Assessment and recalibration of seventeen lung cancer risk prediction models in approximately one million Chinese population utilising healthcare big data: a retrospective cohort analysis

作者：Ziqing Ye, Yexiang Sun, Yueqi Yin, Liya Liu, Miao Cui, Longyao Zhang, Yuantao Hao, David C. Christiani, Hongbo Lin, Peng Shen, Yongyue Wei · 发表于：The Lancet Regional Health - Western Pacific · 年份：2025 · DOI：10.1016/j.lanwpc.2025.101575 · 被引用次数：4 · 研究领域：Lung Cancer Diagnosis and Treatment、Lung Cancer Treatments and Mutations、Radiomics and Machine Learning in Medical Imaging

Background: A number of lung cancer prediction models have been developed worldwide. However, there have been limited validation studies conducted specifically on Chinese populations. The objective of this study is to evaluate the feasibility and performance of 17 global lung cancer risk prediction models when applied to Chinese healthcare big data. Methods: ), the Liverpool Lung Project version 3 (LLPv3), Lung Cancer Risk Score (LCRS), the Optimized Early Warning Model for Lung Cancer Risk (OWL), the University College London-Incidence (UCL-I), the Shanghai Lung Cancer incidence Model (Shanghai-LCM), were evaluated for their performance in overall population and subgroups stratified by age and sex. The discrimination of the 17 models was assessed using Harrell's C-index and time-dependent area under the curve (AUC). The calibration of the models was evaluated using the expected-to-observed ratio (EOR) and calibration curves. Moreover, the models were recalibrated in the Yinzhou population, and the calibration of the recalibrated models was evaluated. For each model before and after recalibration, we redefined risk thresholds that would select the same number of individuals as the China National Lung Cancer Screening Guideline with Low-dose Computed Tomography 2023 Version (CNLCS 2023) could screen out. The Kaplan-Meier method was used to estimate the incidence and number of cases of lung cancer in individuals screened according to different criteria or models over a five-yea...