Objective  To investigate and establish a prediction model of HPV infection in the genital tract of women undergoing health checkups in Chengdu.

Methods  Women who underwent occupational physical examination in three hospitals in Chengdu from March 2022 to March 2023 were selected as study subjects. The possible factors associated with genital tract HPV infection were collected. The study subjects were divided into the model group and validation group in a 7∶3 ratio, and divided into an infected group and a non-infected group according to the presence or absence of HPV infection. LASSO regression was used to screen the potential factors of HPV infection. Logistic regression model was used to establish a risk prediction model for the risk of HPV infection and to draw a nomogram graph The receiver operating characteristic (ROC) curve, area under curve (AUC), calibration curve and decision curve were used to assess the discrimination, calibration and clinical applicability of the risk prediction model.

Results  A total of 2,318 women undergoing health checkups were included and 481 (20.75%) were infected with HPV, of which 316 (65.70%) were single infections, 165 (34.30%) were multiple infections. 1,622 cases in the model group and 696 cases in the validation group. 341 cases were in the infected group and 1,281 cases were in the non-infected group in the model group. The LASSO and Logistic regression results showed that age [OR=0.955, 95%CI(0.912, 0.999)], number of births [OR=4.392, 95%CI(1.420, 13.583)], age at first sexual intercourse [OR=0.870, 95%CI(0.774, 0.979)], condom use [OR=0.314, 95%CI (0.109, 0.905)], number of sexual partners [OR=6.068, 95%CI(1.825, 20.177)], circumcision of sexual partners [OR=3.218, 95%CI(1.042, 9.936)], prevalence of sexually transmitted diseases [OR=3.476, 95%CI(1.071, 11.277)], inflammation of the genital tract [OR=3.526, 95%CI(1.185, 10.494)], and cervical columnar epithelial ectasia [OR=4.375, 95%CI(1.374, 13.934)] were the independent correlates of HPV infection in health checkup’s women (P<0.05).The results of ROC curve showed that the AUC of the predictive models in the model and validation groups were 0.913 [95%CI (0.866, 0.960)] and 0.880 [95% CI (0.818, 0.941)], respectively. The results of the H-L goodness-of-fit test for the column prediction models in both the model and validation groups were not statistically significant (P>0.05). The results of calibration curves showed that the prediction curves in the model group and validation group basically fitted the standard curve. The decision curve showed that when the risk probability thresholds of the model and validation groups were 0.05~0.90 and 0.05~0.78, respectively, the patient benefit was greater than 0.

Conclusion  The prevalence of HPV infection in the health checkups of women in Chengdu was 20.75%, which was mainly affected by age, number of births, age at first sexual intercourse, condom use, number of sexual partners, circumcision of sexual partners, prevalence of sexually transmitted diseases, inflammation of the genital tract, and cervical columnar epithelial ectasia. The risk prediction model for HPV infection in the female genital tract based on the above factors is valuable for clinical use.

1.Selinger C, Rahmoun M, Murall CL, et al. Cytokine response following perturbation of the cervicovaginal milieu during HPV genital infection[J]. Immunol Res, 2021, 69(3): 255-263. DOI: 10.1007/s12026-021-09196-2.

2.Lu X, Ji M, Wagner AL, et al. Willingness to pay for HPV vaccine among female health care workers in a Chinese nationwide survey[J]. BMC Health Serv Res, 2022, 22(1): 1324. DOI: 10.1186/s12913-022-08716-6.

3.Kops NL, Caierão J, Bessel M, et al. Behavioral factors associated with multiple-type HPV genital infections: data from a cross-sectional study in young women in Brazil[J]. Reprod Health, 2021, 18(1): 201. DOI: 10.1186/s12978-021-01244-2.

4.Costa AS, Gomes JM, Germani ACCG, et al. Knowledge gaps and acquisition about HPV and its vaccine among Brazilian medical students[J]. PloS One, 2020, 15(3): e0230058. DOI: 10.1371/journal.pone.0230058.

5.王卉, 雷英, 闫晶晶, 等. 重庆市万州区已婚女性HPV感染危险因素和预测模型构建及验证[J]. 中华医院感染学杂志, 2023, 33(2): 238-242. [Wang H, Lei  Y, Yan JJ, et al. Risk factors for HPV infection in married women of Wanzhou District, Chongqing, establishment of prediction model and its validation[J]. Chinese Journal of Nosocomiology, 2023, 33(2): 238-242.] DOI: 10.11816/cn.ni.2023-213055.

6.Niu J, Pan S, Wei Y, et al. Epidemiology and analysis of potential risk factors of high-risk human papillomavirus (HPV) in Shanghai China: a cross-sectional one-year study in non-vaccinated women[J]. J Med Virol, 2022, 94(2): 761-770. DOI: 10.1002/jmv.27453.

7.Helmkamp LJ, Szilagyi PG, Zimet G, et al. A validated modification of the vaccine hesitancy scale for childhood, influenza and HPV vaccines[J]. Vaccine, 2021, 39(13): 1831-1839. DOI: 10.1016/j.vaccine.2021.02.039.

8.Harrison SE, Yelverton V, Wang Y, et al. Examining associations between knowledge and vaccine uptake using the Human Papillomavirus Knowledge Questionnaire (HPV-KQ)[J]. Am J Health Behav, 2021, 45(5): 810-827. DOI: 10.5993/AJHB.45.5.2.

