Wang J, Ding L, Lyu Y J, Meng D, Liu H, Song L, Qi Z, Jia H X, Pei R X, Tian Z Q, Hao M, Wang J T
Department of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan 030001, China.
Somatological Hospital of Shanxi Medical University, Taiyuan 030001, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2021 Jun 10;42(6):1108-1112. doi: 10.3760/cma.j.cn112338-20200808-01045.
To investigate the diagnostic value of different vaginal micro-environmental factors in low-grade cervical intraepithelial neoplasia (CIN Ⅰ) and determine the optimal model in high-risk human papillomavirus (HR-HPV) infection. A total of 926 women, including 623 with normal cervical (NC) condition and 303 CINⅠ patients, had undergone pathological examinations, and were enrolled in the study. All the women were from a community previously established cohort. Vaginal cleanliness, pH, HO, β-glucuronidase, coagulase, sialidase, and leukocyte esterase (LE) were detected by the combined detection method aerobic vaginitis/bacterial vaginosis in vaginal secretions. HPV genotyping was performed by using the flow-through hybridization technology. The data were analyzed by SAS 9.2 and SPSS 23.0. The vaginal cleanliness, pH, sialidase, and LE were determined as the representative vaginal micro-environment factors by principal component analysis. Based on logistic regression theory to analyze the ROC curve, the results showed that the highest sensitivity was with pH value (76.2%), and the highest specificity was with sialidase (90.9%). The area under ROC curve were higher in combination detection modes of sialidase+LE (0.714), pH+sialidase+LE (0.719), vaginal cleanness+sialidase+LE (0.713) and pH+vaginal cleanness+sialidase+LE (0.709). According to HR-HPV infection status, the TOPSIS method was used to analyze the combined detection optimal model. Specifically, we found that the best diagnostic model was pH+sialidase +LE (=0.585) in the HR-HPV positive group and vaginal cleanness+sialidase+LE (=0.641) in the negative group. The combined detection of vaginal microenvironment factors could be used for auxiliary diagnosis for CINⅠ. It would be more effective when detecting pH, sialidase, and LE in HR-HPV positive women while vaginal cleanness, sialidase, and LE in HR-HPV negative women at the same time.
探讨不同阴道微环境因素在低级别宫颈上皮内瘤变（CINⅠ）中的诊断价值，并确定高危型人乳头瘤病毒（HR-HPV）感染的最佳模型。本研究共纳入926名女性，其中623名宫颈情况正常（NC），303名CINⅠ患者，均接受了病理检查。所有女性均来自一个先前建立的社区队列。采用需氧性阴道炎/细菌性阴道病联合检测方法检测阴道分泌物中的阴道清洁度、pH值、过氧化氢（HO）、β-葡萄糖醛酸酶、凝固酶、唾液酸酶和白细胞酯酶（LE）。采用流氏杂交技术进行HPV基因分型。数据采用SAS 9.2和SPSS 23.0进行分析。通过主成分分析确定阴道清洁度、pH值、唾液酸酶和LE为代表性阴道微环境因素。基于逻辑回归理论分析ROC曲线，结果显示，敏感性最高的是pH值（76.2%），特异性最高的是唾液酸酶（90.9%）。唾液酸酶+LE（0.714）、pH+唾液酸酶+LE（0.719）、阴道清洁度+唾液酸酶+LE（0.713）和pH+阴道清洁度+唾液酸酶+LE（0.709）联合检测模式的ROC曲线下面积较高。根据HR-HPV感染状态，采用TOPSIS法分析联合检测最佳模型。具体而言，我们发现HR-HPV阳性组最佳诊断模型为pH+唾液酸酶+LE（=0.585），阴性组为阴道清洁度+唾液酸酶+LE（=0.641）。阴道微环境因素联合检测可用于CINⅠ的辅助诊断。同时检测HR-HPV阳性女性的pH值、唾液酸酶和LE，以及HR-HPV阴性女性的阴道清洁度、唾液酸酶和LE时，诊断效果更佳。
