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基于中国长沙高危型人乳头瘤病毒(HPV)分型预测宫颈高级别癌前病变风险

Predicting the risk of high-grade precancerous cervical lesions based on high-risk HPV typing in Changsha China.

作者信息

Xiao Yaling, Liu Rangjiao, Wang Shaobo, Wang Yuxiang, Miao Weimin, Chen Meiwei, Liu Xiaowen, Chen Yan, Wen Yongchun, Deng Zhongping, Dai Lizhong, Mao Zenghui, He Jun

机构信息

Hunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control, Changsha, China.

Changsha Hospital for Maternal & Child Health Care, Hunan Normal University, Changsha, China.

出版信息

BMC Womens Health. 2025 Jan 20;25(1):28. doi: 10.1186/s12905-025-03562-0.

DOI:10.1186/s12905-025-03562-0
PMID:39833893
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11749071/
Abstract

BACKGROUND

Persistent infection with high-risk human papillomavirus (HPV) is a significant risk factor for cervical cancer. HPV typing and cytology are conducted in women of appropriate age to assess the risk of cervical lesions and to guide the need for further diagnostic procedures such as colposcopy, cervical biopsy, or treatment. This article explores methods to predict the risks of high-grade precancerous cervical lesions based on high-risk HPV typing.

METHODS

We conducted a retrospective analysis of HPV typing data from 158,565 women, including 19,707 who underwent ThinPrep cytologic testing (TCT), 7,539 who had colposcopy examinations, and 4,762 who had biopsies. We evaluated the sensitivity, specificity, and risk parameters of high-grade lesions associated with high-risk HPV types.

RESULTS

(1) The overall prevalence of HPV infection was 17.89%, with the most prevalent types being HPV52 (4.44%), HPV58 (2.10%), HPV53 (1.96%), HPV81 (1.85%), HPV42 (1.75%), and HPV16 (1.44%). (2) The sensitivity and specificity of detecting high-grade lesions in TCT, colposcopy, and biopsy, based on high-risk HPV typing, demonstrated a strong linear correlation with the infection rate of each type. (3) HPV16 was confirmed to have a higher risk of CIN2 + in biopsies using a self-defined risk parameter. (4) The top five HPV types with the highest PPVs and pathogenicity risks in biopsies were HPV45, HPV16, HPV58, HPV33, and HPV18.

CONCLUSION

In Changsha, China, HPV52, HPV58, and HPV53 were the most prevalent and contributed significantly to high-grade lesions. After adjusting for infection rates, a self-defined risk parameter was proposed as a measure of the intrinsic risks of high-grade lesions associated with high-risk HPV types. Focused monitoring of prevalent high-risk HPV types such as HPV45, HPV16, HPV58, HPV33, and HPV18, which show the highest pathogenicity risks, is recommended in our region.

摘要

背景

高危型人乳头瘤病毒(HPV)持续感染是宫颈癌的一个重要风险因素。对适龄女性进行HPV分型和细胞学检查,以评估宫颈病变风险并指导是否需要进一步的诊断程序,如阴道镜检查、宫颈活检或治疗。本文探讨基于高危型HPV分型预测高级别宫颈前病变风险的方法。

方法

我们对158,565名女性的HPV分型数据进行了回顾性分析,其中19,707人接受了薄层液基细胞学检测(TCT),7,539人进行了阴道镜检查,4,762人进行了活检。我们评估了与高危型HPV相关的高级别病变的敏感性、特异性和风险参数。

结果

(1)HPV感染的总体患病率为17.89%,最常见的类型为HPV52(4.44%)、HPV58(2.10%)、HPV53(1.96%)、HPV81(1.85%)、HPV42(1.75%)和HPV16(1.44%)。(2)基于高危型HPV分型,TCT、阴道镜检查和活检中检测高级别病变的敏感性和特异性与每种类型的感染率呈强线性相关。(3)使用自定义风险参数,活检中证实HPV16发生CIN2+的风险更高。(4)活检中阳性预测值(PPV)和致病性风险最高的前五种HPV类型为HPV45、HPV16、HPV58、HPV33和HPV18。

结论

在中国长沙,HPV52、HPV58和HPV53最为常见,对高级别病变的贡献显著。在调整感染率后,提出了一个自定义风险参数,作为衡量与高危型HPV相关的高级别病变内在风险的指标。建议对本地区致病性风险最高的常见高危型HPV类型,如HPV45、HPV16、HPV58、HPV33和HPV18进行重点监测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/60f1b896dacd/12905_2025_3562_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/94fbdf642afa/12905_2025_3562_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/27155e33933f/12905_2025_3562_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/76fa78005d80/12905_2025_3562_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/60f1b896dacd/12905_2025_3562_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/94fbdf642afa/12905_2025_3562_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/839af9225c13/12905_2025_3562_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/364fbb32f4c2/12905_2025_3562_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/27155e33933f/12905_2025_3562_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/76fa78005d80/12905_2025_3562_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a273/11749071/60f1b896dacd/12905_2025_3562_Fig6_HTML.jpg

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