The goal of this study is to assess outcome measures for stage IV non-small cell lung cancer (NSCLC) patients in a real-world setting in a prospective manner. A previous retrospective project at Windsor Regional Hospital Cancer Program showed that comparative outcomes were better initially for the patients treated with monotherapy rather than a combination of chemo and immunotherapy. We will compare outcomes of mono-immunotherapy with combination immunotherapy and chemotherapy based on individual patient characteristics in a real-world setting. The data collected will be correlated to patient factors in the two treatment groups in order to identify patient populations that are better suited to either immune-monotherapy or combined immunotherapy and chemotherapy. This study will utilize a prospective cohort design assessing stage IV NSCLC patients treated at Windsor Regional Hospital Cancer Program between February 1, 2023 and January 31, 2025. The primary endpoints of this study are progression-free survival and overall survival. The secondary endpoints will include side effects, discontinuation rates and breaks in treatment, performance status, steroid and antibiotic use, comorbidities, and patient demographics and disease characteristics. Data will be collected via CERNER chart review in REDCap and anonymized. Standard telephone consent will be obtained to use the anonymized data for research purposes. A University of Windsor statistician will assist in anonymized data analysis. A poster presentation and complete manuscript will be produced after the completion of the project.

Clinical trials have demonstrated the efficacy of both immunotherapy alone and immunotherapy in conjunction with chemotherapy to improve outcomes in metastatic NSCLC. However, little literature exists comparing immunotherapy to combined immunotherapy and chemotherapy. As a result, it is important to assess outcome measures seen in clinical practice. It is also important to assess the relative efficacies of these two modalities based on individual patient factors such as performance status, comorbidities, patient demographics, and disease characteristics, so that future treatment may be better tailored to improve outcomes of individual patients.