Retrospective Analysis of the Association Between Cervical Squamous Intraepithelial Lesions and Human Papillomavirus Genotypes

Retrospective Analysis of the Association Between Cervical Squamous Intraepithelial Lesions and Human Papillomavirus Genotypes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Retrospective Analysis of the Association Between Cervical Squamous Intraepithelial Lesions and Human Papillomavirus Genotypes Linghua Kong, Xiaoping Xiao, Tao Xu, Ru Wan, Yang Xiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-667054/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Human papillomavirus (HPV) has been confirmed as a major causative factor for malignant transformation of cervical epithelial cells and for the development of cervical intraepithelial neoplasia (CIN) and invasive cervical cancer. Methods: We collected the cervical cell samples of women who visited the gynecological clinic of Peking Union Medical College Hospital between October 2017 and May 2020 and submitted them to the HPV genotyping test. We analyzed the distribution of single-type HPV genotypes in CIN of different severities and the age-dependent prevalence for single-type HPV infection. Results: In both CIN2 and CIN3 group, HPV 16, 58, 52, 33 and 31/18 were detected as top 5 HPV types, which accounts for 89.25% and 88.54% of single HPV infection incidence respectively. HPV 16 was the dominant genotype in both CIN2 and CIN3, accounted for 46.24% and 55.21%, respectively. The prevalence of HPV 16 was the most frequent in all the age groups, except >64 years group in CIN3. The prevalence of HPV 16 and 33 increased obviously with increasing grade of CIN (chi-squared test for trend, P < 0.001), while HPV 18, 31, 52 and 58 showed the opposite trends. The peak of the incidence of CIN3 was observed at 25~34 years (33.68%), followed by 35-44 years (31.58%). Conclusion: High grade CIN peak at 25-44 years, women of this age are recommended for normative screening if conditions permit. HPV 16 was particularly aggressive in the development of cervical premalignant lesions and malignant lesions in almost all age groups, except >64 years group in CIN3. For women >64 years old, patients infected with other HPV types should be also taken seriously. In general, HPV 16, 58, 52, 33, 31 and 18 were the most common genotypes in high grade CIN, and vaccine including these predominant genotypes might be of great significance for cervical cancer prevention in China. Immunology Infectious Diseases human papillomavirus (HPV) genotypes distribution cervical intraepithelial neoplasia (CIN) age Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Background Cervical cancer is the second most frequent cancer among women globally, especially in developing countries. It has been estimated that about 529000 women are diagnosed with cervical cancer annually, and causing approximately 275000 deaths every year [ 1 ]. In 2015, there were 98900 new cases of cervical cancer and 30500 cervical cancer-related deaths in China [ 2 ]. Human papillomavirus (HPV), the most common sexually transmitted virus, has been confirmed as a major causative factor for malignant transformation of cervical epithelial cells and for the development of cervical intraepithelial neoplasia (CIN) and invasive cervical cancer [ 3 ]. To date, 14 HPV types have been classified as “high-risk” for their strong carcinogenic potentials, which contribute to 96.6% of invasive cervical cancers diagnosed worldwide [ 4 ]. Among the high-risk HPV types, HPV16 and HPV18 are well-known carcinogenic genotypes, additionally, HPV31, 33, 35, 39, 45, 51, 52, 56, 58, 59 are also classified as “carcinogenic to humans” [ 5 ]. Besides, the low-risk types, such as HPV6, and 11, are classified as “non-oncogenic to humans”, which are associated with hyperplastic lesions [ 5 ]. As there are differences in pathogenicity between different HPV genotypes, it is important to understand the information on HPV prevalence and type distribution in cervical lesions, particularly precancerous lesions. In January 2019, aglobal strategy towards the elimination of cervical cancer as a public health problem was approved by World Health Organization, which outlines key goals and agreed targets to be reached by 2030 and set the world on track to elimination [ 6 ]. In the era of widespread HPV-based primary screening and HPV-based triage of screen-detected cervical abnormalities, HPV genotyping will provide evidence for the future selection of vaccines targeting HPV types common to a specific region and further aid the development of public health policy programs of eliminating cervical cancer by 2030. Therefore, updated information on type-specific HPV prevalence and distribution is of guiding significance for cervical cancer prevention. In this study, HPV prevalence and genotype distribution in Negative tissue and CIN patients were described, and the age-dependent prevalence of single-type HPV infection were also investigated. These data will provide information for estimating the potential impact of HPV prophylactic vaccines in Chinese women. 2. Method 2.1 The aim To investigate the correlation between cervical squamous intraepithelial lesions and HPV genotypes and to understand the importance of HPV genotypes distribution. 2.2 The design We collected the cervical cell samples of women who visited the gynecological clinic of Peking Union Medical College Hospital between October 2017 and May 2020 and submitted them to the HPV genotyping test. A total of 24199 cases were submitted to individual HPV genotyping test, among which, 1661 cases underwent colposcopy biopsy and were included in the current study. Among the cases, 456 cases were diagnosed as Negative tissue, 899 cases were diagnosed as CIN1, 156 cases were diagnosed as CIN2, 144 cases were diagnosed with CIN3, 6 cases were diagnosed with SCC. We analyzed the distribution of single-type HPV genotypes in CIN of different severities and the age-dependent prevalence for single-type HPV infection. As this study was retrospective, which was approved by the Ethics Committee of our hospital (approval number S-K1604). 2.3 HPV DNA test Cervical samples were collected by gynecologists and stored in standard preservative media provided by manufacturers along with their kits. The testing was based on the polymerase chain reaction (PCR) and the TaqMan technique using a commercially available HPV Genotyping Real Time PCR kit (ZJ Bio-Tech Co., Ltd, Shanghai, China), which could detect HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 82 and 6/11 simultaneous individually. 2.4 Pathological examination Pathological diagnosis of cervical lesions was used as the gold standard. The results of pathology were classified into negative (normal or inflammation), CIN1, CIN2, CIN3 and SCC. All the histologic specimens were reviewed by 2 independent expert pathologists. 2.5 Statistical analysis SPSS v25.0 was used for statistical analysis. The count data are expressed as a percentage or n (%). The prevalence of HPV across cervical lesions was compared by Chi-square test. The P value was used to indicate the significance, the test level was α = 0.05, and P < 0.05 was considered statistically significant. 3. Results A total of 1661 cases with histopathologic diagnoses and HPV genotyping test results were included in the study. 456 women were diagnosed as Negative tissue, 1199 women were diagnosed with CIN and 6 women were diagnosed as cervical cancer. Among women diagnosed with CIN, 899 (75.29%) had CIN1, 156 (13.06%) had CIN2 and 144 (11.65%) had CIN3. HPV-positive results reported in Negative, CIN1, CIN2, CIN3 and SCC were 91.45%, 90.99%, 98.08%, 96.53% and 100%, respectively (x 2 = 14.577, P = 0.006). The proportion of single HPV infection were 64.75%, 58.19%, 60.78%, 69.06% and 100% in Negative, CIN1, CIN2, CIN3 and SCC, respectively, which increased with increasing grade of CIN (x 2 = 5.906, P = 0.052) (Fig. 1 ). And infections with multiple types were identified in 35.25%, 41.81%, 39.22%, 30.94% and 0% of individuals in Negative, CIN1, CIN2, CIN3 and SCC, respectively, which decreased with increasing grade of CIN (x 2 = 5.906, P = 0.052) (Fig. 1 ). 