Embodiments of the present invention relate generally to non-invasive methods and diagnostic tests that measure biomarkers (e.g., tumor antigens), clinical parameters and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient with radiographic apparent pulmonary nodules are malignant as compared to benign, relative to a patient population or a cohort population. By utilizing algorithms generated from the biomarker levels (e.g., tumor antigens) from large volumes of longitudinal or prospectively collected blood samples (e.g., real world data from one or more regions where blood based tumor biomarker cancer screening is commonplace) together with one or more clinical parameters (e.g. age, smoking history, disease signs or symptoms) a risk level of that patient having malignant pulmonary nodules is provided.
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