Simone Perandini1, G A Soardi2, A R Larici3, A Del Ciello3, G Rizzardi4, A Solazzo5, L Mancino6, F Zeraj6, M Bernhart7, M Signorini2, M Motton2, S Montemezzi2. 1. UOC Radiologia, Ospedale Maggiore di Borgo Trento, Azienda Ospedaliera Universitaria Integrata di Verona, Piazzale Stefani 1, Verona, 37124, Italy. mail@simoneperandini.com. 2. UOC Radiologia, Ospedale Maggiore di Borgo Trento, Azienda Ospedaliera Universitaria Integrata di Verona, Piazzale Stefani 1, Verona, 37124, Italy. 3. Dipartimento di Scienze Radiologiche, Università Cattolica del Sacro Cuore, Roma, Italy. 4. UO Chirurgia Toracica, Ospedale Humanitas Gavazzeni, Bergamo, Italy. 5. UO Radiologia, Ospedale Humanitas Gavazzeni, Bergamo, Italy. 6. UO Pneumologia, Ospedale dell'Angelo di Mestre, Venezia, Italy. 7. UO Radiologia, Ospedale dell'Angelo di Mestre, Venezia, Italy.
Abstract
OBJECTIVES: To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models. METHODS: Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines. RESULTS: Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875). CONCLUSIONS: Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis. KEY POINTS: • The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.
OBJECTIVES: To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models. METHODS: Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines. RESULTS: Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875). CONCLUSIONS: Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis. KEY POINTS: • The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.
Authors: K Nakamura; H Yoshida; R Engelmann; H MacMahon; S Katsuragawa; T Ishida; K Ashizawa; K Doi Journal: Radiology Date: 2000-03 Impact factor: 11.105
Authors: S J Swensen; M D Silverstein; E S Edell; V F Trastek; G L Aughenbaugh; D M Ilstrup; C D Schleck Journal: Mayo Clin Proc Date: 1999-04 Impact factor: 7.616
Authors: David M Hansell; Alexander A Bankier; Heber MacMahon; Theresa C McLoud; Nestor L Müller; Jacques Remy Journal: Radiology Date: 2008-01-14 Impact factor: 11.105
Authors: Annette McWilliams; Martin C Tammemagi; John R Mayo; Heidi Roberts; Geoffrey Liu; Kam Soghrati; Kazuhiro Yasufuku; Simon Martel; Francis Laberge; Michel Gingras; Sukhinder Atkar-Khattra; Christine D Berg; Ken Evans; Richard Finley; John Yee; John English; Paola Nasute; John Goffin; Serge Puksa; Lori Stewart; Scott Tsai; Michael R Johnston; Daria Manos; Garth Nicholas; Glenwood D Goss; Jean M Seely; Kayvan Amjadi; Alain Tremblay; Paul Burrowes; Paul MacEachern; Rick Bhatia; Ming-Sound Tsao; Stephen Lam Journal: N Engl J Med Date: 2013-09-05 Impact factor: 91.245
Authors: James M Isbell; Stephen Deppen; Joe B Putnam; Jonathan C Nesbitt; Eric S Lambright; Aaron Dawes; Pierre P Massion; Theodore Speroff; David R Jones; Eric L Grogan Journal: Ann Thorac Surg Date: 2011-01 Impact factor: 4.330
Authors: Nichole T Tanner; Alexander Porter; Michael K Gould; Xiao-Jun Li; Anil Vachani; Gerard A Silvestri Journal: Chest Date: 2017-01-20 Impact factor: 9.410
Authors: Felipe Alves Mourato; Ana Emília Teixeira Brito; Monique Sampaio Cruz Romão; Renata Guerra Galvão Santos; Cristiana Altino de Almeida; Paulo José de Almeida Filho; Aline Lopes Garcia Leal Journal: Radiol Bras Date: 2020 Jan-Feb