Lung cancer risk assessment by prediction model: a global perspective.

ABSTRACT:

Background

Numerous lung cancer risk prediction models have been developed and validated worldwide. It is imperative to offer a comprehensive overview and comparative analysis of their performances.

Methods

We conducted an extensive literature search to identify studies developing and/or validating lung cancer risk prediction models. Then we summarised and compared the external performance of these models, focusing on discriminative accuracy (C-index) and calibration performance (E:O ratio).

Results

After an initial screening of 10 210 articles, 35 studies on 21 distinct prediction models were identified, which used 42 different types of predictors spanning seven categories. Notable performance variations were observed in external validations. In North American cohort

SUBMITTER: Zhang L 

PROVIDER: S-EPMC12703260 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature