Skip to main content

Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.

Publication ,  Journal Article
Schultz, EM; Sanders, GD; Trotter, PR; Patz, EF; Silvestri, GA; Owens, DK; Gould, MK
Published in: Thorax
April 2008

BACKGROUND: Effective strategies for managing patients with solitary pulmonary nodules (SPN) depend critically on the pre-test probability of malignancy. OBJECTIVE: To validate two previously developed models that estimate the probability that an indeterminate SPN is malignant, based on clinical characteristics and radiographic findings. METHODS: Data on age, smoking and cancer history, nodule size, location and spiculation were collected retrospectively from the medical records of 151 veterans (145 men, 6 women; age range 39-87 years) with an SPN measuring 7-30 mm (inclusive) and a final diagnosis established by histopathology or 2-year follow-up. Each patient's final diagnosis was compared with the probability of malignancy predicted by two models: one developed by investigators at the Mayo Clinic and the other developed from patients enrolled in a VA Cooperative Study. The accuracy of each model was assessed by calculating areas under the receiver operating characteristic (ROC) curve and the models were calibrated by comparing predicted and observed rates of malignancy. RESULTS: The area under the ROC curve for the Mayo Clinic model (0.80; 95% CI 0.72 to 0.88) was higher than that of the VA model (0.73; 95% CI 0.64 to 0.82), but this difference was not statistically significant (Delta = 0.07; 95% CI -0.03 to 0.16). Calibration curves showed that the probability of malignancy was underestimated by the Mayo Clinic model and overestimated by the VA model. CONCLUSIONS: Two existing prediction models are sufficiently accurate to guide decisions about the selection and interpretation of subsequent diagnostic tests in patients with SPNs, although clinicians should also consider the prevalence of malignancy in their practice setting when choosing a model.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Thorax

DOI

EISSN

1468-3296

Publication Date

April 2008

Volume

63

Issue

4

Start / End Page

335 / 341

Location

England

Related Subject Headings

  • Solitary Pulmonary Nodule
  • Retrospective Studies
  • Respiratory System
  • ROC Curve
  • Probability
  • Predictive Value of Tests
  • Models, Biological
  • Middle Aged
  • Male
  • Lung Neoplasms
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Schultz, E. M., Sanders, G. D., Trotter, P. R., Patz, E. F., Silvestri, G. A., Owens, D. K., & Gould, M. K. (2008). Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules. Thorax, 63(4), 335–341. https://doi.org/10.1136/thx.2007.084731
Schultz, E. M., G. D. Sanders, P. R. Trotter, E. F. Patz, G. A. Silvestri, D. K. Owens, and M. K. Gould. “Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.Thorax 63, no. 4 (April 2008): 335–41. https://doi.org/10.1136/thx.2007.084731.
Schultz EM, Sanders GD, Trotter PR, Patz EF, Silvestri GA, Owens DK, et al. Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules. Thorax. 2008 Apr;63(4):335–41.
Schultz, E. M., et al. “Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules.Thorax, vol. 63, no. 4, Apr. 2008, pp. 335–41. Pubmed, doi:10.1136/thx.2007.084731.
Schultz EM, Sanders GD, Trotter PR, Patz EF, Silvestri GA, Owens DK, Gould MK. Validation of two models to estimate the probability of malignancy in patients with solitary pulmonary nodules. Thorax. 2008 Apr;63(4):335–341.

Published In

Thorax

DOI

EISSN

1468-3296

Publication Date

April 2008

Volume

63

Issue

4

Start / End Page

335 / 341

Location

England

Related Subject Headings

  • Solitary Pulmonary Nodule
  • Retrospective Studies
  • Respiratory System
  • ROC Curve
  • Probability
  • Predictive Value of Tests
  • Models, Biological
  • Middle Aged
  • Male
  • Lung Neoplasms