3.1 Distribution of single HPV genotypes In the present study, when only the cases with single type HPV were evaluated, HPV 16 accounts for 24.07%, 22.06%, 46.24% and 55.21% of infections in Negative, CIN1, CIN2 and CIN3, respectively, which increased significantly with increasing grade of CIN (chi-squared test for trend, P < 0.001). The prevalence of HPV 33 was 2.22%, 3.15%, 5.38% and 8.33% in Negative, CIN1, CIN2 and CIN3, respectively, which also increased with increasing grade of CIN (chi-squared test for trend, P = 0.033). Besides, the incidence of HPV 16/18 was 33.33%, 29.41%, 50.54% and 59.38% in Negative, CIN1, CIN2 and CIN3, respectively, which increased significantly with the increasing grade of CIN (chi-squared test for trend, P < 0.001). However, the prevalence of HPV 51, 56 and 66 were lower than 8.00% in all the CIN grades and decreased obviously with the increasing grade of CIN (chi-squared test for trend, P < 0.05). Then, the incidence of other HPV types, namely genotypes excluding 16, 18, 6 and 11, was 66.67%, 70.59%, 49.46% and 40.63% in Negative, CIN1, CIN2 and CIN3, respectively, which also exhibited the same trend, which decreased with increasing grade of CIN (chi-squared test for trend, P < 0.001). In the Negative group, the 5 most frequent genotypes were, in descending order of frequency, HPV types 16, 52, 58, 18 and 51/56 (ranged from 24.07–5.19%), the total incidence of these 5 genotypes was 67.41%. In CIN1 patients, the 5 most common HPV types were 16 (22.06%), 52 (17.02%), 58 (14.92%), 18 (7.35%) and 66 (7.14%), with a total incidence of 68.49%. The 5 predominant genotypes were 16 (46.24%), 52 (15.05%), 58 (15.05%), 31 (7.53%) and 33 (5.38%), with a total incidence of 89.25% in CIN2 patients. In the CIN3 group, in order of prevalence, HPV 16 (55.21%), 58 (11.46%), 52 (9.38%), 33 (8.33%), 31/18 (4.17%) were detected as top 5 HPV genotypes, which accounts for 88.54% of infection incidence. Moreover, single type infection of 45 and 6/11 were not observed in both CIN2 and CIN3. Additionally, all of the six SCC cases were infected with single-type HPV 16. (Table 1 ) Table 1 Distribution of HPV genotypes in CIN HPV types Negative (n = 270) CIN1 (n = 476) CIN2 (n = 93) CIN3 (n = 96) P -value 16 24.07% 22.06% 46.24% 55.21% < 0.001 18 9.26% 7.35% 4.30% 4.17% 0.243 31 3.70% 2.10% 7.53% 4.17% 0.053 33 2.22% 3.15% 5.38% 8.33% 0.033 35 1.48% 2.10% 1.08% 2.08% 0.871 39 4.81% 2.94% 1.08% 0.00% 0.065 45 1.48% 0.63% 0.00% 0.00% 0.325 51 5.19% 5.67% 1.08% 0.00% 0.031 52 14.81% 17.02% 15.05% 9.38% 0.295 56 5.19% 5.04% 0.00% 1.04% 0.046 58 14.07% 14.92% 15.05% 11.46% 0.842 59 2.96% 3.36% 2.15% 1.04% 0.630 66 4.81% 7.14% 1.08% 0.00% 0.006 68 4.81% 4.62% 0.00% 1.04% 0.065 82 0.37% 0.84% 0.00% 2.08% 0.311 6 + 11 0.74% 1.05% 0.00% 0.00% 0.571 16/18 33.33% 29.41% 50.54% 59.38% < 0.001 Others* 66.67% 70.59% 49.46% 40.63% < 0.001 *Others: HPV includes 6, 11, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 82 3.2 Distribution patten of predominant HPV genotypes As Fig. 2 showed, in single-type infection, HPV 16 was the most frequent genotype in Negative, CIN1, CIN2 and CIN3, whose prevalence increased significantly with the aggravation of the CIN (chi-squared test for trend, P < 0.001). HPV 33 also increased with increasing grade of CIN (chi-squared test for trend, P = 0.033), with prevalence lower than 10% in all the CIN grades. However, HPV18 (chi-squared test for trend, P = 0.243), 31 (chi-squared test for trend, P = 0.053), 52 (chi-squared test for trend, P = 0.295), 58 (chi-squared test for trend, P = 0.842) showed the opposite trends, which decreased with increasing grade of CIN. Besides, other HPV types also decreased with increasing grade of CIN (chi-squared test for trend, P < 0.001). Regarding single infection, the cumulative positive rate of HPV 16, 18, 31, 33, 52 and 58 was 68.15%, 66.60%, 93.55% and 92.71% in Negative group, CIN1, CIN2 and CIN3, respectively. 3.3 Coloscopy referral number for detecting 1 CIN2+/CIN3 To detect one CIN2 + cases, 2.8, 8.5, 3.2 and 7.1 women should receive colposcopy referrals if using HPV16, HPV 18, HPV 16/18 and HPV others as screening methods for detecting cervical lesions, respectively. Meanwhile, to detect one CIN3 case, the referral numbers for HPV16, HPV 18, HPV 16/18 and HPV others were 5.0, 17.0, 5.9 and 15.4 women, respectively. The colposcopy referral rate for HPV others is 2.5 times and 3 times higher than HPV 16 for detecting one CIN2 + case and one CIN3 case, respectively (Table 2 ). Table 2 Colposcopy referral number for detecting one CIN2 + and CIN3 by using different HPV genotypes HPV type Negative % (n/N) CIN1 % (n/N) CIN2 % (n/N) CIN3 % (n/N) Coloscopy referral number for detecting 1 CIN2+ Coloscopy referral number for detecting 1 CIN3 HPV 16 (n = 266) 24.07% (65/270) 22.06% (105/476) 46.24% (43/93) 55.21% (53/96) 2.8 5.0 HPV 18 (n = 68) 9.26% (25/270) 7.35% (35/476) 4.30% (4/93) 4.17% (4/96) 8.5 17.0 HPV 16/18 (n = 334) 33.33% (90/270) 29.41% (140/476) 49.46% (46/93) 59.37% (57/96) 3.2 5.9 HPV others (n = 601) 66.67% (180/270) 70.59% (336/476) 49.46% (46/93) 40.62% (39/96) 7.1 15.4 3.4 Age-dependent prevalence for single-type HPV infection In the present study, the average age of CIN2 and CIN3 were (41.51 ± 10.53) years and (40.75 ± 10.51) years, respectively. In CIN2, the predominant morbidity age were 35–44 years (36.46%) and 25–34 years (33.33%), and the prevalence of CIN2 decreased obviously with increasing age in women over 45 years old. While the peak of the incidence of CIN3 was observed at 25 ~ 34 years (33.68%), followed by 35–44 years (31.58%), and decreased obviously with increasing age. Moreover, no single type infections were identified under 25 years old in both CIN2 and CIN3. (Fig. 3 ) When age-dependent prevalence for single-type HPV infection in Negative, CIN1, CIN2 and CIN3 were evaluated, the top 5 most frequent HPV types in different age groups were analyzed (Fig. 4 ). In general, the prevalence of HPV 16 was the most frequent in all the age groups, except > 64 years group in CIN3. Among CIN1 patients, HPV 16, 52 and 58 were the common predominant HPV types in all the age groups except > 64 years. In CIN2 patients, the most prevalent HPV types in different age groups were included in 16, 52, 58, 33, 31 and 18, with relative proportion differed somewhat by age. In CIN3 patients, HPV16, 52, 58 and 33 were the common frequent types in the age groups of 25 ~ 34 years, 35 ~ 44 years and 45 ~ 54 years. Moreover, the prevalence of HPV 16 in younger groups (25 ~ 34 years, 35 ~ 44 years and 45 ~ 54 years) was significantly higher than older groups (55 ~ 64 years and > 64 years), while HPV58 showed the opposite trends. 4. Discussion In the present study, HPV-positive rate reported in Negative, CIN1, CIN2 and CIN3 were 91.45%, 90.99%, 98.08% and 96.53%, respectively, which were higher than the positive rate in cervical cancer screening [ 7 , 8 ]. The main reason for the difference is due to the fact that this study was a retrospective analysis based on opportunistic screening, the patients included were detected with abnormal cytology/HPV results and underwent a coloscopy test and a potential cervical biopsy according to the 2012 American Society of Colposcopy and Cervical Pathology (ASCCP) guideline [ 9 ]. Therefore, the HPV positive rate of Negative group and CIN1 group were relatively much higher in the current study. In addition, the proportions of multiple HPV infection were 35.25%, 41.81%, 39.22%, 30.94% and 0% in Negative, CIN1, CIN2, CIN3 and SCC, respectively, which decreased with increasing grade of CIN. Thus, a negative relationship between multiple infection and the progression of CIN was found, which revealed that multiple infection was not the leading factor for the progression of CIN2+, the finding was consistent with previous study [ 10 – 12 ]. When only the cases with single type HPV infection were evaluated, HPV 16 and 33 increased significantly with increasing CIN grades, while HPV18, 31, 52, 58 showed the opposite trends. Besides, all