Attribution of high-risk human papillomavirus genotypes in cervical lesions detected in a screening population in Shanxi Province, China

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Methods : Data from the records of cervical cancer screening programs for rural women in Shanxi Province wereretrospectively collected. Women who underwent primary HPV screeningbetween January 2014 and December 2019 were included. The attribution proportion of specific hrHPV types for different grades of cervical lesions was calculated by using the type contribution weighting and the proportional attribution methods to estimate the potential impact of HPV vaccines on CIN II+ lesions. Results : CIN II+ lesions were observed mainly with HPV16 (65.85%), HPV18 (10.20%), HPV58 (10.20%), HPV52 (7.98%), HPV31 (4.66%), HPV33 (4.43%), HPV51 (2.22%) and HPV56 (2.22%). A total of 97.42% of all CIN II+ lesions were attributed to HPV16, HPV18, HPV52, HPV58, HPV31, HPV33 and HPV35. A total of 75.4% (95% CI, 71.4-79.4) of CIN II+ lesions were attributable to HPV16/18, and 21.1% (95% CI, 17.4-25.1) were attributable to the 5 additional types (HPV31/33/45/52/58) covered by the 9-valent vaccine. Conclusions : The prevalence of hrHPV infection among women in Shanxi Province was high, and HPV16, HPV18, HPV58, HPV52, HPV31, HPV33 and HPV35 had the highest attributable fractions of CIN II+ lesions. The type-specific HPV prevalence and attribution proportion of cervical precancerous lesions should be taken into consideration in both clinical management and the design of preventive strategies. Biological sciences/Cancer Health sciences/Diseases Human papillomavirus HPV genotyping cervical intraepithelial neoplasia attribution proportion cervical cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Cervical cancer is a major problem because of its high incidence and mortality in low-income and middle-income settings 1 . In 2015, there were approximately 98,900 new cases and 30,500 deaths in China 2 . Persistent infection with high-risk human papillomavirus (hrHPV) is the main cause of cervical cancer and its precursors 3 . Approximately 15 HPV genotypes (HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV53, HPV56, HPV58, HPV59, HPV66, and HPV68) are known as high-risk genotypes and are associated with cervical cancer 4 . Different hrHPV genotypes are associated with different risks of cervical precancerous lesions and cancer 5,6 . Recent studies suggest that if HPV screening and HPV vaccination programs expand to 80%-100% coverage over the next 50 years, successful elimination of cervical cancer will be possible by the end of the century 7 . The ultimate goal of vaccines is to prevent the development of cervical cancer and precancerous lesions, and existing vaccines cannot prevent all hrHPV types. Before the immunization program in China is expanded, extensive research is urgently needed to predict the potential effect of existing vaccines in reducing cervical lesions. The preventive effect of the HPV vaccine on cervical cancer has been confirmed in several studies. A study 8 in the United States showed that HPV vaccination showed a concrete and substantial contribution to the decline in CIN II+. China has approved HPV vaccines since 2017 9 . Since 2009, Shanxi Province has provided free cervical cancer screening for rural women. A retrospective study was conducted to evaluate the genotype distribution of hrHPV and the attribution of different grades of cervical lesions to the disease in Shanxi Province to estimate the potential impact of the 9-valent HPV vaccine on CIN II + lesions to research HPV vaccines and provide data support. Methods Study population and ethics approval Data from the records of cervical cancer screening programs for rural women in Shanxi Province were retrospectively collected. Women who underwent primary HPV screening between January 2014 and December 2019 were included. After excluding people with hrHPV bulk tests and partial hrHPV typing, participants’ information with specific classifications from 2014 to 2019 was collected in the cervical cancer examination project database of rural women. This study was approved by the Ethics Committee of Shanxi Maternal and Child Health Hospital (approval number: IRB-KYYN-2021-001(5)). Screening procedures Basically, the screening procedure was performed according to the released ASCCP (American Colposcopy and Cervical Pathology Association) interim guidelines 10 . The participants underwent hrHPV genotyping as the primary test, and those who tested positive were further triaged by cytology and/or colposcopy. The management procedures for hrHPV-positive women were as follows: ① An immediate colposcopy referral was recommended for women with clinically suspicious cervical cancer or HPV16/18 infection. ② Other hrHPV-positive and HPV16/18-positive participants underwent cervical cytology or cervical iodoacetic acid (VIA/VILI) tests. If cervical cytology showed ASC-US (atypical squamous cells of undetermined significance), the patients underwent colposcopy. Those suspected by colposcopy or cervical smear underwent cervical biopsy and were referred for pathological examination. Pathological diagnostic reports of cervical precancerous lesions were based on the traditional classification, i.e., cervical intraepithelial neoplasia (CIN) I, CIN II, and CIN III, or a dichotomy, i.e., low-grade squamous intraepithelial lesions (LSIL) and high-grade squamous intraepithelial lesions (HSIL). Statistical Analyses We calculated the hrHPV type-specific prevalence. The prevalence of hrHPV was defined as a comparison of the number of positive cases of hrHPV to the total number of hrHPV cases that had complete genotyping results (six women were excluded because they received no further testing and dropped out from the screening program). GraphPad Prism 8.0.1.244 (GraphPad Software, San Diego, CA, USA) was used to evaluate the prevalence. The ORs with 95% confidence intervals (CIs) related to individual hrHPV types in the subcohort of patients with a single infection were analysed using logistic regression analysis. SPSS 22.0 (IBM, Armonk, NY, USA) was used to analyse the data. The calculations of attributable proportions of lesions caused by specific hrHPV types have been described previously 11,12 . Multiple hrHPV infections were defined as testing positive for two or more different types of hrHPV. To evaluate the contribution ratio of each genotype for individuals with single or multiple infections, the standard was set as the proportion of hrHPV genotypes that caused a single infection in the population with the same pathological grade 13 . Since 2014, the 9-valent HPV vaccine has been approved to provide protection against HPV6, HPV11, HPV16, HPV18, HPV31, HPV33, HPV45, HPV52 and HPV58 14 . To estimate the potential protective effects of the 9-valent HPV vaccine on CIN II + lesions, hrHPV classification data were divided into three categories: HPV16/18, HPV31/33/45/52/58, and other high-risk types (HPV35/39/51//53/56/59/66/68). Currently, the bivalent HPV vaccine protects against hrHPV types 16 and 18, the quadrivalent HPV vaccine protects against HPV types 6 and 11 and 16 and 18, and the nine-valent HPV vaccine protects against infections with nine HPV types: 6, 11, 16, 18, 31, 33, 45, 52 and 58 15 . The 95% confidence interval (CI) was determined using the Wilson scoring method. When describing the sociodemographic characteristics of the participants, we used three age groups: 35–40 years, 41–50 years and 51–64 years. We classified educational level as junior high school and below, high school and technical secondary school or above. Whether the participants had a history of cervical cancer screening was also evaluated. We used the Pearson X 2 test to assess the association between hrHPV type and demographic characteristics. A p value < 0.05 was considered statistically significant. Results Screening results of the study population In total, 111,353 women underwent HPV primary screening between January 2014 and December 2019 according to the registry records. Among them, 15,605 (14.01%) participants were hrHPV positive, including 4,522 women who had complete genotyping results. Six women were excluded because they received no further testing and dropped out from the screening program. Finally, 4,516 patients with a median age of 47.89 years (range, 47.67–48.11 years) were included in the present study, and 1,431 (31.69%) of them underwent a cervical biopsy. According to the pathological examination results, 451 (451/4,516, 9.99%) women had CIN II + lesions, including four with CIN II, three with CIN III, 403 with HSIL, four with AIS, and thirty-seven with cervical cancer; 396 (396/4516, 8.77%) women had CIN I or LSIL (Fig. 1 ). HPV genotype distribution in cervical lesions Of the 4,516 women who were positive for hrHPV revealed by complete genotyping tests, 4071 (90.15%) had single infections, and 445 (9.85%) had multiple infections. The proportions of multiple infections in women with no detected lesions, CIN I or LSIL, and CIN II + were 81.24%, 8.77%, and 9.99%, respectively. In the entire cohort, HPV16 (27.81%), HPV52 (16.54%), HPV58 (12.11%), HPV18 (8.79%), and HPV53 (6.36%) were the most common genotypes. The distribution pattern differed between different subgroups. Notably, HPV16 was the only genotype that showed an upward trend in infection prevalence from negative lesions (20.99%) to CIN I or LSIL (47.73%), then to CIN II+ (65.85%), while the other hrHPV types only showed modest differences between groups or even the lowest prevalence in the CIN II + subgroup. In the CIN II + subgroup ( N = 451), HPV16 was the predominant type, with a positive rate of 65.85%, followed by HPV18 (10.20%), HPV58 (10.20%), HPV52 (7.98%), and HPV31 (4.66%). These prevalent HPV subtypes were predominantly identified as single infections in CIN II + patients, while less prevalent subtypes, such as HPV51, HPV53, HPV68, HPV59, HPV45, and HPV39, were mainly found in women with multiple infections (Fig. 2 ). Type-specific risk of CIN II + lesions HPV subtypes have been found to vary in carcinogenic properties, and HPV16 and HPV18 are the most robust subtypes 16,17 . This may in part explain the different distribution patterns of individual hrHPV subtypes among different subgroups of cervical lesions. To estimate the hrHPV type-specific risk of CIN II+, we analysed the ORs related to individual hrHPV types in the subcohort of patients with single infections ( N = 4,071). There were 399 CIN II + cases in this subcohort. HPV39, HPV45, and HPV68 were not included because they did not cause any single infections. Among the 12 hrHPV subtypes analysed, as expected, HPV16 and HPV18 showed the highest risks for CIN II+, followed by HPV31, HPV33, and HPV58, while HPV51, HPV59, and HPV53 were ranked as the three types with the lowest risks (Fig. 3 ). The attributable proportions of different grades of cervical lesions in hrHPV The prevalence of lesions attributed to different hrHPV types was low when weighting multi-infection lesions. A total of 46.94% of CIN I cases and 65.44% of CIN II + cases were attributed to HPV16. In total, HPV16, HPV18, HPV52, and HPV58 combined caused 77.70% of all CIN I lesions. A total of 97.42% of all CIN II + lesions were attributed to HPV16, HPV18, HPV52, HPV58, HPV31, HPV33 and HPV35 combined (Table 1 ). Table 1 Distribution and attributable proportion of hrHPV genotypes in different grades of cervical lesions hrHPV Genotypes CIN I ( N = 396) CIN II+ ( N = 451) N %* Single Infection Attributable Proportion (%) # N %* Single infection Attributable Proportion (%) # Any type 396 - 343 100.00 451 - 399 100.00 16 189 47.73 165 46.94 297 65.85 267 65.44 18 69 17.42 57 15.87 46 10.20 38 9.30 31 6 1.52 3 0.81 21 4.66 11 3.38 33 19 4.80 15 4.02 20 4.43 12 3.12 35 12 3.03 5 1.50 8 1.77 5 1.21 39 7 1.77 5 1.59 1 0.22 0 0.00 45 5 1.26 5 1.26 1 0.22 0 0.00 51 21 5.30 8 3.45 10 2.22 2 0.72 52 35 8.84 26 7.65 36 7.98 28 6.75 53 17 4.29 12 3.67 6 1.33 1 0.24 56 12 3.03 7 2.18 10 2.22 3 0.91 58 34 8.59 23 7.24 46 10.20 29 8.22 59 8 2.02 4 1.39 4 0.89 1 0.23 66 6 1.52 3 0.89 4 0.89 2 0.48 68 13 3.28 5 1.54 5 1.11 0 0.00 Note: *Women with multiple HPV types detected are counted to each type, and therefore counted more than once; # Proportion of multiple attributable fraction and number of single infection within hrHPV positive women. Using the proportional attribution method to estimate the potential impact of the 9-valent HPV vaccine on CIN II + lesions in this study, 75.4% (95% CI, 71.4–79.4) of CIN II + lesions were attributable to HPV16/18, 21.1% (95% CI, 17.4–25.1) to the 5 additional types (HPV31/33/45/52/58) covered by the candidate 9-valent vaccine, and 3.5% (95% CI, 2.0-5.7) of CIN II + lesions were attributable to hrHPV types not covered by the 9-valent vaccine (Fig. 4 ). HPV16/18 was responsible for the largest percentage of CIN II + lesions across all age groups (Table 2 ). Among 35- to 40-year-olds, HPV16/18 attribution was 81.6%. The attribution was lowest (72.2%) in the age group of 41- to 50-year-olds. Conversely, the proportion of CIN II + lesions attributable to HPV31/33/45/52/58 was notably greater among women aged 41 to 50 years in comparison to younger age groups. There was no significant difference in the distribution of HPV16/18 or HPV31/33/45/52/58 types based on educational level among women with CIN II+. In individuals without a history of cervical cancer screening, HPV16/18 was responsible for the majority of CIN II + lesions. Nonetheless, the proportion of CIN II + lesions attributable to HPV31/33/45/52/58 and other high-risk types was significantly higher among women with a history of cervical cancer screening than among those without (Table 2 ). Table 2 HPV type attribution among women diagnosed with CIN II+, stratified by select characteristics Basic features 16/18 31/33/45/52/58 Other high-risk types a N % (95%CI) P N % (95%CI) P N % (95%CI) P Total 340 75.4 (71.1–79.3) 95 21.1 (17.4–25.1) 16 3.5 (2.0-5.7) Age (years) 0.203 0.411 0.455 35–40 80 81.6 (72.5–88.7) 16 16.3 (9.6–25.2) 2 2.0 (0.2–7.2) 41–50 148 72.2 (65.5–78.2) 47 22.9 (17.4–29.3) 10 4.9 (2.4–8.8) 51–64 112 75.7 (67.9–82.3) 32 21.6 (15.3–29.1) 4 2.7 (0.7–6.8) Educational Level 0.806 0.789 0.245 Junior middle school and below 237 75.7 (70.6–80.4) 67 21.4 (17.0-26.4) 9 2.9 (1.3–5.4) High school or technical secondary school or above 103 74.6 (66.5–81.7) 28 20.3 (13.9–28.0) 7 5.1 (2.1–10.2) History of cervical cancer screening 0.011 0.044 0.142 Yes 140 69.7 (62.8–75.9) 51 25.4 (19.5–32.0) 10 5.0 (2.4-9.0) No 200 80.0 (74.5–84.8) 44 17.6 (13.1–22.9) 6 2.4 (0.9–5.2) Note: a,Other high-risk