Inverse Association Between METS-IR and Lung Cancer Risk: The Role of BMI in a Nationwide Korean Cohort.

BACKGROUND: Although insulin resistance has been implicated in cancer development, its specific role in lung cancer remains unclear. The metabolic score for insulin resistance (METS-IR) is a novel surrogate marker that integrates multiple metabolic parameters and has demonstrated strong predictive value for metabolic disorders. This study aimed to investigate the association between METS-IR and lung cancer incidence in a large-scale nationwide cohort. METHODS: We analyzed data from 322,624 participants of the National Health Insurance Service-National Health Screening Cohort in Republic of Korea. Participants were stratified into METS-IR quartiles, and lung cancer incidence was assessed using Kaplan-Meier survival curves and Cox proportional hazards regression models. Subgroup analyses were conducted to examine the impact of body composition, particularly sarcopenia, on the association between METS-IR and lung cancer. RESULTS: Over a median follow-up of 9.5 years, 5912 lung cancer cases were identified. Lung cancer incidence per 1000 person-years was highest in the lowest METS-IR quartile (Q1: 2.27) and decreased across quartiles (Q2: 1.93, Q3: 1.81, Q4: 1.72). In fully adjusted Cox regression models, using Q1 as the reference group, higher METS-IR quartiles were associated with a significantly lower risk of lung cancer (Q2: HR 0.91, 95% CI 0.85-0.98; Q3: HR 0.86, 95% CI 0.79-0.92; Q4: HR 0.80, 95% CI 0.74-0.86; p for trend < 0.001). Subgroup analyses revealed that the inverse association was more pronounced in male participants and individuals with a low body mass index. CONCLUSIONS: In this nationwide cohort study, we observed a significant inverse association between METS-IR and lung cancer risk. However, METS-IR showed limitations in fully explaining lung cancer risk based on insulin resistance alone. These findings highlight the need for future studies incorporating body composition assessments to better evaluate metabolic vulnerability.