of the 6 SCC cases in this study were infected with single-type HPV 16. These results indicated that HPV 16 is the most aggressive Hr-HPV in the development of cervical premalignant lesions and malignant lesions and is less likely to regress compared with other HPV genotypes, the finding is consistent with previous studies [ 13 , 14 ]. Moreover, the frequency of HPV 33 also increased with the severity of the cervical lesion grade, which deserves further attention due to the limited cases in this analysis. However, the present study demonstrated that the prevalence of HPV 18 was less than 10% and decreased with the severity of cervical lesions, which was not the most common HPV genotype in high grade CIN, the finding was similar with other Chinese studies [ 11 , 12 , 15 ], but was different with international data [ 14 , 16 ]. Furthermore, only 7 cases (0.94%) with single-type HPV 45 was found in ≤ CIN1 patients, while no cases of single-type HPV 45 was identified in both CIN2 and CIN3 in this study. Although HPV 18 and 45 showed a relative lower prevalence in the current analysis, they were reported to be associated with glandular lesions in the endocervical canal [ 9 , 17 ], which are still of great importance. In consequence, patients with HPV 18/45 infection should pay close attention on endocervical canal lesions when referring coloscopy. In addition, the referrals and colposcopies number were as low as 2.7 and 5.0 if using HPV16 as screening method for detecting one CIN2 + and one CIN3, respectively, which is much lower than that of HPV others. Meanwhile, the data of HPV others showed in Table 2 was actually not using HPV others alone as screening method, but in combination with the results of abnormal cytology. Therefore, the actual referrals and colposcopies number using HPV others alone as screening method would be higher. HPV genotype distribution in high-grade cervical lesions has been reported to vary significantly in different geographic population [ 17 , 18 ]. According to a meta-analysis, the prevalent HPV types in high-grade cervical lesions were 16 (57.90%), 31 (15.80%), 33 (4.40%), 18 (4.00%) and 52 (2.90%) in Europe, while the top five HPV types in CIN3 were 16, 31, 18, 52 and 59 in Canada [ 19 ]. In this study, the 5 predominant genotypes were 16 (46.24%), 52 (15.05%), 58 (15.05%), 31 (7.53%) and 33 (5.38%) in CIN2 patients and the most prevalent HPV genotypes among CIN3 patients were HPV 16 (36.81%), 58 (7.64%), 52 (6.25%), 33 (5.56%) and 31/18 (2.78%). The prevalence of these predominant genotypes comprised 93.55% and 92.71% of total single HPV infection in CIN2 and CIN3, respectively. It is worth mentioning that most of the patients in our gynecological clinic came from all over China with confirmed HPV infection or suspected cervical lesions, which does not belong to the category of regional cervical cancer screening, but opportunistic screening. Our finding was consistent with a previous analysis [ 20 ], which reported the predominant types of CIN2/3 in Asia were HPV 16, 58, 52, 18, 33 and 31. Regarding the distribution of HPV genotypes in China, little regional differences among high-grade cervical lesions were observed. In northern China, the most prevalent HPV genotypes were found to be HPV16, 58, 33, 52 and 18 [ 15 ]. In a large cohort study based on western Chinese women, the most commonly detected HPV genotypes in CIN2/CIN3 cases were HPV 16 (48.1%), 58 (19.3%), 52 (10.0%), 33 (9.6%) and 18 (4.6%) [ 11 ]. In eastern China, the top 5 predominant genotypes in CIN2 were 16, 58, 52, 33 and 31, while in CIN3 were HPV 16, 58, 33, 52 and 31 [ 12 ]. Thus, based on the prior studies and the current study, HPV 16, 58, 52, 33, 31 and 18 were the predominant genotypes in the majority of Chinese women. Therefore, vaccine including HPV 16, 18, 31, 33, 52 and 58 is potentially very effective for Chinese women, which might reduce the morbidity of cervical cancer in China. Of cause, large multicenter studies and long-term follow up are needed to further confirm this hypothesis. In the present study, the incidence of high-grade cervical lesions was significantly higher among women age 25 ~ 34 years and 35 ~ 44 years than among the other age groups, the results were similar with previous studies. For example, in a previous population-based study in Beijing, a peak of 2.2% at age 30 ~ 34 years was observed in CIN2+ [ 21 ]. Besides, a cross-sectional study of Yangtze River Delta area (China) showed that the prevalence of CIN2 and CIN3 peaked at 40 ~ 44 years and 35 ~ 39 years, respectively, and followed by 35 ~ 39 years and 30 ~ 34 years, respectively [ 12 ]. According to the evolution of cervical lesions, it takes several years for the occurrence of high-grade CIN [ 22 ]. Consequently, women over 25 years old were recommended for a standardized screening when conditions permit. When age-dependent prevalence for single-type infection was examined in CIN3 groups, we found that the prevalence of HPV 16 was significantly lower in the patients older than 55 years. In contrast, the prevalence of HPV 58 was obviously higher in the patients older than 55 years. This data suggested that HPV 16 is the most malignant HPV type, which has a strong potential for CIN trends, and whose progression from benign to premalignant (or malignant lesions) is earlier than that of other types. However, other HPV types, such as HPV 58, may need longer time to progress into premalignant lesions. In this study, 3 cases of CIN3 were found in > 64 years group, with 2 cases infected with HPV 58 and one case infected with HPV 16. As a country with a vast territory, China still faces many difficulties in cervical cancer screening, many women older than 64 years old have not yet received routine cervical cancer screening before. Therefore, women older than 64 years old with other HPV types infection should be paid special attention as well. 5. Conclusions In summary, age-dependent distribution suggested that high grade CIN peak at 25-44 years of age, women aged 25 years and older in China are recommended for a routine screening if conditions permit. For women >64 years old, patients infected with other HPV types should be also taken seriously. For women 25 to 64 years old, HPV 16 was particularly aggressive in the development of cervical premalignant lesions and malignant lesions. In general, HPV 16, 58, 52, 33, 31 and 18 were the most common genotypes in high grade CIN, vaccine including these main genotypes might be of great value for cervical cancer prevention in China. The current study was a single-center and retrospective analysis with a relatively small sample size, further confirmation and validation are needed in future multicenter prospective study with large samples. 6. Abbreviations Number Abbreviations Full name 1 CIN Cervical intraepithelial neoplasia 2 Hr-HPV High-risk human papillomavirus 3 SCC Squamous cervical carcinoma 4 PCR Polymerase chain reaction 5 ASCCP American Society of Colposcopy and Cervical Pathology Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of Peking Union Medical College Hospital (approval number S-K1604) and the study was retrospective, with only data been used and analyzed, no consent was need to participate, which was in compliance with the institutional and national policies concerning research approvals. Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding Not applicable Authors' contributions LK and YX conceived of the original idea for the study, interpreted results, obtained ethical approval, edited the paper and was overall guarantor. TX and XX carried out the statistical analysis and contributed to the preparation of the data set. LK, XX and RW interpreted results and contributed to the writing of the paper. All authors read and approved the final manuscript. Acknowledgements Not applicable References 1. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM: Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008 . Int J Cancer 2010, 127 (12):2893-2917. 2. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J: Cancer statistics in China, 2015 . CA Cancer J Clin 2016, 66 (2):115-132. 