types include HPV35/39/51/53/56/59/66/68. Abbreviations: CIN II+, cervical intraepithelial neoplasia grades 2. Discussion This study described the distribution of hrHPV types among different grades of cervical lesions and their attribution proportions among women in Shanxi Province, China. In our study, CIN II + lesions occurred mainly with HPV16 (65.85%), HPV18 (10.20%), HPV58 (10.20%), HPV52 (7.98%), HPV31 (4.66%), HPV33 (4.43%), HPV51 (2.22%) and HPV56 (2.22%). HPV58, HPV52, HPV31, and HPV33 accounted for 27.27% of CIN II + lesions. Consistent with previous studies 18–20 , HPV16, HPV52, HPV58, HPV33, HPV31 and HPV18 were the main genotypes in HSIL + patients. A European study 21 analysed the difference in the prevalence of HPV types between HSIL and invasive cervical cancer, which showed that the most common types of HPV in women with HSIL were HPV16/33/31 and those in women with cervical cancer were HPV16/18/45. In our study, the two with the highest rate of CIN II + lesions were also HPV16 and HPV18. However, HPV45 had the lowest incidence. The risk of progression and disease contribution varied by individual HPV genotype 22 . To exclude the influence of the varied prevalence of specific HPV genotypes, we introduced the absolute risk to estimate HPV risks for CIN II+. Our findings revealed that HPV16, HPV18, HPV31, HPV33, HPV58, HPV35, HPV52, HPV56, and HPV66 often carried a high immediate risk for CIN II+ (≥ 4%). This is consistent with previous research 23 that reported the risk ratio for individuals at high risk of progressing to CIN III; seven HPV types (HPV16, HPV18, HPV31, HPV33, HPV35, HPV52 and HPV58) showed a high risk of progression. Considering the incidence and carcinogenic potential of different genotypes, we used attribution to explore the genotype distribution of hrHPV. The prevalence of lesions attributed to different hrHPV types was low when weighting multi-infection lesions. A global 24 study on HPV genotypes and hrHPV DNA-based screening tests and protocols focused on HPV16, HPV18, and HPV45. In our study, the two with the highest attribution rate of CIN II + lesions were also HPV16 and HPV18. However, HPV52, HPV58, HPV31, HPV33 and HPV35 were often detected more frequently than HPV45 in CIN II + lesions. Consistent with previous conclusions 25 , HPV16, HPV52, HPV58, HPV31 and HPV33 were more common in women with cervical lesions in eastern China. A study 26 showed that adding HPV35 to the vaccine can prevent a small subset of CIN III and SCC, with a greater potential impact on CIN III + in black women. Similarly, based on our cross-sectional study, HPV35 may deserve special attention in addition to HPV16, HPV18, HPV52, HPV58, HPV31 and HPV33. The distribution of specific HPV genotypes in the general population and in patients with cervical lesions is critical to developing precise CC prevention strategies 11,27 . In a 20-year nationwide study 28 , the incidence of severe cervical precancerous lesions (CIN III and AIS) as well as cervical cancer (squamous cell types) decreased after the implementation of the national multicohort HPV vaccination program in Denmark. In our data, we analysed the potential impact on CIN II + lesions from candidates for the 9-valent HPV vaccine. HPV16/18 accounted for 75.4% of CIN II + lesions. The additional 5 HPV types in the 9-valent vaccine, HPV31/33/45/52/58, contributed to 21.1% of CIN II + cases. Similar to a global study 29 , the 9-valent HPV vaccine can prevent most CIN II + cases in Shanxi Province. In our CIN II + population, HPV35 was more common than HPV45, and adding HPV35 to current HPV vaccines can prevent a small portion of CIN II + cases. This study is the first large-scale, population-based study among rural women in Shanxi Province. However, this study has some limitations. The data were acquired from an official records system, and the original data cannot be backtracked. This is one of the few studies to evaluate the predictive value of type-specific hrHPV detection of cervical cancer and precancerous lesions in a Chinese cohort. In our study, only 4% of the population underwent full genotyping, and more prospective studies with larger sample sizes are needed to determine the specific hrHPV genotypes that cause CIN II+. In the work of Baay M.F.D 30 , 13% of cancers were HPV negative. The analysis of the incidence of CIN II + attributed to individual HPV types was novel, but the contribution of hrHPV may have been overestimated. Conclusions In summary, HPV16, HPV18, HPV52, and HPV58 were the most dominant high-risk genotypes in this population and accounted for 89.27% of all CIN II + lesions. In addition to HPV16, HPV18, HPV52, HPV58, HPV31 and HPV33, HPV35 may deserve special attention. Given the differing risks attributed to different hrHPV types, we propose that health care workers should pay attention to the specific hrHPV types in cervical lesions during screening in the rural Chinese population. Our data suggest that screening tests and protocols based on specific types of HPV should focus on HPV16, HPV18, HPV52, HPV31, HPV33, HPV35 and HPV58. Additionally, we assessed the potential impacts of the 9-valent vaccine on cervical cancer and precancer. The 9-valent vaccine can reduce the risk of most HPV-related cervical cancers and precancerous lesions in rural women under 40 years of age in Shanxi. Therefore, research on the global prevalence and causes of different hrHPV types may not be entirely relevant to the female population in China. It is important to take into account the distinctive characteristics of cervical HPV infections in China when developing HPV screening techniques and vaccines. Taking into account the prevalence of combined HPV genotypes and the proportion of high-grade cervical intraepithelial neoplasia lesions attributed to these genotypes may provide valuable insights for developing more accurate and efficient cervical cancer screening programs tailored to specific regions. Our findings may help health care authorities assess the impact of vaccination programs and inform the application of tailored HPV vaccines in Shanxi Province. Abbreviations HPV, human papillomavirus. hrHPV, high-risk human papillomavirus. ACS, American Cancer Society. OR, odds ratio. CI, confidence interval. ASCCP: American Society for Colposcopy and Cervical Pathology. ASCP: American Society for Clinical Pathology. ICC, invasive cervical carcinoma. AIS, adenocarcinoma in situ. Declarations Data sharing statement The datasets generated during the current study are not yet publicly available due to privacy concerns and ongoing additional research. Data can be made available for peer review upon reasonable request by contacting the corresponding author. Consent for publication Not applicable. Funding The National Natural Science Foundation of China (82072891). The Project of the Central Government Guiding Local in Shanxi Province (YDZJSX2022B012) Basic Research Program of Shanxi Province (202103021224352) Shanxi Maternal and Child Health Hospital (2021009). Author Contribution RS and JC conceived and designed the study, having full access to all of the data in the study and taking responsibility for the content of the manuscript. RS and ZHW analyzed the data, took responsibility for the accuracy of the data analysis and wrote the first draft of the manuscript. ZHW and MZ reviewed the paper. RS, WJQ, JC, ZHW, and MZ contributed to the interpretation of the data and clinical inputs. All authors were involved in the revision of the manuscript for important intellectual content and approved the final version to be published. 