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. 2007 Feb;131(2):383-8.
doi: 10.1378/chest.06-1261.

A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules

Michael K Gould  1 , Lakshmi Ananth, Paul G Barnett; Veterans Affairs SNAP Cooperative Study Group
Affiliations

A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodules

Michael K Gould et al. Chest. 2007 Feb.

Abstract

Background: Estimating the clinical probability of malignancy in patients with a solitary pulmonary nodule (SPN) can facilitate the selection and interpretation of subsequent diagnostic tests.

Methods: We used multiple logistic regression analysis to identify independent clinical predictors of malignancy and to develop a parsimonious clinical prediction model to estimate the pretest probability of malignancy in a geographically diverse sample of 375 veterans with SPNs. We used data from Department of Veterans Affairs (VA) administrative databases and a recently completed VA Cooperative Study that evaluated the accuracy of positron emission tomography (PET) scans for the diagnosis of SPNs.

Results: The mean (+/- SD) age of subjects in the sample was 65.9 +/- 10.7 years. The prevalence of malignant SPNs was 54%. Most participants were either current smokers (n = 177) or former smokers (n = 177). Independent predictors of malignant SPNs included a positive smoking history (odds ratio [OR], 7.9; 95% confidence interval [CI], 2.6 to 23.6), older age (OR, 2.2 per 10-year increment; 95% CI, 1.7 to 2.8), larger nodule diameter (OR, 1.1 per 1-mm increment; 95% CI, 1.1 to 1.2), and time since quitting smoking (OR, 0.6 per 10-year increment; 95% CI, 0.5 to 0.7). Model accuracy was very good (area under the curve of the receiver operating characteristic, 0.79; 95% CI, 0.74 to 0.84), and there was excellent agreement between the predicted probability and the observed frequency of malignant SPNs.

Conclusions: Our prediction rule can be used to estimate the pretest probability of malignancy in patients with SPNs, and thereby facilitate clinical decision making when selecting and interpreting the results of diagnostic tests such as PET imaging.

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Conflict of interest statement

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Figures

Figure 1
Figure 1
Calibration curve for the clinical prediction model. The figure plots the observed frequency of malignancy as a function of the predicted probability of malignancy for patients in each quintile of predicted probability. The curve shows that the observed frequency of malignancy was similar to the predicted probability of malignancy for patients in each quintile. The range of predicted probabilities for patients in the first, second, third, fourth and fifth quintiles were < 0.29, 0.29 to 0.48, 0.48 to 0.66, 0.66 to 0.79, and > 0.79, respectively.
See this image and copyright information in PMC

References

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