A Prospective Study: the Impact of Sleep Disturbances on Immunotherapy in Patients With Lung Cancer

In recent years, immunotherapy has made significant progress in the treatment of lung cancer, especially immune checkpoint inhibitors (such as PD-1/PD-L1 antibodies) against non-small cell lung cancer (NSCLC). However, there are significant individual differences in patient response to treatment. Studies have shown that sleep disorders may affect the function of the immune system, thereby affecting tumor progression and treatment response. Therefore, the aim of this study was to evaluate the impact of sleep disturbances on lung cancer patients receiving immunotherapy.

Project title Association analysis between sleep disorders and tumor immunity in lung cancer: a prospective study Backgroundsleep disorders have been extensively studied in recent years and have been shown to be closely related to the development and prognosis of a variety of chronic diseases, including cancer. Especially in patients with lung cancer, sleep disorders may have an important impact on immune function, treatment response and patient survival. The changes of tumor immune microenvironment play an important role in the occurrence, development and response to immunotherapy of lung cancer. However, the relationship between sleep disorders and the tumor immune microenvironment of lung cancer has not been systematically explored. Therefore, the aim of this study was to evaluate the potential relationship between sleep disorders and tumor immunity in lung cancer and provide a new perspective for tumor immunotherapy strategies. Aimsthe aim of this study was to evaluate the potential relationship between sleep disorders and tumor immunity in lung cancer and provide a new perspective on tumor immunotherapy strategies. Primary outcome: Changes in tumor immune microenvironment: The effect of sleep disorders on tumor immune microenvironment was evaluated by immune cell infiltration analysis and immune marker expression level evaluation. Expression levels of immune checkpoint molecules: the changes of immune checkpoint molecules such as PD-1 and PD-L1 in tumor tissues of patients were detected. Secondary outcomes: The overall survival (OS) and progression-free survival (PFS) were analyzed. Biomarker changes: such as changes in the levels of cytokines (IL-6, TNF-α, etc.). Patient quality of life: The impact of sleep quality on patient general health was assessed using a standardized quality of life questionnaire. Study DesignThis study was a single-center, prospective, observational cohort study, combining biomarker analysis with clinical follow-up. The sample size estimate anticipated enrollment of 300 patients Inclusion/Exclusion/Withdrawal Criteria Inclusion criteria: Patients diagnosed with non-small cell lung cancer (NSCLC) or small cell lung cancer (SCLC). Age: 18 to 70 years old. Patients were required to have stage I-IV disease at diagnosis and to have consented to participate in the study. Patients had not received immunotherapy for 6 months before enrollment. Exclusion criteria: There were severe comorbidities (such as severe cardiovascular disease, end-stage liver and kidney disease, etc.). Patients with psychiatric conditions or inability to complete sleep assessments. Pregnant or lactating women. Patients who have received immunotherapy or other therapies that interfere with the immune microenvironment. Prospective study period from July 2025 to December 2027: patient collection, outcome follow-up, data collection and analysis; January to June 2028: data analysis, paper writing July 2028 \~ December 2028: Submission of papers Statistical analysis plan Descriptive statistics: Descriptive statistical analysis was performed on the basic characteristics of patients, sleep quality scores, and immune markers. Survival analysis: Kaplan-Meier survival curve was used to analyze the relationship between sleep quality and overall survival (OS) and progression-free survival (PFS) of lung cancer patients. log-rank test was used to compare the difference of survival time between different sleep quality groups. Multivariate Cox regression analysis: the effect of sleep quality on immune microenvironment and survival outcome was further analyzed after adjusting for clinical covariates (such as age, gender, lung cancer stage, treatment regimen, etc.). Immune cell infiltration analysis: The degree of immune cell infiltration in patients with different sleep quality was analyzed by immunohistochemistry and flow cytometry, and its relationship with immunotherapy response was explored.