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Cite Share Download PDF Status: Published Journal Publication published 02 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 01 Apr, 2025 Reviews received at journal 29 Mar, 2025 Reviewers agreed at journal 19 Mar, 2025 Reviews received at journal 26 Sep, 2024 Reviewers agreed at journal 17 Sep, 2024 Reviewers invited by journal 30 May, 2024 Editor assigned by journal 30 May, 2024 Editor invited by journal 27 May, 2024 Submission checks completed at journal 22 May, 2024 First submitted to journal 17 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4436179","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":309391942,"identity":"54d3a8f0-f42b-4a92-9053-e0fdea8b99b9","order_by":0,"name":"Ru Shi","email":"","orcid":"","institution":"Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ru","middleName":"","lastName":"Shi","suffix":""},{"id":309391943,"identity":"7a6ecc36-8192-4a9c-8117-dd58cead2a89","order_by":1,"name":"Wenjuan QI","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenjuan","middleName":"","lastName":"QI","suffix":""},{"id":309391945,"identity":"9e7ec06b-f983-4df0-858a-5e5b319755fb","order_by":2,"name":"Zehua Wang","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zehua","middleName":"","lastName":"Wang","suffix":""},{"id":309391947,"identity":"377b5d87-c0ac-48bb-8214-f2a3113ade4b","order_by":3,"name":"Jing Cai","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Cai","suffix":""},{"id":309391948,"identity":"e4b643fb-bee3-46aa-9392-b567fe942d2a","order_by":4,"name":"Min Zhao","email":"","orcid":"","institution":"Shanxi Provincial Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Zhao","suffix":""},{"id":309391949,"identity":"b9e64964-3615-4667-9d60-3bc5562d88cb","order_by":5,"name":"Zanhong Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBAC+wYGNhib8UFChQ1hLYxIWpgNHpxJI00Lm+TDtkOEtTCznz324OOO2sT+2e3XKhLYDjDwt3cn4NXCxpOXbjjzzPHEGXfOlN1I4LnDIHHm7Aa8WngYcsykeduO5TbcyEm7kSDxjMFAIhe/Fgn+NxAt84FaChIMDhPWYiABtqUmd8ON9GMMCQlEaXljJjmz7UD9xhs5zBIJB9J4CPrFvj/HTOJjW52x3I30hx9//rOR42/vxa8FCg4DMY8BiMVDjHIQqANi9gfEqh4Fo2AUjIIRBgCv405AsW2z3QAAAABJRU5ErkJggg==","orcid":"","institution":"Third Hospital of Shanxi Medical University, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zanhong","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-05-17 10:47:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4436179/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4436179/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-14228-0","type":"published","date":"2025-08-02T16:13:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57672874,"identity":"cf19e1fb-4783-4395-949a-efd990ac1c35","added_by":"auto","created_at":"2024-06-04 06:59:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":584736,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4436179/v1/d293131e788797b8e9c5d4dc.png"},{"id":57672875,"identity":"f3974eee-6304-4a26-999b-dc55a0ea9fdf","added_by":"auto","created_at":"2024-06-04 06:59:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1204105,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4436179/v1/e51bb6aad5361573022fc9b5.png"},{"id":57672873,"identity":"16a0c3a1-f0be-47c0-85b1-051a352f571d","added_by":"auto","created_at":"2024-06-04 06:59:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":617469,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4436179/v1/731fb6ad55eec8a579777d8a.png"},{"id":57673417,"identity":"2fd5fb69-d03d-4ec2-be4c-54adbb210444","added_by":"auto","created_at":"2024-06-04 07:07:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":670676,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4436179/v1/c64909eda7e3f9ba6fc5888c.png"},{"id":88268238,"identity":"3fa57a24-68ea-486f-9e22-91fefb3476b7","added_by":"auto","created_at":"2025-08-04 16:50:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3978435,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4436179/v1/454dcdf6-6143-4949-966d-cb8cbaffae3c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Attribution of high-risk human papillomavirus genotypes in cervical lesions detected in a screening population in Shanxi Province, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical cancer is a major problem because of its high incidence and mortality in low-income and middle-income settings\u003csup\u003e1\u003c/sup\u003e. In 2015, there were approximately 98,900 new cases and 30,500 deaths in China\u003csup\u003e2\u003c/sup\u003e. Persistent infection with high-risk human papillomavirus (hrHPV) is the main cause of cervical cancer and its precursors\u003csup\u003e3\u003c/sup\u003e. Approximately 15 HPV genotypes (HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV53, HPV56, HPV58, HPV59, HPV66, and HPV68) are known as high-risk genotypes and are associated with cervical cancer\u003csup\u003e4\u003c/sup\u003e. Different hrHPV genotypes are associated with different risks of cervical precancerous lesions and cancer \u003csup\u003e5,6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecent studies suggest that if HPV screening and HPV vaccination programs expand to 80%-100% coverage over the next 50 years, successful elimination of cervical cancer will be possible by the end of the century\u003csup\u003e7\u003c/sup\u003e. The ultimate goal of vaccines is to prevent the development of cervical cancer and precancerous lesions, and existing vaccines cannot prevent all hrHPV types. Before the immunization program in China is expanded, extensive research is urgently needed to predict the potential effect of existing vaccines in reducing cervical lesions. The preventive effect of the HPV vaccine on cervical cancer has been confirmed in several studies. A study\u003csup\u003e8\u003c/sup\u003e in the United States showed that HPV vaccination showed a concrete and substantial contribution to the decline in CIN II+. China has approved HPV vaccines since 2017\u003csup\u003e9\u003c/sup\u003e. Since 2009, Shanxi Province has provided free cervical cancer screening for rural women. A retrospective study was conducted to evaluate the genotype distribution of hrHPV and the attribution of different grades of cervical lesions to the disease in Shanxi Province to estimate the potential impact of the 9-valent HPV vaccine on CIN II\u0026thinsp;+\u0026thinsp;lesions to research HPV vaccines and provide data support.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and ethics approval\u003c/h2\u003e \u003cp\u003eData from the records of cervical cancer screening programs for rural women in Shanxi Province were retrospectively collected. Women who underwent primary HPV screening between January 2014 and December 2019 were included. After excluding people with hrHPV bulk tests and partial hrHPV typing, participants\u0026rsquo; information with specific classifications from 2014 to 2019 was collected in the cervical cancer examination project database of rural women. This study was approved by the Ethics Committee of Shanxi Maternal and Child Health Hospital (approval number: IRB-KYYN-2021-001(5)).