Understanding East-West differences in subsolid nodules: prevalence and overdiagnosis implications in lung cancer screening - Yeun-Chung Chang; Yi-Chi Hung; Yun-Ju Wu; En-Kuei Tang; Fu-Zong Wu (Annals of Medicine)
Background Owing to the widespread opportunistic LDCT screening leading to increased overdiagnosis in Asian countries, such as South Korea, mainland China, and Taiwan, this study seeks to analyze the divergence in SSN prevalence between Eastern and Western nations, focusing on the influence of SSN on the growing overdiagnosis trend, notably among females.Methods This retrospective study collected data from 4166 participants who underwent baseline LDCT in a hospital-based cohort between January 2014 and August 2021. Clinical parameters, including age, sex, lung imaging reporting and data system (Lung-RADS) categories, smoking history, pack-year dose, and SSN characteristics, were extracted from electronic medical records. Additionally, a narrative review and pooled analysis integrated relevant published studies on the prevalence of subsolid nodules and sex disparities.Results The study encompassed 4166 participants, with females accounting for 49.3% and males for 50.7%, with a mean age of 53.38 ± 10.89. The prevalence of SSNs was significantly higher in females (20.1%) than in males (12.6%). Pooled analysis across seven studies revealed a significantly higher prevalence of SSN in Eastern countries (12.6%) compared to the prevalence in Western countries (3.6%) (test for subgroup differences: p < 0.01; I2 = 100%). Additionally, a notable sex difference was observed in the prevalence of SSNs (risk ratio = 0.489, 95% CI: 0.301–0.796, p < 0.01; reference group: male group).Conclusions Apart from differences in clinical management and health literacy regarding SSNs between Eastern and Western countries, the high prevalence of SSNs in Asian nations, particularly among females, significantly contributes to the issue of overdiagnosis in opportunistic lung cancer screening in Asian countries. Tailored sex-specific strategies and risk prediction models are essential for effective screening optimization.