JAMA network open
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Malignancy prediction models based on participant-related characteristics and imaging parameters from low-dose computed tomography (CT) may improve decision-making regarding nodule management and diagnosis in lung cancer screening. ⋯ This diagnostic study found that PanCan models showed excellent discrimination and calibration in prevalence screenings, confirming their ability to improve nodule management in screening settings, although calibration to nodules detected in follow-up scans should be improved. The models developed by the Mayo Clinic, Peking University People's Hospital, Department of Veterans Affairs, and UK Lung Cancer Screening Trial did not perform as well.