9.Clavé Llavall A, de Wildt G, Meza G, et al. Nurses' and teachers' perceived barriers and facilitators to the uptake of the Human Papilloma Virus (HPV) vaccination program in Iquitos, Peru: a qualitative study[J]. PloS One, 2021, 16(7): e0255218. DOI: 10.1371/journal.pone.0255218.

10.张梦培, 尹如铁, 李克敏, 等. 中国西部女性生殖道高危人乳头状病毒感染状况的Meta分析[J]. 中国循证医学杂志, 2019, 19(11): 1268-1275. [Zhang MP, Yin RT, Li KM, et al. The prevalence of high risk human papillomavirus of females in western China: a Meta-analysis[J]. Chinese Journal of Evidence-Based Medicine, 2019, 19(11): 1268-1275.] DOI: 10.7507/1672-2531.201905076.

11.赵塔娜, 曾茵茹, 王瑞, 等. 中国女性HPV感染危险因素的Meta分析[J]. 中国艾滋病性病, 2022, 28(11): 1334-1338. [Zhao TN, Zeng YR, Wang R, et al. Meta-analysis of risk factors for HPV infection in Chinese women[J]. Chinese Journal of AIDS & STD, 2022, 28(11): 1334-1338.] DOI: 10.13419/j.cnki.aids.2022.11.28.

12.洪艳, 程正兰, 汪俊丽. 马鞍山市12 935名妇女高危型HPV感染现状及影响因素[J]. 华南预防医学, 2022, 48(12): 1524-1526, 1530. [Hong Y,Cheng ZL, Wang JL. Status and influencing factors of high-risk HPV infection among 12 935 women in Maanshan City[J]. South China Journal of Preventive Medicine, 2022, 48(12): 1524-1526, 1530.] DOI: 10.12183/j.scjpm.2022.1524.

13.Isabirye A, Mbonye M, Asiimwe JB, et al. Factors associated with HPV vaccination uptake in Uganda: a multi-level analysis[J]. BMC Womens Health, 2020, 20(1): 145. DOI: 10.1186/s12905-020-01014-5.

14.Aimagambetova G, Babi A, Issa T, et al. What factors are associated with attitudes towards HPV vaccination among Kazakhstani women? Exploratory analysis of cross-sectional survey data[J]. Vaccines (Basel), 2022, 10(5): 824. DOI: 10.3390/vaccines10050824.

15.Chowdhury S, Ara R, Roy S, et al. Knowledge, attitude, and practices regarding human papillomavirus and its' vaccination among the young medical professionals and students of Bangladesh[J]. Clin Exp Vac Res, 2022, 11(1): 63-71. DOI: 10.7774/cevr.2022.11.1.63.

16.Rios Velazquez E, Hoebers F, Aerts HJ, et al. Externally validated HPV-based prognostic nomogram for oropharyngeal carcinoma patients yields more accurate predictions than TNM staging[J]. Radiother Oncol, 2014, 113(3): 324-330. DOI: 10.1016/j.radonc.2014.09.005.

17.Albosale AH, Mashkina EV. Association between promoter polymorphisms of IL-1B, IL-4 and IL-6 Genes and a viral load infected women with human papillomavirus[J]. J Reprod Infertil, 2021, 22(2): 92-102. DOI: 10.18502/jri.v22i2.5794.

18.Riza E, Karakosta A, Tsiampalis T, et al. Knowledge, attitudes and perceptions about cervical cancer risk, prevention and human papilloma virus (HPV) in vulnerable women in Greece[J]. Int J Environ Res Public Health, 2020, 17(18): 6892. DOI: 10.3390/ijerph17186892.

19.Bogani G, Sopracordevole F, Di Donato V, et al. High-risk HPV-positive and-negative high-grade cervical dysplasia: analysis of 5-year outcomes[J]. Gynecol Oncol, 2021, 161(1): 173-178. DOI: 10.1016/j.ygyno.2021.01.020.

20.Gopalani SV, Sedani AE, Janitz AE, et al. Barriers and factors associated with HPV vaccination among American Indians and Alaska natives: a systematic review[J]. J Commun Health, 2022, 47(3): 563-575. DOI: 10.1007/s10900-022-01079-3.

21.Olarewaju VO, Jafflin K, Deml MJ, et al. The youth attitudes about vaccines (YAV-5) scale: adapting the parent attitudes about childhood vaccines short scale for use with youth in German, French, and Italian in Switzerland, exploratory factor analysis and mokken scaling analysis[J]. Hum Vaccin Immunother, 2021, 17(12): 5183-5190. DOI: 10.1080/21645515.2021.1980314.

22.Bogani G, Lalli L, Sopracordevole F, et al. Development of a nomogram predicting the risk of persistence/recurrence of cervical dysplasia[J]. Vaccines (Basel), 2022, 10(4): 579. DOI: 10.3390/vaccines10040579.

23.孟令昊, 胥秋艳, 李科, 等. 1990—2019年中国女性宫颈癌疾病负担变化的分析[J]. 中国循证医学杂志, 2021, 21(6): 648-653. [Meng LH, Xu QY, Li K, et al. The burden of disease of Chinese females cervical cancer from 1990 to 2019[J]. Chinese Journal of Evidence-Based Medicine, 2021, 21(6): 648-653.] DOI: 10.7507/1672-2531.202101091.

24.Kotani K, Iwata A, Kukimoto I, et al. Nomogram for predicted probability of cervical cancer and its precursor lesions using miRNA in cervical mucus, HPV genotype and age[J]. Sci Rep, 2022, 12(1):16231. DOI: 10.1038/s41598-022-19722-3.