Liu Hua-Mei, Zhang Fan, Cai Heng-Yun, Lv Yu-Mei, Pi Meng-Yuan
Department of Gynecology and Obstetrics, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.
Department of Clinical Laboratory, Xiangyang Hospital of Integrated Chinese and Western Medicine, Xiangyang, Hubei, 441004, People's Republic of China.
Int J Womens Health. 2024 Oct 30;16:1765-1774. doi: 10.2147/IJWH.S479836. eCollection 2024.
High-risk human papillomavirus (HR-HPV) is a significant risk factor for cervical precancerous lesions and cancer. This study aimed to investigate the relationship between vaginal microecology and HR-HPV infection and to evaluate the clinical applicability of vaginal microecology in predicting HR-HPV infection.
Overall, 2000 women with simultaneously detected vaginal discharge and cervical HPV were selected between March 2022 and March 2023, including 241 and 1759 cases in the HR-HPV positive and HPV negative groups, respectively.
No significant differences were found in age, vulvovaginal candidiasis, trichomonas vaginitis, and β-N-acetylglucosaminosidase between the two groups (P>0.05). Significant differences were observed in deficiency, bacterial vaginitis (BV), aerobic vaginitis (AV), glucuronidase (GUS), sialidase (SNA), and leukocyte esterase (LE) between the two groups (P<0.05). In the multivariate logistic regression equation, deficiency, BV, AV, SNA, LE, and GUS were risk factors for HR-HPV infection (P<0.05). Three prediction models, namely, logistic regression, decision tree, and random forest, were established to rank the importance of the predictors. BV ranked first among the three prediction models. The logistic regression model demonstrated the highest accuracy in predicting the risk of HR-HPV infection. The calibration curve of the logistic regression model showed a strong correlation between the predicted and actual probabilities, and decision curve analysis revealed that the prediction model had good clinical applicability.
Overall, vaginal microecology imbalance was closely associated with cervical HR-HPV infection, particularly BV and AV. The logistic regression model for the risk of HR-HPV infection based on six predictive factors (BV, AV, LE, SNA, deficiency, and GUS) had good accuracy and clinical applicability.
高危型人乳头瘤病毒（HR-HPV）是宫颈上皮内瘤变及宫颈癌的重要危险因素。本研究旨在探讨阴道微生态与HR-HPV感染之间的关系，并评估阴道微生态在预测HR-HPV感染方面的临床适用性。
选取2022年3月至2023年3月期间同时检测阴道分泌物和宫颈HPV的2000例女性，其中HR-HPV阳性组241例，HPV阴性组1759例。
两组在年龄、外阴阴道假丝酵母菌病、滴虫性阴道炎及β-N-乙酰氨基葡萄糖苷酶方面差异无统计学意义（P>0.05）。两组在乳酸缺乏、细菌性阴道病（BV）、需氧菌性阴道炎（AV）、葡萄糖醛酸酶（GUS）、唾液酸酶（SNA）及白细胞酯酶（LE）方面差异有统计学意义（P<0.05）。在多因素logistic回归方程中，乳酸缺乏、BV、AV、SNA、LE及GUS是HR-HPV感染的危险因素（P<0.05）。建立了logistic回归、决策树和随机森林三种预测模型，对预测因子的重要性进行排序。BV在三种预测模型中均排名第一。logistic回归模型在预测HR-HPV感染风险方面准确性最高。logistic回归模型的校准曲线显示预测概率与实际概率之间有很强的相关性，决策曲线分析显示该预测模型具有良好的临床适用性。
总体而言，阴道微生态失衡与宫颈HR-HPV感染密切相关，尤其是BV和AV。基于六个预测因素（BV、AV、LE、SNA、乳酸缺乏和GUS）建立的HR-HPV感染风险logistic回归模型具有良好的准确性和临床适用性。