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eScreening procedures\u003c/h2\u003e \u003cp\u003eBasically, the screening procedure was performed according to the released ASCCP (American Colposcopy and Cervical Pathology Association) interim guidelines\u003csup\u003e10\u003c/sup\u003e. The participants underwent hrHPV genotyping as the primary test, and those who tested positive were further triaged by cytology and/or colposcopy. The management procedures for hrHPV-positive women were as follows: ① An immediate colposcopy referral was recommended for women with clinically suspicious cervical cancer or HPV16/18 infection. ② Other hrHPV-positive and HPV16/18-positive participants underwent cervical cytology or cervical iodoacetic acid (VIA/VILI) tests. If cervical cytology showed ASC-US (atypical squamous cells of undetermined significance), the patients underwent colposcopy. Those suspected by colposcopy or cervical smear underwent cervical biopsy and were referred for pathological examination. Pathological diagnostic reports of cervical precancerous lesions were based on the traditional classification, i.e., cervical intraepithelial neoplasia (CIN) I, CIN II, and CIN III, or a dichotomy, i.e., low-grade squamous intraepithelial lesions (LSIL) and high-grade squamous intraepithelial lesions (HSIL).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eWe calculated the hrHPV type-specific prevalence. The prevalence of hrHPV was defined as a comparison of the number of positive cases of hrHPV to the total number of hrHPV cases that had complete genotyping results (six women were excluded because they received no further testing and dropped out from the screening program). GraphPad Prism 8.0.1.244 (GraphPad Software, San Diego, CA, USA) was used to evaluate the prevalence. The ORs with 95% confidence intervals (CIs) related to individual hrHPV types in the subcohort of patients with a single infection were analysed using logistic regression analysis. SPSS 22.0 (IBM, Armonk, NY, USA) was used to analyse the data.\u003c/p\u003e \u003cp\u003eThe calculations of attributable proportions of lesions caused by specific hrHPV types have been described previously\u003csup\u003e11,12\u003c/sup\u003e. Multiple hrHPV infections were defined as testing positive for two or more different types of hrHPV. To evaluate the contribution ratio of each genotype for individuals with single or multiple infections, the standard was set as the proportion of hrHPV genotypes that caused a single infection in the population with the same pathological grade\u003csup\u003e13\u003c/sup\u003e. Since 2014, the 9-valent HPV vaccine has been approved to provide protection against HPV6, HPV11, HPV16, HPV18, HPV31, HPV33, HPV45, HPV52 and HPV58\u003csup\u003e14\u003c/sup\u003e. To estimate the potential protective effects of the 9-valent HPV vaccine on CIN II\u0026thinsp;+\u0026thinsp;lesions, hrHPV classification data were divided into three categories: HPV16/18, HPV31/33/45/52/58, and other high-risk types (HPV35/39/51//53/56/59/66/68). Currently, the bivalent HPV vaccine protects against hrHPV types 16 and 18, the quadrivalent HPV vaccine protects against HPV types 6 and 11 and 16 and 18, and the nine-valent HPV vaccine protects against infections with nine HPV types: 6, 11, 16, 18, 31, 33, 45, 52 and 58\u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe 95% confidence interval (CI) was determined using the Wilson scoring method. When describing the sociodemographic characteristics of the participants, we used three age groups: 35\u0026ndash;40 years, 41\u0026ndash;50 years and 51\u0026ndash;64 years. We classified educational level as junior high school and below, high school and technical secondary school or above. Whether the participants had a history of cervical cancer screening was also evaluated. We used the Pearson X\u003csup\u003e2\u003c/sup\u003e test to assess the association between hrHPV type and demographic characteristics. A \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eScreening results of the study population\u003c/h2\u003e \u003cp\u003eIn total, 111,353 women underwent HPV primary screening between January 2014 and December 2019 according to the registry records. Among them, 15,605 (14.01%) participants were hrHPV positive, including 4,522 women who had complete genotyping results. Six women were excluded because they received no further testing and dropped out from the screening program. Finally, 4,516 patients with a median age of 47.89 years (range, 47.67\u0026ndash;48.11 years) were included in the present study, and 1,431 (31.69%) of them underwent a cervical biopsy. According to the pathological examination results, 451 (451/4,516, 9.99%) women had CIN II\u0026thinsp;+\u0026thinsp;lesions, including four with CIN II, three with CIN III, 403 with HSIL, four with AIS, and thirty-seven with cervical cancer; 396 (396/4516, 8.77%) women had CIN I or LSIL (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHPV genotype distribution in cervical lesions\u003c/h2\u003e \u003cp\u003eOf the 4,516 women who were positive for hrHPV revealed by complete genotyping tests, 4071 (90.15%) had single infections, and 445 (9.85%) had multiple infections. The proportions of multiple infections in women with no detected lesions, CIN I or LSIL, and CIN II\u0026thinsp;+\u0026thinsp;were 81.24%, 8.77%, and 9.99%, respectively. In the entire cohort, HPV16 (27.81%), HPV52 (16.54%), HPV58 (12.11%), HPV18 (8.79%), and HPV53 (6.36%) were the most common genotypes. The distribution pattern differed between different subgroups. Notably, HPV16 was the only genotype that showed an upward trend in infection prevalence from negative lesions (20.99%) to CIN I or LSIL (47.73%), then to CIN II+ (65.85%), while the other hrHPV types only showed modest differences between groups or even the lowest prevalence in the CIN II\u0026thinsp;+\u0026thinsp;subgroup. In the CIN II\u0026thinsp;+\u0026thinsp;subgroup (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;451), HPV16 was the predominant type, with a positive rate of 65.85%, followed by HPV18 (10.20%), HPV58 (10.20%), HPV52 (7.98%), and HPV31 (4.66%). These prevalent HPV subtypes were predominantly identified as single infections in CIN II\u0026thinsp;+\u0026thinsp;patients, while less prevalent subtypes, such as HPV51, HPV53, HPV68, HPV59, HPV45, and HPV39, were mainly found in women with multiple infections (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eType-specific risk of CIN II\u0026thinsp;+\u0026thinsp;lesions\u003c/h2\u003e \u003cp\u003eHPV subtypes have been found to vary in carcinogenic properties, and HPV16 and HPV18 are the most robust subtypes\u003csup\u003e16,17\u003c/sup\u003e. This may in part explain the different distribution patterns of individual hrHPV subtypes among different subgroups of cervical lesions. To estimate the hrHPV type-specific risk of CIN II+, we analysed the ORs related to individual hrHPV types in the subcohort of patients with single infections (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4,071). There were 399 CIN II\u0026thinsp;+\u0026thinsp;cases in this subcohort. HPV39, HPV45, and HPV68 were not included because they did not cause any single infections. Among the 12 hrHPV subtypes analysed, as expected, HPV16 and HPV18 showed the highest risks for CIN II+, followed by HPV31, HPV33, and HPV58, while