Pneumoconioses Radiographs in a Large Population of U.S. Coal Workers: Variability in A Reader and B Reader Classifications by Using the International Labour Office Classification.

Purpose To assess the level of concordance between chest radiographic classifications of A and B Readers in a national surveillance program offered to U.S. coal miners over an approximate 36-year period. Materials and Methods The National Institute for Occupational Safety and Health (NIOSH) Coal Workers' Health Surveillance Program (CWHSP) is a surveillance program with nonresearch designation and is exempt from Human Subjects Review Board approval (11-DRDS-NR03). Thirty-six years of data (1979-2015) from the CWHSP were analyzed, which included all conventional screen-film radiographs with a classification by at least one A Reader and one B Reader. Agreement was assessed by using κ statistics; prevalence ratios were used to describe differences between A and B Reader determinations of image technical quality, small opacity profusion, and presence of large opacities and pleural abnormalities. Results The analysis included 79 185 matched A and B Reader chest radiograph classifications. A majority of both A and B Readers were radiologists (74.2% [213 of 287] vs 64.7% [22 of 34]; P = .04). A and B Readers had minimal agreement on technical image quality (κ = 0.0796; 95% confidence interval [CI]: 0.07, 0.08) and the distribution of small opacity profusion (subcategory κ, 0.2352; 95% CI: 0.22, 0.25). A Readers classified more images as "good" quality (prevalence ratio, 1.38; 95% CI: 1.35, 1.41) and identified more pneumoconiosis (prevalence ratio, 1.22; 95% CI: 1.20, 1.23). Conclusion A Readers classified substantially more radiographs with evidence of pneumoconiosis and classified higher small opacity profusion compared with B Readers. These observations reinforce the importance of multiple classifications by readers who have demonstrated ongoing competence in the International Labour Office classification system to ensure accurate radiographic classifications. © RSNA, 2017.