基于阴道微环境构建老年宫颈癌患者预后风险预测模型及验证

doi:10.3969/j.issn.1003-9198.2026.05.005

摘要/Abstract

摘要： 目的探讨老年宫颈癌患者阴道微环境变化特征,构建老年宫颈癌患者预后风险预警模型并分析其临床应用价值。方法选取2018年1月至2021年1月南京医科大学附属妇产医院收治的129例老年宫颈癌患者作为训练集,依据疗效评估将其分为预后良好组(71例)和预后不良组(58例)。另选取2021年2月至2022年8月收治的76例老年宫颈癌患者作为验证集。采集患者的阴道分泌物和宫颈上皮细胞,分析高危型人乳头瘤病毒(HR-HPV)感染、阴道微环境变化与宫颈癌患者预后的关系。采用多因素logistic回归分析筛选老年宫颈癌患者预后的危险因素,构建风险预测模型;运用ROC曲线和Hosmer-Lemeshow(H-L)检验评价模型的诊断效能。结果 HR-HPV感染组与未感染组间阴道pH＞4.5、乳酸杆菌少量/无比例,白细胞酯酶、凝固酶、β-葡萄糖醛酸酶、念珠菌阳性率差异具有统计学意义(P<0.05);宫颈癌预后不良组与预后良好组阴道pH＞4.5、乳酸杆菌少量/无比例,过氧化氢(H₂O₂)、白细胞酯酶、唾液酸苷酶、凝固酶、β-葡萄糖醛酸酶、念珠菌、解脲脲原体、沙眼衣原体、加德纳菌阳性率以及HR-HPV感染率比较,差异均具有统计学意义(P<0.05或P<0.01);多因素logistic回归分析显示:阴道pH>4.5、H₂O₂阳性、乳酸杆菌少量/无、解脲脲原体阳性、沙眼衣原体阳性以及HR-HPV感染是老年宫颈癌患者预后不良的独立风险因素。训练集模型AUC为0.855(95%CI:0.782~0.911,P<0.001),灵敏度和特异度分别为94.83%、69.01%;验证集AUC为0.864(95%CI:0.792~0.918,P<0.001),灵敏度和特异度分别为89.66%、74.65%;且训练集和验证集拟合均较好(χ²=4.640、1.827,P=0.326、0.767)。结论基于阴道微环境构建的老年宫颈癌患者预后风险预测模型诊断效果较好,可为临床制定老年宫颈癌患者预后的风险分层方案和干预策略提供参考依据。

关键词: 宫颈癌, 老年人, 高危型人乳头瘤病毒, 阴道微环境, 预后, 预测模型

Abstract: Objective To explore the characteristics of vaginal microenvironment changes in elderly patients with cervical cancer, and to construct and validate an early-warning prognostic risk model for elderly patients with cervical cancer. Methods A total of 129 elderly patients with cervical cancer admitted to the Affiliated Obstetrics and Gynecology Hospital of Nanjing Medical University from January 2018 to January 2021 were selected as the training set. An additional 76 elderly patients with cervical cancer admitted to the same hospital from February 2021 to August 2022 were selected as the validation set. Based on therapeutic efficacy evaluation, patients in the training set were divided into a good prognosis group (71 cases) and a poor prognosis group (58 cases). Vaginal secretions and cervical epithelial cells were collected from all patients to analyze the relationships among high-risk human papillomavirus (HR-HPV) infection, vaginal microenvironment changes and prognosis. Multivariate logistic regression was used to identify risk factors for prognosis and a risk predictive model was constructed. The diagnostic performance of the model was evaluated using the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow (H-L) test. Results The proportion of vaginal pH＞4.5, and the positive rates of Lactobacilli, leukocyte esterase, coagulase, β-glucuronidase and Candida in the HR-HPV infection group were significantly different from those in the non-infection group (P<0.05). The proportion of vaginal pH, ＞4.5, and the positive rates of H₂O₂, leukocyte esterase, sialidase, coagulase, β-glucuronidase, Lactobacilli, Candida, Ureaplasma urealyticum, Chlamydia trachomatis, Gardnerella pneumoniae, and HR-HPV in the poor prognosis group were statistically different compared with those in the good prognosis group (P<0.05 or P<0.01). Vaginal pH>4.5, H₂O₂ positivity, low levels of Lactobacilli, Ureaplasma urealyticum positivity, Chlamydia trachomatis positivity, and HR-HPV positivity were independent risk factors for poor prognosis of elderly patients with cervical cancer. The area under the curve (AUC) for the model predicting prognosis in the training set was 0.855(95%CI:0.782-0.911,P<0.001), with a sensitivity and specificity of 94.83% and 69.01%, respectively. In the validation set, the AUC was 0.864(95%CI:0.792-0.918,P<0.001), with a sensitivity and specificity of 89.66% and 74.65%, respectively. Goodness-of-fit tests indicated that the model fitted well both in the training set (χ²=4.640, P=0.326) and the validation set (χ²=1.827, P=0.767). Conclusions The prognostic risk predictive model for elderly patients with cervical cancer developed based on the vaginal microenvironment demonstrates excellent diagnostic performance. It can serve as a valuable reference for clinical risk stratification and the formulation of targeted intervention strategies for this population.

Key words: cervical cancer, aged, high risk human papillomavirus, vaginal microenvironment, prognosis, predictive model

中图分类号:

R 737.33

欧阳苏卉, 刘旸, 冯晓丹. 基于阴道微环境构建老年宫颈癌患者预后风险预测模型及验证[J]. 实用老年医学, 2026, 40(5): 457-463.

