medicare, Lung Neoplasms, Poverty, Proportional Hazards Models, Retrospective Studies
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Internal Medicine Commons, Medical Sciences Commons, Oncology Commons, Pulmonology Commons
Comments
Supplementary Materials
PMID: 36346180