title: Comparison of three mathematical prediction models in patients with a solitary pulmonary nodule.
abstract: BACKGROUND
  Effective methods for managing patients with solitary pulmonary nodules (SPNs) depend critically on the predictive probability of malignancy.
  
  
  METHODS
  Between July 2009 and June 2011, data on gender, age, cancer history, tumor familial history, smoking status, tumor location, nodule size, spiculation, calcification, the tumor border, and the final pathological diagnosis were collected retrospectively from 154 surgical patients with an SPN measuring 3-30 mm. Each final diagnosis was compared with the probability calculated by three predicted models-the Mayo, VA, and Peking University (PU) models. The accuracy of each model was assessed using area under the receiver operating characteristics (ROC) and calibration curves.
  
  
  RESULTS
  The area under the ROC curve of the PU model [0.800; 95% confidence interval (CI): 0.708-0.891] was higher than that of the Mayo model (0.753; 95% CI: 0.650-0.857) or VA model (0.728; 95% CI: 0.623-0.833); however, this finding was not statistically significant. To varying degrees, calibration curves showed that all three models overestimated malignancy.
  
  
  CONCLUSIONS
  The three predicted models have similar accuracy for prediction of SPN malignancy, although the accuracy is not sufficient. For Chinese patients, the PU model may has greater predictive power.
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Xuan
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Hong-Hong
authors.initials: HH
authors.lastname: Yan
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Jun-Tao
authors.initials: JT
authors.lastname: Lin
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Ze-Hua
authors.initials: ZH
authors.lastname: Wu
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Jia
authors.initials: J
authors.lastname: Liu
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Xu-Wei
authors.initials: XW
authors.lastname: Cao
authors.affiliation: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China .
authors.forename: Xue-Ning
authors.initials: XN
authors.lastname: Yang
keywords: Solitary pulmonary nodule (SPN); benign and malignant; comparison; model