OUYANG Suhui, LIU Yang, FENG Xiaodan. Development and validation of a vaginal microenvironment-based predictive model for prognostic risk in elderly patients with cervical cancer[J]. Practical Geriatrics, 2026, 40(5): 457-463.

参考文献

[1] BRAY F, LAVERSANNE M, SUNG H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263.
[2] PERKINS R B, WENTZENSEN N, GUIDO R S, et al. Cervical cancer screening: a review[J]. JAMA, 2023, 330(6): 547-558.
[3] 李健芳, 冯勤梅, 孙晋瑞, 等. 阴道微生态与免疫微环境的变化对宫颈癌的影响[J]. 中国微生态学杂志, 2022, 34(4): 493-496, 封3.
[4] ZHANG W, YIN Y, JIANG Y, et al. Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer[J]. J Transl Med, 2024, 22(1): 396.
[5] 邹玉凤, 李铤, 赵月鸣, 等. 老年女性患者中HPV基因型的分布特征及意义[J]. 长春中医药大学学报, 2024, 40(12): 1397-1401.
[6] HUANG R, LIU Z, SUN T, et al. Cervicovaginal microbiome, high-risk HPV infection and cervical cancer: mechanisms and therapeutic potential[J]. Microbiol Res, 2024, 287: 127857.
[7] LIU Y, WANG S, LIU J, et al. Characteristics of vaginal microbiota in various cervical intraepithelial neoplasia: a cross-sectional study[J]. J Transl Med, 2023, 21(1): 816.
[8] WEI B, CHEN Y, LU T, et al. Correlation between vaginal microbiota and different progression stages of cervical cancer[J]. Genet Mol Biol, 2022, 45(2): e20200450.
[9] FANG B, LI Q, WAN Z, et al. Exploring the association between cervical microbiota and HR-HPV infection based on 16S rRNA gene and metagenomic sequencing[J]. Front Cell Infect Microbiol, 2022, 12: 922554.
[10] SANTELLA B, SCHETTINO M T, FRANCI G, et al. Microbiota and HPV: the role of viral infection on vaginal microbiota[J]. J Med Virol, 2022, 94(9): 4478-4484.
[11] NTULI L, MTSHALI A, MZOBE G, et al. Role of immunity and vaginal microbiome in clearance and persistence of human papillomavirus infection[J]. Front Cell Infect Microbiol, 2022, 12: 927131.
[12] LI J, JIN H, SUN Y, et al. Reconnoitering correlation between human papillomavirus infection-induced vaginal microecological abnormality and squamous intraepithelial lesion (SIL) progression[J]. BMC Womens Health, 2024, 24(1): 5.
[13] TAO H, ZENG D, CHEN W, et al. Focused ultrasound: a novel therapy for improving vaginal microecology in patients with high-risk HPV infection[J]. Int J Hyperthermia, 2023, 40(1): 2211276.
[14] LIU H M, ZHANG F, CAI H Y, et al. Cross-sectional study on the correlation between vaginal microecology and high-risk human papillomavirus infection: establishment of a clinical prediction model[J]. Int J Womens Health, 2024, 16: 1765-1774.
[15] LI L, DING L, GAO T, et al. Association between vaginal micro-environment disorder and cervical intraepithelial neoplasia in a community based population in China[J]. J Cancer, 2020, 11(2): 284-291.
[16] PAWAR K, ARANHA C. Lactobacilli metabolites restore E-cadherin and suppress MMP9 in cervical cancer cells[J]. Curr Res Toxicol, 2022, 3: 100088.
[17] ADAMOPOULOU M, AVGOUSTIDIS D, VOYIATJAKI C, et al. Impact of combined Mycoplasmataceae and HPV co-infection on females with cervical intraepithelial neoplasia and carcinoma[J]. J BUON, 2021, 26(4): 1313-1319.
[18] 谢建萍, 杨志红, 伊芳, 等. 宫颈高危型人乳头瘤病毒感染与阴道菌群及宫颈局部免疫功能的关系[J]. 中华医院感染学杂志, 2017, 27(10): 2336-2339.
[19] GARGIULO ISACCO C, BALZANELLI M G, GARZONE S, et al. Alterations of vaginal microbiota and Chlamydia trachomatis as crucial co-causative factors in cervical cancer genesis procured by HPV[J]. Microorganisms, 2023, 11(3): 662.
[20] YANG J, LONG X, LI S, et al. The correlation between vaginal pathogens and high-risk human Papilloma virus infection: a meta-analysis of case-control studies[J]. Front Oncol, 2024, 14: 1423118.
[21] 张颖婕, 刘佩意, 王贺, 等. 宫颈癌免费筛查女性生殖道沙眼衣原体感染与高危型人乳头瘤病毒感染的关联性研究[J]. 中国肿瘤, 2024, 33(4): 334-340.
[22] JIANG M, DING H, HE L, et al. Association between co-infection with Chlamydia trachomatis or Mycoplasma genitalium and cervical lesions in HPV-positive population in Hunan, China: a cross-sectional study[J]. Infect Agent Cancer, 2023, 18(1): 76.
[23] XIE L, LI Q, DONG X, et al. Investigation of the association between ten pathogens causing sexually transmitted diseases and high-risk human Papilloma virus infection in Shanghai[J]. Mol Clin Oncol, 2021, 15(1): 132.