HPV51, HPV59, and HPV53 were ranked as the three types with the lowest risks (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eThe attributable proportions of different grades of cervical lesions in hrHPV\u003c/h2\u003e \u003cp\u003eThe prevalence of lesions attributed to different hrHPV types was low when weighting multi-infection lesions. A total of 46.94% of CIN I cases and 65.44% of CIN II\u0026thinsp;+\u0026thinsp;cases were attributed to HPV16. In total, HPV16, HPV18, HPV52, and HPV58 combined caused 77.70% of all CIN I lesions. A total of 97.42% of all CIN II\u0026thinsp;+\u0026thinsp;lesions were attributed to HPV16, HPV18, HPV52, HPV58, HPV31, HPV33 and HPV35 combined (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution and attributable proportion of hrHPV genotypes in different grades of cervical lesions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ehrHPV\u003c/p\u003e \u003cp\u003eGenotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eCIN I (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;396)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eCIN II+ (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;451)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eInfection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAttributable\u003c/p\u003e \u003cp\u003eProportion (%)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e%*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003einfection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAttributable Proportion (%)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e65.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e65.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: *Women with multiple HPV types detected are counted to each type, and therefore counted more than once; \u003csup\u003e#\u003c/sup\u003eProportion of multiple attributable fraction and number of single infection within hrHPV positive women.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUsing the proportional attribution method to estimate the potential impact of the 9-valent HPV vaccine on CIN II\u0026thinsp;+\u0026thinsp;lesions in this study, 75.4% (95% CI, 71.4\u0026ndash;79.4) of CIN II\u0026thinsp;+\u0026thinsp;lesions were attributable to HPV16/18, 21.1% (95% CI, 17.4\u0026ndash;25.1) to the 5 additional types (HPV31/33/45/52/58) covered by the candidate 9-valent vaccine, and 3.5% (95% CI, 2.0-5.7) of CIN II\u0026thinsp;+\u0026thinsp;lesions were attributable to hrHPV types not covered by the 9-valent vaccine (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHPV16/18 was responsible for the largest percentage of CIN II\u0026thinsp;+\u0026thinsp;lesions across all age groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among 35- to 40-year-olds, HPV16/18 attribution was 81.6%. The attribution was lowest (72.2%) in the age group of 41- to 50-year-olds. Conversely, the proportion of CIN II\u0026thinsp;+\u0026thinsp;lesions attributable to HPV31/33/45/52/58 was notably greater among women aged 41 to 50 years in comparison to younger age groups. There was no significant difference in the distribution of HPV16/18 or HPV31/33/45/52/58 types based on educational level among women with CIN II+. In individuals without a history of cervical cancer screening, HPV16/18 was responsible for the majority of CIN II\u0026thinsp;+\u0026thinsp;lesions. Nonetheless, the proportion of CIN II\u0026thinsp;+\u0026thinsp;lesions attributable to HPV31/33/45/52/58 and other high-risk types was significantly higher among women with a history of cervical cancer screening than among those without (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHPV type attribution among women diagnosed with CIN II+, stratified by select characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBasic features\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e16/18\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e31/33/45/52/58\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eOther high-risk types\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e% (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e% (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.4 (71.1\u0026ndash;79.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.1 (17.4\u0026ndash;25.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.5 (2.0-5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.6 (72.5\u0026ndash;88.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.3 (9.6\u0026ndash;25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.0 (0.2\u0026ndash;7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.2 (65.5\u0026ndash;78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.9 (17.4\u0026ndash;29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.9 (2.4\u0026ndash;8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.7 (67.9\u0026ndash;82.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.6 (15.3\u0026ndash;29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.7 (0.7\u0026ndash;6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior middle school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.7 (70.6\u0026ndash;80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.4 (17.0-26.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.9 (1.3\u0026ndash;5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or technical secondary school or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.6 (66.5\u0026ndash;81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.3 (13.9\u0026ndash;28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.1 (2.1\u0026ndash;10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of cervical cancer screening\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.7 (62.8\u0026ndash;75.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.4 (19.5\u0026ndash;32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.0 (2.4-9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.0 (74.5\u0026ndash;84.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17.6 (13.1\u0026ndash;22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.4 (0.9\u0026ndash;5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote: a,Other high-risk types include HPV35/39/51/53/56/59/66/68. Abbreviations: CIN II+, cervical intraepithelial neoplasia grades 2.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study described the distribution of hrHPV types among different grades of cervical lesions and their attribution proportions among women in Shanxi Province, China. In our study, CIN II\u0026thinsp;+\u0026thinsp;lesions occurred mainly with HPV16 (65.85%), HPV18 (10.20%), HPV58 (10.20%), HPV52 (7.98%), HPV31 (4.66%), HPV33 (4.43%), HPV51 (2.22%) and HPV56 (2.22%). HPV58, HPV52, HPV31, and HPV33 accounted for 27.27% of CIN II\u0026thinsp;+\u0026thinsp;lesions. Consistent with previous studies\u003csup\u003e18\u0026ndash;20\u003c/sup\u003e, HPV16, HPV52, HPV58, HPV33, HPV31 and HPV18 were the main genotypes in HSIL\u0026thinsp;+\u0026thinsp;patients. A European study\u003csup\u003e21\u003c/sup\u003e analysed the difference in the prevalence of HPV types between HSIL and invasive cervical cancer, which showed that the most common types of HPV in women with HSIL were HPV16/33/31 and those in women with cervical cancer were HPV16/18/45. In our study, the two with the highest rate of CIN II\u0026thinsp;+\u0026thinsp;lesions were also HPV16 and HPV18. However, HPV45 had the lowest incidence.