Combined application of multiple biomarkers for early auxiliary diagnosis of silicosis

Silicosis is an important industrial health problem for those workers exposed to silica. The present study aimed to investigate the sensitivity and specificity of combined detection of biomarkers in early auxiliary diagnosis of silicosis, the risk factors of silicosis were also studied. The study sample comprised 65 workers who had clinical silicosis and 70 matched control subjects who were exposed to silica but did not have clinical silicosis. The levels of superoxide dismutase, malondialdehyde, interleukin 6 (IL-6), tumor necrosis factor-alpha, and cholinesterases in the serum of 135 subjects were measured. After completing the biochemical assays, a logistic regression model based on the above biochemical determination results was established, and the receiver operating characteristic curve was used for judging the discrimination ability of different statistical indexes. The expression levels of MDA, IL-6, and TNF-alpha in serum samples of patients with stage I silicosis and MDA and IL-6 in serum samples of patients with stage II silicosis were all significantly higher. Results from logistic regression analysis showed that ChEs were protective factors for silicosis, while age, chronic respiratory symptoms, IL-6, and MDA were risk factors. The areas under the ROC curve (AUC) were 0.86 (IL-6), 0.81 (MDA), and 0.65 (TNF-alpha or ChEs). AUC-ROC = 0.90 (95%CI:0.84-0.95). The diagnostic efficiency of IL-6 combined with MDA and TNF-alpha was better than that of any single biomarker.