title: Multicentre external validation of the BIMC model for solid solitary pulmonary nodule malignancy prediction.
abstract: OBJECTIVE
  To provide multicentre external validation of the Bayesian Inference Malignancy Calculator (BIMC) model by assessing diagnostic accuracy in a cohort of solitary pulmonary nodules (SPNs) collected in a clinic-based setting. To assess model impact on SPN decision analysis and to compare findings with those obtained via the Mayo Clinic model.
  
  
  METHODS
  Clinical and imaging data were retrospectively collected from 200 patients from three centres. Accuracy was assessed by means of receiver-operating characteristic (ROC) areas under the curve (AUCs). Decision analysis was performed by adopting both the American College of Chest Physicians (ACCP) and the British Thoracic Society (BTS) risk thresholds.
  
  
  RESULTS
  ROC analysis showed an AUC of 0.880 (95 % CI, 0.832-0.928) for the BIMC model and of 0.604 (95 % CI, 0.524-0.683) for the Mayo Clinic model. Difference was 0.276 (95 % CI, 0.190-0.363, P < 0.0001). Decision analysis showed a slightly reduced number of false-negative and false-positive results when using ACCP risk thresholds.
  
  
  CONCLUSIONS
  The BIMC model proved to be an accurate tool when characterising SPNs. In a clinical setting it can distinguish malignancies from benign nodules with minimal errors by adopting current ACCP or BTS risk thresholds and guiding lesion-tailored diagnostic and interventional procedures during the work-up.
  
  
  CONCLUSIONS
  • The BIMC model can accurately discriminate malignancies in the clinical setting • The BIMC model showed ROC AUC of 0.880 in this multicentre study • The BIMC model compares favourably with the Mayo Clinic model.
authors.affiliation: UOC Radiologia, Ospedale Maggiore di Borgo Trento, AOUI Verona, Verona, Italy.
authors.forename: Gian Alberto
authors.initials: GA
authors.lastname: Soardi
authors.affiliation: UOC Radiologia, Ospedale Maggiore di Borgo Trento, AOUI Verona, Verona, Italy. mail@simoneperandini.com.
authors.forename: Simone
authors.initials: S
authors.lastname: Perandini
authors.affiliation: Dipartimento di Scienze Radiologiche, Università Cattolica del Sacro Cuore, Roma, Italy.
authors.forename: Anna Rita
authors.initials: AR
authors.lastname: Larici
authors.affiliation: Dipartimento di Scienze Radiologiche, Università Cattolica del Sacro Cuore, Roma, Italy.
authors.forename: Annemilia
authors.initials: A
authors.lastname: Del Ciello
authors.affiliation: UO Chirurgia Toracica, Ospedale Humanitas Gavazzeni, Bergamo, Italy.
authors.forename: Giovanna
authors.initials: G
authors.lastname: Rizzardi
authors.affiliation: UO Radiologia, Ospedale Humanitas Gavazzeni, Bergamo, Italy.
authors.forename: Antonio
authors.initials: A
authors.lastname: Solazzo
authors.affiliation: UO Pneumologia, Ospedale dell'Angelo di Mestre (VE), Mestre, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Mancino
authors.affiliation: UO Radiologia, Ospedale dell'Angelo di Mestre (VE), Mestre, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Bernhart
authors.affiliation: UOC Radiologia, Ospedale Maggiore di Borgo Trento, AOUI Verona, Verona, Italy.
authors.forename: Massimiliano
authors.initials: M
authors.lastname: Motton
authors.affiliation: UOC Radiologia, Ospedale Maggiore di Borgo Trento, AOUI Verona, Verona, Italy.
authors.forename: Stefania
authors.initials: S
authors.lastname: Montemezzi
mesh_terms: D000368:Aged; D000066491:Clinical Decision-Making; D003661:Decision Support Techniques; D055088:Early Detection of Cancer; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis*; D008297:Male; D008962:Models, Theoretical; D003074:Solitary Pulmonary Nodule / Q000175:diagnosis*
keywords: Computed tomography; Decision analysis; Lung cancer; Solid pulmonary nodule