Table 1. Prediction model examples (listed in order of appearance).

Model	Outcome	Type of model	Study design	Population
TREAT model (Deppen et al.) (4)	Lung cancer in indeterminate pulmonary nodules	Logistic regression	Retrospective cohort	Patients with indeterminate pulmonary nodules presenting to thoracic surgery clinics (high prevalence of lung cancer)
ACS NSQIP Mortality (5)	Mortality after surgery	Logistic regression	Retrospective cohort	Low-risk patients referred for general surgery procedures
Mayo Clinic model (Swensen et al.) (6)	Lung cancer in solitary lung nodules	Logistic regression	Retrospective cohort	Pulmonary clinic patients with solitary pulmonary nodules (low prevalence of lung cancer)
Farjah et al. (7)	Presence of N2 nodal disease in lung cancer	Logistic regression	Retrospective cohort	Patients with suspected or confirmed non-small cell lung cancer and negative mediastinum by PET
Liverpool Lung Project (LLP) model (Cassidy et al.) (8)	Lung cancer development	Logistic regression	Retrospective case control	Patients at high risk of developing lung cancer
Tammemagi model (9)	Lung cancer screening-detected pulmonary nodules	Logistic regression	Prospective cohort	High-risk patients undergoing screening CT scan

TREAT, Thoracic Research Evaluation And Treatment; PET, positron emission tomography.