Mathematical predication models (MPMs have been developed to inform of lung cancer risk for CT identified lung nodules, using simple clinical information (demographics, patient reported smoking and cancer history, and radiologist interpretation of CT data). We have demonstrated that the accuracy of these MPMs when applied to a common cohort of subjects, differs from that reported in the development publications. Our web tool (and published paper below) allows for exploration and tuning of MPM performance on local patient cohort.

https://www.i-clic.uihc.uiowa.edu/resources/sieren/mpm/

_{Uthoff J, Koehn N, Larson J, Dilger SKN, Hammond E, Schwartz A, Mullan B, Sanchez R, Hoffman RM, Sieren JC. Post-imaging pulmonary nodule mathematical prediction models: are they clinically relevant? European Radiology. 2019;29(10):5367-77. Epub 2019/04/03. doi: 10.1007/s00330-019-06168-x. PubMed PMID: 30937590; PMCID: PMC6717521.}