3. Walboomers JM, Jacobs MV, Manos MM, Bosch FX, Kummer JA, Shah KV, Snijders PJ, Peto J, Meijer CJ, Muñoz N: Human papillomavirus is a necessary cause of invasive cervical cancer worldwide . J Pathol 1999, 189 (1):12-19. 4. Crow JM: HPV: The global burden . Nature 2012, 488 (7413):S2-3. 5. Bouvard V, Baan R, Straif K, Grosse Y, Secretan B, El Ghissassi F, Benbrahim-Tallaa L, Guha N, Freeman C, Galichet L et al : A review of human carcinogens--Part B: biological agents . Lancet Oncol 2009, 10 (4):321-322. 6. Bruni L, Saura A, Montoliu A, Brotons M, Alemany L, Diallo MS, Afsar OZ, LaMontagne DS, Mosina L, Contreras M et al : HPV vaccination introduction worldwide and WHO and UNICEF estimates of national HPV immunization coverage 2010-2019 . Prev Med 2020:106399. 7. Song F, Du H, Xiao A, Wang C, Huang X, Liu Z, Zhao M, Men H, Wu R: Type-specific Distribution of Cervical hrHPV Infection and the Association with Cytological and Histological Results in a Large Population-based Cervical Cancer Screening Program: Baseline and 3-year Longitudinal Data . J Cancer 2020, 11 (20):6157-6167. 8. Wu P, Xiong H, Yang M, Li L, Lazare C, Cao C, Gao P, Meng Y, Zhi W, Lin S et al : Co-infections of HPV16/18 with other high-risk HPV types and the risk of cervical carcinogenesis: A large population-based study . Gynecol Oncol 2019, 155 (3):436-443. 9. Schiffman M, Burk RD, Boyle S, Raine-Bennett T, Katki HA, Gage JC, Wentzensen N, Kornegay JR, Aldrich C, Tam T et al : A study of genotyping for management of human papillomavirus-positive, cytology-negative cervical screening results . J Clin Microbiol 2015, 53 (1):52-59. 10. Li M, Du X, Lu M, Zhang W, Sun Z, Li L, Ye M, Fan W, Jiang S, Liu A et al : Prevalence characteristics of single and multiple HPV infections in women with cervical cancer and precancerous lesions in Beijing, China . Journal of Medical Virology 2019, 91 (3):473-481. 11. Jiang W, Marshall Austin R, Li L, Yang K, Zhao C: Extended Human Papillomavirus Genotype Distribution and Cervical Cytology Results in a Large Cohort of Chinese Women With Invasive Cervical Cancers and High-Grade Squamous Intraepithelial Lesions . Am J Clin Pathol 2018, 150 (1):43-50. 12. Wang H, Cheng X, Ye J, Xu X, Hong Y, Sui L, You Z, Xie X: Distribution of human papilloma virus genotype prevalence in invasive cervical carcinomas and precancerous lesions in the Yangtze River Delta area, China . BMC Cancer 2018, 18 (1). 13. Vinokurova S, Wentzensen N, Kraus I, Klaes R, Driesch C, Melsheimer P, Kisseljov F, Dürst M, Schneider A, von Knebel Doeberitz M: Type-dependent integration frequency of human papillomavirus genomes in cervical lesions . Cancer Res 2008, 68 (1):307-313. 14. Hammer A, Rositch A, Qeadan F, Gravitt PE, Blaakaer J: Age-specific prevalence of HPV16/18 genotypes in cervical cancer: A systematic review and meta-analysis . Int J Cancer 2016, 138 (12):2795-2803. 15. Li Y, Wang Y, Jia C, Ma Y, Lan Y, Wang S: Detection of human papillomavirus genotypes with liquid bead microarray in cervical lesions of northern Chinese patients . Cancer Genet Cytogenet 2008, 182 (1):12-17. 16. Kjær SK, Frederiksen K, Munk C, Iftner T: Long-term absolute risk of cervical intraepithelial neoplasia grade 3 or worse following human papillomavirus infection: role of persistence . J Natl Cancer Inst 2010, 102 (19):1478-1488. 17. de Sanjose S, Quint WG, Alemany L, Geraets DT, Klaustermeier JE, Lloveras B, Tous S, Felix A, Bravo LE, Shin HR et al : Human papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study . Lancet Oncol 2010, 11 (11):1048-1056. 18. Li N, Franceschi S, Howell-Jones R, Snijders PJ, Clifford GM: Human papillomavirus type distribution in 30,848 invasive cervical cancers worldwide: Variation by geographical region, histological type and year of publication . Int J Cancer 2011, 128 (4):927-935. 19. Coutlée F, Ratnam S, Ramanakumar AV, Insinga RR, Bentley J, Escott N, Ghatage P, Koushik A, Ferenczy A, Franco EL: Distribution of human papillomavirus genotypes in cervical intraepithelial neoplasia and invasive cervical cancer in Canada . Journal of Medical Virology 2011, 83 (6):1034-1041. 20. Bosch FX, Burchell AN, Schiffman M, Giuliano AR, de Sanjose S, Bruni L, Tortolero-Luna G, Kjaer SK, Muñoz N: Epidemiology and Natural History of Human Papillomavirus Infections and Type-Specific Implications in Cervical Neoplasia . Vaccine 2008, 26 :K1-K16. 21. Li C, Wu M, Wang J, Zhang S, Zhu L, Pan J, Zhang W: A population-based study on the risks of cervical lesion and human papillomavirus infection among women in Beijing, People's Republic of China . Cancer Epidemiol Biomarkers Prev 2010, 19 (10):2655-2664. 22. Schiffman M, Castle PE, Jeronimo J, Rodriguez AC, Wacholder S: Human papillomavirus and cervical cancer . Lancet 2007, 370 (9590):890-907. Cite Share Download PDF Status: Posted Version 1 posted 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-667054","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":36266469,"identity":"41866418-65ad-497e-bc38-671cd9c55019","order_by":0,"name":"Linghua Kong","email":"","orcid":"","institution":"Peking Union Medical College Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Linghua","middleName":"","lastName":"Kong","suffix":""},{"id":36266470,"identity":"fd9c9f9e-b324-42b5-a4ed-f617d1028ae2","order_by":1,"name":"Xiaoping Xiao","email":"","orcid":"https://orcid.org/0000-0001-5021-9906","institution":"Peking Union Medical College Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoping","middleName":"","lastName":"Xiao","suffix":""},{"id":36266471,"identity":"1e92d988-1322-42b1-9fc6-ec8751229140","order_by":2,"name":"Tao Xu","email":"","orcid":"","institution":"Peking Union Medical College, Chinese Academy of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Xu","suffix":""},{"id":36266472,"identity":"2d803d88-e715-40ed-851c-e6e6b79d2760","order_by":3,"name":"Ru Wan","email":"","orcid":"","institution":"Peking Union Medical College Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ru","middleName":"","lastName":"Wan","suffix":""},{"id":36266473,"identity":"98353fea-0f73-4415-879d-33df7ca34415","order_by":4,"name":"Yang Xiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYDACZjBpAyLYSNKSRooWCDhMghaD48zPHn5tO59ncO3wswcMNXcIa5FsZjM3lm27XWxwO83cgOHYM8Ja+JkZzKQl224nbridwybB2HCYsBY2ZvZvQC3nSNDCz8xjJvmx7QAJWiSbecqkGc4lF0veTjOTSDhGhBaD88e3Sf4os8vju538TOJDDRFaQICZl40hAcxKIE4DAwPjjz/EKx4Fo2AUjIIRCACs1zdd4tzB/wAAAABJRU5ErkJggg==","orcid":"","institution":"Peking Union Medical College Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Xiang","suffix":""}],"badges":[],"createdAt":"2021-06-28 12:15:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-667054/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-667054/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":11054305,"identity":"297f5722-8de0-47fb-b2e6-7ec2b8d0b46b","added_by":"auto","created_at":"2021-07-02 17:45:17","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56775,"visible":true,"origin":"","legend":"The single infection and multiple infection of HPV among different groups","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-667054/v1/630beff4f1d2574709b21750.jpg"},{"id":11054307,"identity":"84d43350-9630-4ac5-add5-b6e086d9163c","added_by":"auto","created_at":"2021-07-02 17:45:17","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53938,"visible":true,"origin":"","legend":"The distribution pattern of predominant HPV genotypes with single-type infection","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-667054/v1/92f9359357a60f46a4f74002.jpg"},{"id":11054371,"identity":"70fbf1ad-a485-4e38-9d2e-29faa9d709c7","added_by":"auto","created_at":"2021-07-02 17:48:17","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":66625,"visible":true,"origin":"","legend":"The age distribution of the incidence of CIN2 and CIN3","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-667054/v1/1d66fc499f431d7697422b87.jpg"},{"id":11054372,"identity":"b138ccdc-3001-4290-864f-eb48949614c7","added_by":"auto","created_at":"2021-07-02 17:48:17","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180609,"visible":true,"origin":"","legend":"HPV genotypes by age groups in CIN","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-667054/v1/d5bd112383b18ef595270a84.jpg"},{"id":13702473,"identity":"8ca941ca-ece8-4b7b-8454-82ce11a81514","added_by":"auto","created_at":"2021-09-17 13:36:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1078466,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-667054/v1/5d5a1b72-0b07-4109-b976-21c3eccf4398.