Improving Lung Cancer Screening Selection: A Comparative Analysis of Risk Models and Traditional Criteria in a Western European General Population

<b>Background/Objectives</b>: The objective of this study is to evaluate the performance of the traditional age/smoking criteria and existing risk prediction models in selecting high-risk populations for lung cancer screening from a Western European general population. <b>Methods</b>: Baseline data from the Dutch population-based Lifelines cohort, collected between 2006 and 2013, were linked to the Dutch cancer registry to confirm lung cancer diagnoses. Five-year lung cancer risk was estimated based on traditional age/smoking criteria (NLST, NELSON, SPSTF-2021) and risk prediction models (LLPv2, PLCOm2012, Hoggart, Bach and Shanghai-LCM). For every strategy, the number of individuals eligible was determined, and total lung cancer cases in the eligible groups versus the ineligible groups were calculated. <b>Results</b>: Among 139,120 participants (aged ≥18 years), 218 (0.2%) developed lung cancer within five years. Age/smoking criteria identified 2161-6295 (1.6-4.5%) participants as eligible, comprising 62-92 (28.4-42.2%) lung cancer cases. Risk prediction models identified 2372-4315 (1.7-3.1%) participants as eligible, comprising 40-85 (18.4-38.9%) lung cancer cases. Among lung cancers in ineligible groups, 46.2-59.6% occurred in individuals who formerly smoked, and 28.7-39.3% occurred in individuals who currently smoke. Additionally, 41.2-70.0% of lung cancer cases in ineligible groups were in individuals younger than 50, and 44.3-72.3% in individuals who had quit smoking > 15 years prior to diagnosis. <b>Conclusions</b>: In a Western European population, current lung cancer screening selection criteria resulted in identifying only 18-42% of lung cancer cases. Cases in ineligible groups predominantly concern individuals who currently smoke and are below the threshold age and individuals who quit smoking > 15 years ago, highlighting the opportunity for more personalized risk-based screening strategies to increase lung cancer detection.