Wang Zhuofeng, Zhang Jiaqi, Wang Tian, Liu Zuodong, Zhang Wanxin, Sun Yuxin, Wu Xi, Shao Hua, Du Zhongjun
Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250062, Shandong Province, P.R. China.
Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, China.
iScience. 2024 May 8;27(6):109948. doi: 10.1016/j.isci.2024.109948. eCollection 2024 Jun 21.
This study aims to establish a scientific foundation for early detection and diagnosis of silicosis by conducting meta-analysis on the role of single biomarkers in independent diagnosis. The combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score, and diagnostic odds ratio (DOR) were 0.84 (95% confidence interval (CI): 0.77-0.90), 0.83 (95% CI: 0.78-0.88), 5.08 (95% CI: 3.92-6.59), 0.19 (95% CI: 0.13-0.27), 3.31 (95% CI: 2.88-3.74) and 27.29 (95% CI: 17.77-41.91), respectively. The area under the curve (AUC) was 0.90 (95% CI: 0.88-0.93). The Fagan plot shows a positive posterior probability of 82% and a negative posterior probability of 15%. This study establishes an academic basis for the swift identification, mitigation, and control of silicosis through scientific approaches. The assessed biomarkers offer precision and dependability in silicosis diagnosis, opening novel paths for early detection and intervention, thereby mitigating the disease burden associated with silicosis.
本研究旨在通过对单个生物标志物在矽肺病独立诊断中的作用进行荟萃分析，为矽肺病的早期检测和诊断奠定科学基础。综合敏感度（Sen）、特异度（Spe）、阳性似然比（PLR）、阴性似然比（NLR）、诊断分数和诊断比值比（DOR）分别为0.84（95%置信区间（CI）：0.77 - 0.90）、0.83（95%CI：0.78 - 0.88）、5.08（95%CI：3.92 - 6.59）、0.19（95%CI：0.13 - 0.27）、3.31（95%CI：2.88 - 3.74）和27.29（95%CI：17.77 - 41.91）。曲线下面积（AUC）为0.90（95%CI：0.88 - 0.93）。Fagan图显示阳性后验概率为82%，阴性后验概率为15%。本研究通过科学方法为矽肺病的快速识别、缓解和控制奠定了学术基础。所评估的生物标志物在矽肺病诊断中提供了准确性和可靠性，为早期检测和干预开辟了新途径，从而减轻了与矽肺病相关的疾病负担。