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eRetrospective Analysis of the Association Between Cervical Squamous Intraepithelial Lesions and Human Papillomavirus Genotypes\u003c/p\u003e","fulltext":[{"header":"1. Background","content":" \u003cp\u003eCervical cancer is the second most frequent cancer among women globally, especially in developing countries. It has been estimated that about 529000 women are diagnosed with cervical cancer annually, and causing approximately 275000 deaths every year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2015, there were 98900 new cases of cervical cancer and 30500 cervical cancer-related deaths in China [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Human papillomavirus (HPV), the most common sexually transmitted virus, has been confirmed as a major causative factor for malignant transformation of cervical epithelial cells and for the development of cervical intraepithelial neoplasia (CIN) and invasive cervical cancer [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. To date, 14 HPV types have been classified as \u0026ldquo;high-risk\u0026rdquo; for their strong carcinogenic potentials, which contribute to 96.6% of invasive cervical cancers diagnosed worldwide [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Among the high-risk HPV types, HPV16 and HPV18 are well-known carcinogenic genotypes, additionally, HPV31, 33, 35, 39, 45, 51, 52, 56, 58, 59 are also classified as \u0026ldquo;carcinogenic to humans\u0026rdquo; [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Besides, the low-risk types, such as HPV6, and 11, are classified as \u0026ldquo;non-oncogenic to humans\u0026rdquo;, which are associated with hyperplastic lesions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs there are differences in pathogenicity between different HPV genotypes, it is important to understand the information on HPV prevalence and type distribution in cervical lesions, particularly precancerous lesions. In January 2019, aglobal strategy towards the elimination of cervical cancer as a public health problem was approved by World Health Organization, which outlines key goals and agreed targets to be reached by 2030 and set the world on track to elimination [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In the era of widespread HPV-based primary screening and HPV-based triage of screen-detected cervical abnormalities, HPV genotyping will provide evidence for the future selection of vaccines targeting HPV types common to a specific region and further aid the development of public health policy programs of eliminating cervical cancer by 2030.\u003c/p\u003e \u003cp\u003eTherefore, updated information on type-specific HPV prevalence and distribution is of guiding significance for cervical cancer prevention. In this study, HPV prevalence and genotype distribution in Negative tissue and CIN patients were described, and the age-dependent prevalence of single-type HPV infection were also investigated. These data will provide information for estimating the potential impact of HPV prophylactic vaccines in Chinese women.\u003c/p\u003e "},{"header":"2. Method","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 The aim\u003c/h2\u003e \u003cp\u003eTo investigate the correlation between cervical squamous intraepithelial lesions and HPV genotypes and to understand the importance of HPV genotypes distribution.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 The design\u003c/h2\u003e \u003cp\u003eWe collected the cervical cell samples of women who visited the gynecological clinic of Peking Union Medical College Hospital between October 2017 and May 2020 and submitted them to the HPV genotyping test. A total of 24199 cases were submitted to individual HPV genotyping test, among which, 1661 cases underwent colposcopy biopsy and were included in the current study. Among the cases, 456 cases were diagnosed as Negative tissue, 899 cases were diagnosed as CIN1, 156 cases were diagnosed as CIN2, 144 cases were diagnosed with CIN3, 6 cases were diagnosed with SCC. We analyzed the distribution of single-type HPV genotypes in CIN of different severities and the age-dependent prevalence for single-type HPV infection. As this study was retrospective, which was approved by the Ethics Committee of our hospital (approval number S-K1604).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 HPV DNA test\u003c/h2\u003e \u003cp\u003eCervical samples were collected by gynecologists and stored in standard preservative media provided by manufacturers along with their kits. The testing was based on the polymerase chain reaction (PCR) and the TaqMan technique using a commercially available HPV Genotyping Real Time PCR kit (ZJ Bio-Tech Co., Ltd, Shanghai, China), which could detect HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 82 and 6/11 simultaneous individually.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Pathological examination\u003c/h2\u003e \u003cp\u003ePathological diagnosis of cervical lesions was used as the gold standard. The results of pathology were classified into negative (normal or inflammation), CIN1, CIN2, CIN3 and SCC. All the histologic specimens were reviewed by 2 independent expert pathologists.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eSPSS v25.0 was used for statistical analysis. The count data are expressed as a percentage or n (%). The prevalence of HPV across cervical lesions was compared by Chi-square test. The \u003cem\u003eP\u003c/em\u003e value was used to indicate the significance, the test level was α\u0026thinsp;=\u0026thinsp;0.05, and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"3. Results","content":"\u003cp\u003eA total of 1661 cases with histopathologic diagnoses and HPV genotyping test results were included in the study. 456 women were diagnosed as Negative tissue, 1199 women were diagnosed with CIN and 6 women were diagnosed as cervical cancer. Among women diagnosed with CIN, 899 (75.29%) had CIN1, 156 (13.06%) had CIN2 and 144 (11.65%) had CIN3. HPV-positive results reported in Negative, CIN1, CIN2, CIN3 and SCC were 91.45%, 90.99%, 98.08%, 96.53% and 100%, respectively (x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;14.577, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). The proportion of single HPV infection were 64.75%, 58.19%, 60.78%, 69.06% and 100% in Negative, CIN1, CIN2, CIN3 and SCC, respectively, which increased with increasing grade of CIN (x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;5.906, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.052) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). And infections with multiple types were identified in 35.25%, 41.81%, 39.22%, 30.94% and 0% of individuals in Negative, CIN1, CIN2, CIN3 and SCC, respectively, which decreased with increasing grade of CIN (x\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;5.906, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.052) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003e3.1 Distribution of single HPV genotypes\u003c/h2\u003e\n \u003cp\u003eIn the present study, when only the cases with single type HPV were evaluated, HPV 16 accounts for 24.07%, 22.06%, 46.24% and 55.21% of infections in Negative, CIN1, CIN2 and CIN3, respectively, which increased significantly with increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The prevalence of HPV 33 was 2.22%, 3.15%, 5.38% and 8.33% in Negative, CIN1, CIN2 and CIN3, respectively, which also increased with increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033). Besides, the incidence of HPV 16/18 was 33.33%, 29.41%, 50.54% and 59.38% in Negative, CIN1, CIN2 