Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for solitary pulmonary nodule evaluation
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To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models.
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.
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).
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.
• 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.
Keywords18 F-fluorodeoxyglucose positron emission tomography Lung cancer Solid pulmonary nodule Decision analysis Computed tomography
The scientific guarantor of this publication is Simone Perandini. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. One of the authors has significant statistical expertise (S.P.). Institutional Review Board approval was not required because the research involved collection and analysis of existing data. Written informed consent was not required for this study because the research involved collection and analysis of existing data. Data and diagnostic specimens were recorded by the investigator in such a manner that subjects cannot be identified. Methodology: retrospective, diagnostic or prognostic study, multicentre study.
- 1.Trotman-Dickenson B, Baumert B (2003) Multidetector-row CT of the solitary pulmonary nodule. In: Seminars in roentgenology, vol. 38, No. 2. WB Saunders, pp 158–167Google Scholar
- 3.Swensen SJ, Silverstein MD, Edell ES, Trastek VF, Aughenbaugh GL, Ilstrup DM, Schleck CD (1999) Solitary pulmonary nodules: clinical prediction model versus physicians. In: Mayo Clinic Proceedings, vol. 74, No. 4. Elsevier, pp 319–329Google Scholar
- 8.McWilliams A, Tammemagi MC, Mayo JR, Roberts H, Liu G, Soghrati K, … Lam S (2013) Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med 369(10):910–919Google Scholar
- 14.Al-Ameri A, Malhotra P, Thygesen H, Plant PK, Vaidyanathan S, Karthik S, Callister ME (2015) Risk of malignancy in pulmonary nodules: a validation study of four prediction models. Lung CancerGoogle Scholar