title: Clinical prediction model to characterize pulmonary nodules: validation and added value of 18F-fluorodeoxyglucose positron emission tomography.
abstract: BACKGROUND
  The added value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scanning as a function of pretest risk assessment in indeterminate pulmonary nodules is still unclear.
  
  
  OBJECTIVE
  To obtain an external validation of the prediction model according to Swensen and colleagues, and to quantify the potential added value of FDG-PET scanning as a function of its operating characteristics in relation to this prediction model, in a population of patients with radiologically indeterminate pulmonary nodules.
  
  
  METHODS
  Between August 1997 and March 2001, all patients with an indeterminate solitary pulmonary nodule who had been referred for FDG-PET scanning were retrospectively identified from the database of the PET center at the VU University Medical Center.
  
  
  RESULTS
  One hundred six patients were eligible for the study, and 61 patients (57%) proved to have malignant nodules. The goodness-of-fit statistic for the model (according to Swensen) indicated that the observed proportion of malignancies did not differ from the predicted proportion (p = 0.46). PET scan results, which were classified using the 4-point intensity scale reading, yielded an area under the evaluated receiver operating characteristic curve of 0.88 (95% confidence interval [CI], 0.77 to 0.91). The estimated difference of 0.095 (95% CI, -0.003 to 0.193) between the PET scan results classified using the 4-point intensity scale reading and the area under the curve (AUC) from the Swensen prediction was not significant (p = 0.058). The PET scan results, when added to the predicted probability calculated by the Swensen model, improves the AUC by 13.6% (95% CI, 6 to 21; p = 0.0003).
  
  
  CONCLUSIONS
  The clinical prediction model of Swensen et al was proven to have external validity. However, especially in the lower range of its estimates, the model may underestimate the actual probability of malignancy. The combination of visually read FDG-PET scans and pretest factors appears to yield the best accuracy.
authors.affiliation: Department of Pulmonary Medicine, VU University Medical Centre, De Boelelaan 1117, 1081 HV Amsterdam, the Netherlands.
authors.forename: Gerarda J
authors.initials: GJ
authors.lastname: Herder
authors.forename: Harm
authors.initials: H
authors.lastname: van Tinteren
authors.forename: Richard P
authors.initials: RP
authors.lastname: Golding
authors.forename: Piet J
authors.initials: PJ
authors.lastname: Kostense
authors.forename: Emile F
authors.initials: EF
authors.lastname: Comans
authors.forename: Egbert F
authors.initials: EF
authors.lastname: Smit
authors.forename: Otto S
authors.initials: OS
authors.lastname: Hoekstra
mesh_terms: D000368:Aged; D005260:Female; D019788:Fluorodeoxyglucose F18 / Q000493:pharmacokinetics; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D049268:Positron-Emission Tomography; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012907:Smoking; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D036542:Tomography, Spiral Computed
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18