Clinical significance of combined use of serum CC16 and SP-D in early diagnosis for occupational silicosis / 中国职业医学

ABSTRACT

OBJECTIVE: To study the method and significance of serum level of Clara cell protein(CC16) and surfactant protein D(SP-D) in the early diagnosis of patients with occupational silicosis. METHODS: By a convenience sampling method, 73 male patients with occupational silicosis were included in the silicosis group, 27 male workers who exposed to dust without occupational silicosis were selected as the dust exposure group, and 27 healthy men with no history of occupational dust exposure were selected as control group. The levels of serum CC16 and SP-D were detected by enzyme-linked immune sorbent assay. RESULTS: Serum levels of CC16 in patients of silicosis and dust exposure groups were significantly lower than those of the control group [(40.15±13.31) vs(53.85±11.45) mg/L,(25.2±48.18) vs(53.85±11.45) mg/L, P<0.05]. The serum level of CC16 in silicosis group was higher than that of dust exposure group [(25.24±8.18) vs(40.15±13.31) mg/L, P<0.05]. Serum level of SP-D in silicosis group was significantly higher than those in the controls and dust exposure group [(59.22±10.67) vs(49.07±9.72) mg/L,(59.22±10.67) vs(46.82±10.40) mg/L, P<0.05]. Bayes discrimination analysis was used to establish a combined diagnostic discriminant model with age, CC16 and SP-D levels. The correct rates for the control group, the dust exposure group and the silicosis group were 100.0%, 59.3% and 83.6%, respectively, and the classification accuracy was 81.9%. The discrimination effect is good. Based on the length of service, age, CC16 and SP-D levels, the Bayes discriminant analysis was used to establish a combined diagnostic discriminant model. The correct rates of the dust exposure and silicosis groups were 100.0% and 91.8%, respectively, and the classification accuracy was 94.0%. CONCLUSION: Bayes discriminant analysis combined with serum level of CC16 and SP-D is useful for the early diagnosis of occupational silicosis and improve the diagnostic accuracy.