\u003c/p\u003e \u003cp\u003eThe risk of progression and disease contribution varied by individual HPV genotype\u003csup\u003e22\u003c/sup\u003e. To exclude the influence of the varied prevalence of specific HPV genotypes, we introduced the absolute risk to estimate HPV risks for CIN II+. Our findings revealed that HPV16, HPV18, HPV31, HPV33, HPV58, HPV35, HPV52, HPV56, and HPV66 often carried a high immediate risk for CIN II+ (\u0026ge;\u0026thinsp;4%). This is consistent with previous research\u003csup\u003e23\u003c/sup\u003e that reported the risk ratio for individuals at high risk of progressing to CIN III; seven HPV types (HPV16, HPV18, HPV31, HPV33, HPV35, HPV52 and HPV58) showed a high risk of progression.\u003c/p\u003e \u003cp\u003eConsidering the incidence and carcinogenic potential of different genotypes, we used attribution to explore the genotype distribution of hrHPV. The prevalence of lesions attributed to different hrHPV types was low when weighting multi-infection lesions. A global\u003csup\u003e24\u003c/sup\u003e study on HPV genotypes and hrHPV DNA-based screening tests and protocols focused on HPV16, HPV18, and HPV45. In our study, the two with the highest attribution rate of CIN II\u0026thinsp;+\u0026thinsp;lesions were also HPV16 and HPV18. However, HPV52, HPV58, HPV31, HPV33 and HPV35 were often detected more frequently than HPV45 in CIN II\u0026thinsp;+\u0026thinsp;lesions. Consistent with previous conclusions\u003csup\u003e25\u003c/sup\u003e, HPV16, HPV52, HPV58, HPV31 and HPV33 were more common in women with cervical lesions in eastern China. A study\u003csup\u003e26\u003c/sup\u003e showed that adding HPV35 to the vaccine can prevent a small subset of CIN III and SCC, with a greater potential impact on CIN III\u0026thinsp;+\u0026thinsp;in black women. Similarly, based on our cross-sectional study, HPV35 may deserve special attention in addition to HPV16, HPV18, HPV52, HPV58, HPV31 and HPV33.\u003c/p\u003e \u003cp\u003eThe distribution of specific HPV genotypes in the general population and in patients with cervical lesions is critical to developing precise CC prevention strategies\u003csup\u003e11,27\u003c/sup\u003e. In a 20-year nationwide study\u003csup\u003e28\u003c/sup\u003e, the incidence of severe cervical precancerous lesions (CIN III and AIS) as well as cervical cancer (squamous cell types) decreased after the implementation of the national multicohort HPV vaccination program in Denmark. In our data, we analysed the potential impact on CIN II\u0026thinsp;+\u0026thinsp;lesions from candidates for the 9-valent HPV vaccine. HPV16/18 accounted for 75.4% of CIN II\u0026thinsp;+\u0026thinsp;lesions. The additional 5 HPV types in the 9-valent vaccine, HPV31/33/45/52/58, contributed to 21.1% of CIN II\u0026thinsp;+\u0026thinsp;cases. Similar to a global study\u003csup\u003e29\u003c/sup\u003e, the 9-valent HPV vaccine can prevent most CIN II\u0026thinsp;\u003cb\u003e+\u003c/b\u003e\u0026thinsp;cases in Shanxi Province. In our CIN II\u0026thinsp;+\u0026thinsp;population, HPV35 was more common than HPV45, and adding HPV35 to current HPV vaccines can prevent a small portion of CIN II\u0026thinsp;+\u0026thinsp;cases.\u003c/p\u003e \u003cp\u003eThis study is the first large-scale, population-based study among rural women in Shanxi Province. However, this study has some limitations. The data were acquired from an official records system, and the original data cannot be backtracked. This is one of the few studies to evaluate the predictive value of type-specific hrHPV detection of cervical cancer and precancerous lesions in a Chinese cohort. In our study, only 4% of the population underwent full genotyping, and more prospective studies with larger sample sizes are needed to determine the specific hrHPV genotypes that cause CIN II+. In the work of Baay M.F.D\u003csup\u003e30\u003c/sup\u003e, 13% of cancers were HPV negative. The analysis of the incidence of CIN II\u0026thinsp;+\u0026thinsp;attributed to individual HPV types was novel, but the contribution of hrHPV may have been overestimated.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, HPV16, HPV18, HPV52, and HPV58 were the most dominant high-risk genotypes in this population and accounted for 89.27% of all CIN II\u0026thinsp;+\u0026thinsp;lesions. In addition to HPV16, HPV18, HPV52, HPV58, HPV31 and HPV33, HPV35 may deserve special attention. Given the differing risks attributed to different hrHPV types, we propose that health care workers should pay attention to the specific hrHPV types in cervical lesions during screening in the rural Chinese population. Our data suggest that screening tests and protocols based on specific types of HPV should focus on HPV16, HPV18, HPV52, HPV31, HPV33, HPV35 and HPV58. Additionally, we assessed the potential impacts of the 9-valent vaccine on cervical cancer and precancer. The 9-valent vaccine can reduce the risk of most HPV-related cervical cancers and precancerous lesions in rural women under 40 years of age in Shanxi. Therefore, research on the global prevalence and causes of different hrHPV types may not be entirely relevant to the female population in China. It is important to take into account the distinctive characteristics of cervical HPV infections in China when developing HPV screening techniques and vaccines. Taking into account the prevalence of combined HPV genotypes and the proportion of high-grade cervical intraepithelial neoplasia lesions attributed to these genotypes may provide valuable insights for developing more accurate and efficient cervical cancer screening programs tailored to specific regions. Our findings may help health care authorities assess the impact of vaccination programs and inform the application of tailored HPV vaccines in Shanxi Province.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHPV, human papillomavirus. hrHPV, high-risk human papillomavirus. ACS, American Cancer Society. OR, odds ratio. CI, confidence interval. ASCCP: American Society for Colposcopy and Cervical Pathology. ASCP: American Society for Clinical Pathology. ICC, invasive cervical carcinoma. AIS, adenocarcinoma in situ.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eData sharing statement\u003c/h2\u003e \u003cp\u003eThe datasets generated during the current study are not yet publicly available due to privacy concerns and ongoing additional research. Data can be made available for peer review upon reasonable request by contacting the corresponding author.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003col\u003e\n \u003cli\u003eThe National Natural Science Foundation of China (82072891).\u003c/li\u003e\n \u003cli\u003eThe Project of the Central Government Guiding Local in Shanxi Province (YDZJSX2022B012)\u003c/li\u003e\n \u003cli\u003eBasic Research Program of Shanxi Province (202103021224352)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eShanxi Maternal and Child Health Hospital (2021009).