and CIN3, respectively, which increased significantly with the increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, the prevalence of HPV 51, 56 and 66 were lower than 8.00% in all the CIN grades and decreased obviously with the increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Then, the incidence of other HPV types, namely genotypes excluding 16, 18, 6 and 11, was 66.67%, 70.59%, 49.46% and 40.63% in Negative, CIN1, CIN2 and CIN3, respectively, which also exhibited the same trend, which decreased with increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003eIn the Negative group, the 5 most frequent genotypes were, in descending order of frequency, HPV types 16, 52, 58, 18 and 51/56 (ranged from 24.07\u0026ndash;5.19%), the total incidence of these 5 genotypes was 67.41%. In CIN1 patients, the 5 most common HPV types were 16 (22.06%), 52 (17.02%), 58 (14.92%), 18 (7.35%) and 66 (7.14%), with a total incidence of 68.49%. The 5 predominant genotypes were 16 (46.24%), 52 (15.05%), 58 (15.05%), 31 (7.53%) and 33 (5.38%), with a total incidence of 89.25% in CIN2 patients. In the CIN3 group, in order of prevalence, HPV 16 (55.21%), 58 (11.46%), 52 (9.38%), 33 (8.33%), 31/18 (4.17%) were detected as top 5 HPV genotypes, which accounts for 88.54% of infection incidence. Moreover, single type infection of 45 and 6/11 were not observed in both CIN2 and CIN3. Additionally, all of the six SCC cases were infected with single-type HPV 16. (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDistribution of HPV genotypes in CIN\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHPV types\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative (n\u0026thinsp;=\u0026thinsp;270)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCIN1 (n\u0026thinsp;=\u0026thinsp;476)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCIN2 (n\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCIN3 (n\u0026thinsp;=\u0026thinsp;96)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.94%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026thinsp;+\u0026thinsp;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16/18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e*Others: HPV includes 6, 11, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, 82\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003e3.2 Distribution patten of predominant HPV genotypes\u003c/h2\u003e\n \u003cp\u003eAs Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e showed, in single-type infection, HPV 16 was the most frequent genotype in Negative, CIN1, CIN2 and CIN3, whose prevalence increased significantly with the aggravation of the CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). HPV 33 also increased with increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033), with prevalence lower than 10% in all the CIN grades. However, HPV18 (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.243), 31 (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.053), 52 (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.295), 58 (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.842) showed the opposite trends, which decreased with increasing grade of CIN. Besides, other HPV types also decreased with increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regarding single infection, the cumulative positive rate of HPV 16, 18, 31, 33, 52 and 58 was 68.15%, 66.60%, 93.55% and 92.71% in Negative group, CIN1, CIN2 and CIN3, respectively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003e3.3 Coloscopy referral number for detecting 1 CIN2+/CIN3\u003c/h2\u003e\n \u003cp\u003eTo detect one CIN2\u0026thinsp;+\u0026thinsp;cases, 2.8, 8.5, 3.2 and 7.1 women should receive colposcopy referrals if using HPV16, HPV 18, HPV 16/18 and HPV others as screening methods for detecting cervical lesions, respectively. Meanwhile, to detect one CIN3 case, the referral numbers for HPV16, HPV 18, HPV 16/18 and HPV others were 5.0, 17.0, 5.9 and 15.4 women, respectively. The colposcopy referral rate for HPV others is 2.5 times and 3 times higher than HPV 16 for detecting one CIN2\u0026thinsp;+\u0026thinsp;case and one CIN3 case, respectively (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eColposcopy referral number for detecting one CIN2\u0026thinsp;+\u0026thinsp;and CIN3 by using different HPV genotypes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHPV type\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003e% (n/N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCIN1\u003c/p\u003e\n \u003cp\u003e% (n/N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCIN2\u003c/p\u003e\n \u003cp\u003e% (n/N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCIN3\u003c/p\u003e\n \u003cp\u003e% (n/N)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eColoscopy referral number for detecting 1 CIN2+\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eColoscopy referral number for detecting 1 CIN3\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 16\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.07% (65/270)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.06% (105/476)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46.24% (43/93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.21% (53/96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 18\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.26% (25/270)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.35% (35/476)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.30% (4/93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.17% (4/96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 16/18\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;334)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.33% (90/270)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29.41% (140/476)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.46% (46/93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59.37% (57/96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV others\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;601)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66.67% (180/270)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e70.59% (336/476)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49.46% (46/93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.62% (39/96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003e3.4 Age-dependent prevalence for single-type HPV infection\u003c/h2\u003e\n \u003cp\u003eIn the present study, the average age of CIN2 and CIN3 were (41.51\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53) years and (40.75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.51) years, respectively. In CIN2, the predominant morbidity age were 35\u0026ndash;44 years (36.46%) and 25\u0026ndash;34 years (33.33%), and the prevalence of CIN2 decreased obviously with increasing age in women over 45 years old. While the peak of the incidence of CIN3 was observed at 25\u0026thinsp;~\u0026thinsp;34 years (33.68%), followed by 35\u0026ndash;44 years (31.58%), and decreased obviously with increasing age. Moreover, no single type infections were identified under 25 years old in both CIN2 and CIN3. (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\n \u003cp\u003eWhen age-dependent prevalence for single-type HPV infection in Negative, CIN1, CIN2 and CIN3 were evaluated, the top 5 most frequent HPV types in different age groups were analyzed (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In general, the prevalence of HPV 16 was the most frequent in all the age groups, except \u0026gt;\u0026thinsp;64 years group in CIN3. Among CIN1 patients, HPV 16, 52 and 58 were the common predominant HPV types in all the age groups except \u0026gt;\u0026thinsp;64 years. In CIN2 patients, the most prevalent HPV types in different age groups were included in 16, 52, 58, 33, 31 and 18, with relative proportion differed somewhat by age. In CIN3 patients, HPV16, 52, 58 and 33 were the common frequent types in the age groups of 25\u0026thinsp;~\u0026thinsp;34 years, 35\u0026thinsp;~\u0026thinsp;44 years and 45\u0026thinsp;~\u0026thinsp;54 years. Moreover, the prevalence of HPV 16 in younger groups (25\u0026thinsp;~\u0026thinsp;34 years, 35\u0026thinsp;~\u0026thinsp;44 years and 45\u0026thinsp;~\u0026thinsp;54 years) was significantly higher than older groups (55\u0026thinsp;~\u0026thinsp;64 years and \u0026gt;\u0026thinsp;64 years), while HPV58 showed the opposite trends.