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Comparative Study
. 1998 Jan;34(1):4-8.

[Solitary pulmonary nodule: application of Bayes theorem in prediction of malignancy]

[Article in Spanish]
Affiliations
  • PMID: 9522014
Comparative Study

[Solitary pulmonary nodule: application of Bayes theorem in prediction of malignancy]

[Article in Spanish]
A Ramos Martínez et al. Arch Bronconeumol. 1998 Jan.

Abstract

Most radiological signs are of low specificity for predicting malignancy in patients with a solitary pulmonary nodule (SPN), making clinical management difficult. Only certain calcification patterns in SPN or the absence of growth over a period two years assures that the nodule is benign. The clinical and radiological characteristics of 31 patients with SPN were studied. Twenty-two were cases bronchopulmonary carcinoma and 9 were pulmonary tuberculoma. Accuracy in the prediction of malignancy was assessed using Bayes' theorem, which is based on degrees of likelihood of various radiological and clinical characteristics. Patients with carcinoma (mean age 65 +/- 9 years) were significantly older than those with tuberculoma (38 +/- 19 years) (p < 0.05). The proportion of smokers was significantly higher among patients with carcinoma (91%) than those with tuberculoma (44%) (p < 0.05). In 50% of the patients with SPN due to bronchopulmonary carcinoma (11 patients), the nodule was in the upper right lobe; in 55% of those with tuberculomas (5 patients) the nodule was found in the upper left lobe. There were no significant differences in the characteristics of the computerized tomography images for the two groups. Mean likelihood of malignancy for patients with carcinoma, by Bayes' theorem, was 83.7%, a rate that was significantly higher than that of tuberculoma patients (46%) (p < 0.05). The application of Bayes' probability theorem for a set of clinical and radiological characteristics can orient the physician as to whether an SPN is likely to be malignant or not, thereby providing guidance on the advisability of performing invasive diagnostic procedures to determine etiology.

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