\u003c/li\u003e\n\u003c/ol\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eRS and JC conceived and designed the study, having full access to all of the data in the study and taking responsibility for the content of the manuscript. RS and ZHW analyzed the data, took responsibility for the accuracy of the data analysis and wrote the first draft of the manuscript. ZHW and MZ reviewed the paper. RS, WJQ, JC, ZHW, and MZ contributed to the interpretation of the data and clinical inputs. All authors were involved in the revision of the manuscript for important intellectual content and approved the final version to be published.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank all the data collectors, without whom this project would not have been possible.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during the current study are not yet publicly available due to privacy concerns and ongoing additional research. Data can be made available for peer review upon reasonable request by contacting the corresponding author\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. \u003cem\u003eCA: A Cancer Journal for Clinicians. \u003c/em\u003e2018;68(6):394-424.\u003c/li\u003e\n\u003cli\u003eChen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015. \u003cem\u003eCA Cancer J Clin. \u003c/em\u003e2016;66(2):115-132.\u003c/li\u003e\n\u003cli\u003eLangsfeld E, Laimins LA. Human Papillomaviruses: Research Priorities for the Next Decade. \u003cem\u003eTrends in Cancer. \u003c/em\u003e2016;2(5):234-240.\u003c/li\u003e\n\u003cli\u003eFlanagan MB. Primary High-Risk Human Papillomavirus Testing for Cervical Cancer Screening in the United States: Is It Time? \u003cem\u003eArchives of Pathology \u0026amp; Laboratory Medicine. \u003c/em\u003e2018;142(6):688-692.\u003c/li\u003e\n\u003cli\u003eCrosbie EJ, Einstein MH, Franceschi S, Kitchener HC. Human papillomavirus and cervical cancer. \u003cem\u003eThe Lancet. \u003c/em\u003e2013;382(9895):889-899.\u003c/li\u003e\n\u003cli\u003eSmelov V, Elfstr\u0026ouml;m KM, Johansson ALV, et al. Long‐term HPV type‐specific risks of high‐grade cervical intraepithelial lesions: A 14‐year follow‐up of a randomized primary HPV screening trial. \u003cem\u003eInternational Journal of Cancer. \u003c/em\u003e2014;136(5):1171-1180.\u003c/li\u003e\n\u003cli\u003eSimms KT, Steinberg J, Caruana M, et al. Impact of scaled up human papillomavirus vaccination and cervical screening and the potential for global elimination of cervical cancer in 181 countries, 2020\u0026ndash;99: a modelling study. \u003cem\u003eThe Lancet Oncology. \u003c/em\u003e2019;20(3):394-407.\u003c/li\u003e\n\u003cli\u003eGargano J, McClung N, Lewis R, et al. HPV type-specific trends in cervical precancers in the United States, 2008 to 2016. \u003cem\u003eInternational journal of cancer. \u003c/em\u003e2023;152(2):137-150.\u003c/li\u003e\n\u003cli\u003eJiang X, Tang H, Chen T. Epidemiology of gynecologic cancers in China. \u003cem\u003eJournal of Gynecologic Oncology. \u003c/em\u003e2018;29(1).\u003c/li\u003e\n\u003cli\u003eHuh WK, Ault KA, Chelmow D, et al. Use of Primary High-Risk Human Papillomavirus Testing for Cervical Cancer Screening. \u003cem\u003eJournal of Lower Genital Tract Disease. \u003c/em\u003e2015;19(2):91-96.\u003c/li\u003e\n\u003cli\u003eZhao X-L, Hu S-Y, Zhang Q, et al. 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Human papillomavirus infection in the female population of Antwerp, Belgium: prevalence in healthy women, women with premalignant lesions and cervical cancer. \u003cem\u003eEur J Gynaecol Oncol. \u003c/em\u003e2001;22(3):204-208.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Human papillomavirus, HPV genotyping, cervical intraepithelial neoplasia, attribution proportion, cervical cancer","lastPublishedDoi":"10.21203/rs.3.rs-4436179/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4436179/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To explore the genotype distribution of high-risk human papillomavirus (hrHPV) and the attribution of different grades of cervical lesions to the disease in Shanxi Province and estimate the potential impact of the HPV vaccine on CIN II+ lesions to direct the implementation of successful programs for cervical cancer prevention and management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Data from the records of cervical cancer screening programs for rural women in Shanxi Province wereretrospectively collected. Women who underwent primary HPV screeningbetween January 2014 and December 2019 were included. The attribution proportion of specific hrHPV types for different grades of cervical lesions was calculated by using the type contribution weighting and the proportional attribution methods to estimate the potential impact of HPV vaccines on CIN II+ lesions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: CIN II+ lesions were observed mainly with HPV16 (65.85%), HPV18 (10.20%), HPV58 (10.20%), HPV52 (7.98%), HPV31 (4.66%), HPV33 (4.43%), HPV51 (2.22%) and HPV56 (2.22%). A total of 97.42% of all CIN II+ lesions were attributed to HPV16, HPV18, HPV52, HPV58, HPV31, HPV33 and HPV35. A total of 75.4% (95% CI, 71.4-79.4) of CIN II+ lesions were attributable to HPV16/18, and 21.1% (95% CI, 17.4-25.1) were attributable to the 5 additional types (HPV31/33/45/52/58) covered by the 9-valent vaccine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The prevalence of hrHPV infection among women in Shanxi Province was high, and HPV16, HPV18, HPV58, HPV52, HPV31, HPV33 and HPV35 had the highest attributable fractions of CIN II+ lesions. The type-specific HPV prevalence and attribution proportion of cervical precancerous lesions should be taken into consideration in both clinical management and the design of preventive strategies.\u003c/p\u003e","manuscriptTitle":"Attribution of high-risk human papillomavirus genotypes in cervical lesions detected in a screening population in Shanxi Province, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 06:59:14","doi":"10.21203/rs.3.rs-4436179/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-01T06:22:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-29T20:09:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133598830805095178321217425567380623183","date":"2025-03-19T15:18:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-26T16:50:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61020833823714084895136516998427284186","date":"2024-09-17T14:28:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-30T11:47:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-30T11:45:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-27T10:48:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-22T10:16:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-17T10:46:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0257aa4a-02f5-44ab-aaf5-22456b62a8d1","owner":[],"postedDate":"June 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32692887,"name":"Biological sciences/Cancer"},{"id":32692888,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2025-08-04T16:42:37+00:00","versionOfRecord":{"articleIdentity":"rs-4436179","link":"https://doi.org/10.1038/s41598-025-14228-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-08-02 16:13:17","publishedOnDateReadable":"August 2nd, 2025"},"versionCreatedAt":"2024-06-04 06:59:14","video":"","vorDoi":"10.1038/s41598-025-14228-0","vorDoiUrl":"https://doi.org/10.1038/s41598-025-14228-0","workflowStages":[]},"version":"v1","identity":"rs-4436179","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4436179","identity":"rs-4436179","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}