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":" \u003cp\u003eIn the present study, HPV-positive rate reported in Negative, CIN1, CIN2 and CIN3 were 91.45%, 90.99%, 98.08% and 96.53%, respectively, which were higher than the positive rate in cervical cancer screening [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The main reason for the difference is due to the fact that this study was a retrospective analysis based on opportunistic screening, the patients included were detected with abnormal cytology/HPV results and underwent a coloscopy test and a potential cervical biopsy according to the 2012 American Society of Colposcopy and Cervical Pathology (ASCCP) guideline [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, the HPV positive rate of Negative group and CIN1 group were relatively much higher in the current study. In addition, the proportions of multiple HPV infection were 35.25%, 41.81%, 39.22%, 30.94% and 0% in Negative, CIN1, CIN2, CIN3 and SCC, respectively, which decreased with increasing grade of CIN. Thus, a negative relationship between multiple infection and the progression of CIN was found, which revealed that multiple infection was not the leading factor for the progression of CIN2+, the finding was consistent with previous study [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhen only the cases with single type HPV infection were evaluated, HPV 16 and 33 increased significantly with increasing CIN grades, while HPV18, 31, 52, 58 showed the opposite trends. Besides, all of the 6 SCC cases in this study were infected with single-type HPV 16. These results indicated that HPV 16 is the most aggressive Hr-HPV in the development of cervical premalignant lesions and malignant lesions and is less likely to regress compared with other HPV genotypes, the finding is consistent with previous studies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, the frequency of HPV 33 also increased with the severity of the cervical lesion grade, which deserves further attention due to the limited cases in this analysis. However, the present study demonstrated that the prevalence of HPV 18 was less than 10% and decreased with the severity of cervical lesions, which was not the most common HPV genotype in high grade CIN, the finding was similar with other Chinese studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], but was different with international data [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, only 7 cases (0.94%) with single-type HPV 45 was found in \u0026le;\u0026thinsp;CIN1 patients, while no cases of single-type HPV 45 was identified in both CIN2 and CIN3 in this study. Although HPV 18 and 45 showed a relative lower prevalence in the current analysis, they were reported to be associated with glandular lesions in the endocervical canal [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which are still of great importance. In consequence, patients with HPV 18/45 infection should pay close attention on endocervical canal lesions when referring coloscopy. In addition, the referrals and colposcopies number were as low as 2.7 and 5.0 if using HPV16 as screening method for detecting one CIN2\u0026thinsp;+\u0026thinsp;and one CIN3, respectively, which is much lower than that of HPV others. Meanwhile, the data of HPV others showed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e was actually not using HPV others alone as screening method, but in combination with the results of abnormal cytology. Therefore, the actual referrals and colposcopies number using HPV others alone as screening method would be higher.\u003c/p\u003e \u003cp\u003eHPV genotype distribution in high-grade cervical lesions has been reported to vary significantly in different geographic population [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. According to a meta-analysis, the prevalent HPV types in high-grade cervical lesions were 16 (57.90%), 31 (15.80%), 33 (4.40%), 18 (4.00%) and 52 (2.90%) in Europe, while the top five HPV types in CIN3 were 16, 31, 18, 52 and 59 in Canada [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In this study, the 5 predominant genotypes were 16 (46.24%), 52 (15.05%), 58 (15.05%), 31 (7.53%) and 33 (5.38%) in CIN2 patients and the most prevalent HPV genotypes among CIN3 patients were HPV 16 (36.81%), 58 (7.64%), 52 (6.25%), 33 (5.56%) and 31/18 (2.78%). The prevalence of these predominant genotypes comprised 93.55% and 92.71% of total single HPV infection in CIN2 and CIN3, respectively. It is worth mentioning that most of the patients in our gynecological clinic came from all over China with confirmed HPV infection or suspected cervical lesions, which does not belong to the category of regional cervical cancer screening, but opportunistic screening. Our finding was consistent with a previous analysis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which reported the predominant types of CIN2/3 in Asia were HPV 16, 58, 52, 18, 33 and 31. Regarding the distribution of HPV genotypes in China, little regional differences among high-grade cervical lesions were observed. In northern China, the most prevalent HPV genotypes were found to be HPV16, 58, 33, 52 and 18 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In a large cohort study based on western Chinese women, the most commonly detected HPV genotypes in CIN2/CIN3 cases were HPV 16 (48.1%), 58 (19.3%), 52 (10.0%), 33 (9.6%) and 18 (4.6%) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In eastern China, the top 5 predominant genotypes in CIN2 were 16, 58, 52, 33 and 31, while in CIN3 were HPV 16, 58, 33, 52 and 31 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Thus, based on the prior studies and the current study, HPV 16, 58, 52, 33, 31 and 18 were the predominant genotypes in the majority of Chinese women. Therefore, vaccine including HPV 16, 18, 31, 33, 52 and 58 is potentially very effective for Chinese women, which might reduce the morbidity of cervical cancer in China. Of cause, large multicenter studies and long-term follow up are needed to further confirm this hypothesis.\u003c/p\u003e \u003cp\u003eIn the present study, the incidence of high-grade cervical lesions was significantly higher among women age 25\u0026thinsp;~\u0026thinsp;34 years and 35\u0026thinsp;~\u0026thinsp;44 years than among the other age groups, the results were similar with previous studies. For example, in a previous population-based study in Beijing, a peak of 2.2% at age 30\u0026thinsp;~\u0026thinsp;34 years was observed in CIN2+ [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Besides, a cross-sectional study of Yangtze River Delta area (China) showed that the prevalence of CIN2 and CIN3 peaked at 40\u0026thinsp;~\u0026thinsp;44 years and 35\u0026thinsp;~\u0026thinsp;39 years, respectively, and followed by 35\u0026thinsp;~\u0026thinsp;39 years and 30\u0026thinsp;~\u0026thinsp;34 years, respectively [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. According to the evolution of cervical lesions, it takes several years for the occurrence of high-grade CIN [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Consequently, women over 25 years old were recommended for a standardized screening when conditions permit. When age-dependent prevalence for single-type infection was examined in CIN3 groups, we found that the prevalence of HPV 16 was significantly lower in the patients older than 55 years. In contrast, the prevalence of HPV 58 was obviously higher in the patients older than 55 years. This data suggested that HPV 16 is the most malignant HPV type, which has a strong potential for CIN trends, and whose progression from benign to premalignant (or malignant lesions) is earlier than that of other types. However, other HPV types, such as HPV 58, may need longer time to progress into premalignant lesions. In this study, 3 cases of CIN3 were found in \u0026gt;\u0026thinsp;64 years group, with 2 cases infected with HPV 58 and one case infected with HPV 16. As a country with a vast territory, China still faces many difficulties in cervical cancer screening, many women older than 64 years old have not yet received routine cervical cancer screening before. Therefore, women older than 64 years old with other HPV types infection should be paid special attention as well.