Effect of improving the quality of radiographic interpretation on the ability to predict pulmonary tuberculosis relapse.

RATIONALE AND OBJECTIVES: Chest radiographic findings are important for diagnosis and management of tuberculosis. The reliability of these findings is therefore of interest. We sought to describe interobserver reliability of chest radiographic findings in pulmonary tuberculosis, and to understand how the reliability of these findings might affect the utility of radiographic findings in predicting tuberculosis relapse. MATERIALS AND METHODS: Three blinded readers independently reviewed chest radiographs from a randomly selected group of 10% of HIV-seronegative subjects participating in a tuberculosis treatment trial. The three readers then arrived at a fourth, consensus radiographic interpretation. RESULTS: A total of 241 films obtained from 99 patients were reviewed. Agreement among the independent readers was very good for the findings of bilateral disease (kappa = 0.71-0.86 among readers) and cavitation (kappa = 0.66-0.73). The original interpretation was reasonably sensitive and specific (compared to the consensus interpretation) for bilateral disease, but the sensitivity for cavity decreased from 81% for the 2-month film to 47% at end of treatment (P = 0.013). Substituting the consensus interpretation for the original interpretation increased the odds ratio for the association between cavitation on early chest radiograph and subsequent tuberculosis relapse from 4.97 to 8.97. CONCLUSION: Radiographic findings were reasonably reliable between independent reviewers and the original interpretations. The original investigators, who knew the patient's clinical course, were less likely to identify cavitation on the end of treatment chest radiograph. Improving the reliability of these findings could improve the utility of chest radiographs for predicting tuberculosis relapse.

Duke Scholars

Author Jason Eric Stout Medicine, Infectious Diseases

Author Andrzej Stanislaw Kosinski Biostatistics & Bioinformatics, Division of Biostatistics

Author Carol Dukes Hamilton Medicine, Infectious Diseases

Author Philip C. Goodman Radiology, Cardiothoracic Imaging