Utilization, outcomes, and costs related to the use of immune checkpoint inhibitors for the treatment of advanced non-small cell lung cancer among individuals with preexisting autoimmune diseases

The National Cancer Institute awarded Yale University $100,228 on December 15, 2026, under the Cancer Research Manpower program (CFDA 93.398) to conduct observational studies on immune checkpoint inhibitor utilization, outcomes, and costs in advanced non-small cell lung cancer patients with preexisting autoimmune diseases.

The research generates population-based evidence through three aims using real-world insurance claims data. Aim 1 analyzes MarketScan research databases to evaluate the association between autoimmune disease status and immunosuppressant use on immune checkpoint inhibitor utilization in patients with newly diagnosed advanced lung cancer across all ages. Aims 2 and 3 use SEER-Medicare data to estimate survival differences and compare immune-related adverse event costs, cancer treatment costs, and total healthcare costs between patients with and without preexisting autoimmune diseases in the over-65 population. The study addresses a critical evidence gap, as individuals with autoimmune diseases have been largely excluded from clinical trials despite the expanding use of immune checkpoint inhibitors in advanced lung cancer treatment.

Yale University serves as the recipient with place of performance in New Haven, Connecticut. The period of performance runs from December 15, 2026, through July 15, 2028. The Cancer Research Manpower program supports biomedical training opportunities for individuals pursuing careers in basic, clinical, and prevention research important to the National Cancer Program.

Abstract

Immune checkpoint inhibitors (ICIS) have significantly improved outcomes for many patients with advanced lung cancer. However, individuals with preexisting autoimmune diseases (ADS) have largely been excluded from clinical trials due to concerns about immune-related adverse events (IRAES). As a result, evidence guiding treatment decisions for this complex patient population is limited, and IT remains unclear how ad status and immunosuppressant use influence ICI utilization, outcomes, and costs. This proposal seeks to generate population-based evidence on ICI use in individuals with ad through a series of observational studies using real-world data from two large insurance claims databases. Aim 1 will use the marketscan research databases to evaluate the association between ad status and immunosuppressant use and the utilization of ICIS in patients with newly diagnosed advanced lung cancer. Aims 2 and 3 will use seer-medicare data to estimate differences in survival and irae-related, cancer treatment-related, and total healthcare costs between those with and without preexisting ADS. Using the marketscan data will allow US to understand the prevalence of ad and the utilization of ICIS across all ages in the overall population of individuals with advanced lung cancer. However, both lung cancer and ad are more common in older adults, which motivates the use of the over-65 seer-medicare sample for aims 2 & 3. Given the rapidly changing treatment landscape and limited high-quality evidence, IT is essential to analyze the real-world utilization, outcomes, costs, and toxicity of ICI therapy among those with preexisting ad as compared to the non-ad lung cancer population. Upon successful completion of this study, we will have addressed critical knowledge gaps on factors impacting the risks and benefits of ICI use in a real-world setting. These findings will support more informed, individualized clinical decision-making for the vulnerable population of individuals with advanced lung cancer and preexisting ad. The fellowship training plan includes advanced coursework and mentored training in causal inference, survival analysis, and health services research approaches, along with structured opportunities to present and publish results generated from these analyses. The research will be conducted in a highly collaborative, methodologically rigorous environment with strong faculty mentorship and access to state-of-the-art data resources. This work will prepare the candidate for a career as an independent investigator focused on improving cancer care for medically complex populations.