\u003c/p\u003e "},{"header":"5. Conclusions","content":"\u003cp\u003eIn summary, age-dependent distribution suggested that high grade CIN peak at 25-44 years of age, women aged 25 years and older in China are recommended for a routine screening if conditions permit. For women \u0026gt;64 years old, patients infected with other HPV types should be also taken seriously. For women 25 to 64 years old, HPV 16 was particularly aggressive in the development of cervical premalignant lesions and malignant lesions. In general, HPV 16, 58, 52, 33, 31 and 18 were the most common genotypes in high grade CIN, vaccine including these main genotypes might be of great value for cervical cancer prevention in China. The current study was a single-center and retrospective analysis with a relatively small sample size, further confirmation and validation are needed in future multicenter prospective study with large samples.\u003c/p\u003e"},{"header":"6. Abbreviations","content":"\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.58695652173913%\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.471014492753625%\"\u003e\n \u003cp\u003eAbbreviations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.94202898550725%\"\u003e\n \u003cp\u003eFull name\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.58695652173913%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.471014492753625%\"\u003e\n \u003cp\u003eCIN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.94202898550725%\"\u003e\n \u003cp\u003eCervical intraepithelial neoplasia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.58695652173913%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.471014492753625%\"\u003e\n \u003cp\u003eHr-HPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.94202898550725%\"\u003e\n \u003cp\u003eHigh-risk human papillomavirus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.58695652173913%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.471014492753625%\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.94202898550725%\"\u003e\n \u003cp\u003eSquamous cervical carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.58695652173913%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.471014492753625%\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.94202898550725%\"\u003e\n \u003cp\u003ePolymerase chain reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"13.58695652173913%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.471014492753625%\"\u003e\n \u003cp\u003eASCCP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"65.94202898550725%\"\u003e\n \u003cp\u003eAmerican Society of Colposcopy and Cervical Pathology\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Peking Union Medical College Hospital (approval number S-K1604) and the study was retrospective, with only data been used and analyzed, no consent was need to participate, which was in compliance with the institutional and national policies concerning research approvals.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLK and YX conceived of the original idea for the study, interpreted results, obtained ethical approval, edited the paper and was overall guarantor. TX and XX carried out the statistical analysis and contributed to the preparation of the data set. LK, XX and RW interpreted results and contributed to the writing of the paper. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e1. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM: \u003cstrong\u003eEstimates of worldwide burden of cancer in 2008: GLOBOCAN 2008\u003c/strong\u003e. \u003cem\u003eInt J Cancer\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e127\u003c/strong\u003e(12):2893-2917.\u003c/p\u003e\n\u003cp\u003e2. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J: \u003cstrong\u003eCancer statistics in China, 2015\u003c/strong\u003e. \u003cem\u003eCA Cancer J Clin\u0026nbsp;\u003c/em\u003e2016, \u003cstrong\u003e66\u003c/strong\u003e(2):115-132.\u003c/p\u003e\n\u003cp\u003e3. Walboomers JM, Jacobs MV, Manos MM, Bosch FX, Kummer JA, Shah KV, Snijders PJ, Peto J, Meijer CJ, Mu\u0026ntilde;oz N: \u003cstrong\u003eHuman papillomavirus is a necessary cause of invasive cervical cancer worldwide\u003c/strong\u003e. \u003cem\u003eJ Pathol\u0026nbsp;\u003c/em\u003e1999, \u003cstrong\u003e189\u003c/strong\u003e(1):12-19.\u003c/p\u003e\n\u003cp\u003e4. Crow JM: \u003cstrong\u003eHPV: The global burden\u003c/strong\u003e. \u003cem\u003eNature\u0026nbsp;\u003c/em\u003e2012, \u003cstrong\u003e488\u003c/strong\u003e(7413):S2-3.\u003c/p\u003e\n\u003cp\u003e5. Bouvard V, Baan R, Straif K, Grosse Y, Secretan B, El Ghissassi F, Benbrahim-Tallaa L, Guha N, Freeman C, Galichet L\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eA review of human carcinogens--Part B: biological agents\u003c/strong\u003e. \u003cem\u003eLancet Oncol\u0026nbsp;\u003c/em\u003e2009, \u003cstrong\u003e10\u003c/strong\u003e(4):321-322.\u003c/p\u003e\n\u003cp\u003e6. Bruni L, Saura A, Montoliu A, Brotons M, Alemany L, Diallo MS, Afsar OZ, LaMontagne DS, Mosina L, Contreras M\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eHPV vaccination introduction worldwide and WHO and UNICEF estimates of national HPV immunization coverage 2010-2019\u003c/strong\u003e. \u003cem\u003ePrev Med\u0026nbsp;\u003c/em\u003e2020:106399.\u003c/p\u003e\n\u003cp\u003e7. Song F, Du H, Xiao A, Wang C, Huang X, Liu Z, Zhao M, Men H, Wu R: \u003cstrong\u003eType-specific Distribution of Cervical hrHPV Infection and the Association with Cytological and Histological Results in a Large Population-based Cervical Cancer Screening Program: Baseline and 3-year Longitudinal Data\u003c/strong\u003e. \u003cem\u003eJ Cancer\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e11\u003c/strong\u003e(20):6157-6167.\u003c/p\u003e\n\u003cp\u003e8. Wu P, Xiong H, Yang M, Li L, Lazare C, Cao C, Gao P, Meng Y, Zhi W, Lin S\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eCo-infections of HPV16/18 with other high-risk HPV types and the risk of cervical carcinogenesis: A large population-based study\u003c/strong\u003e. \u003cem\u003eGynecol Oncol\u0026nbsp;\u003c/em\u003e2019, \u003cstrong\u003e155\u003c/strong\u003e(3):436-443.\u003c/p\u003e\n\u003cp\u003e9. Schiffman M, Burk RD, Boyle S, Raine-Bennett T, Katki HA, Gage JC, Wentzensen N, Kornegay JR, Aldrich C, Tam T\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eA study of genotyping for management of human papillomavirus-positive, cytology-negative cervical screening results\u003c/strong\u003e. \u003cem\u003eJ Clin Microbiol\u0026nbsp;\u003c/em\u003e2015, \u003cstrong\u003e53\u003c/strong\u003e(1):52-59.\u003c/p\u003e\n\u003cp\u003e10. Li M, Du X, Lu M, Zhang W, Sun Z, Li L, Ye M, Fan W, Jiang S, Liu A\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003ePrevalence characteristics of single and multiple HPV infections in women with cervical cancer and precancerous lesions in Beijing, China\u003c/strong\u003e. \u003cem\u003eJournal of Medical Virology\u0026nbsp;\u003c/em\u003e2019, \u003cstrong\u003e91\u003c/strong\u003e(3):473-481.\u003c/p\u003e\n\u003cp\u003e11. Jiang W, Marshall Austin R, Li L, Yang K, Zhao C: \u003cstrong\u003eExtended Human Papillomavirus Genotype Distribution and Cervical Cytology Results in a Large Cohort of Chinese Women With Invasive Cervical Cancers and High-Grade Squamous Intraepithelial Lesions\u003c/strong\u003e. \u003cem\u003eAm J Clin Pathol\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e150\u003c/strong\u003e(1):43-50.\u003c/p\u003e\n\u003cp\u003e12. Wang H, Cheng X, Ye J, Xu X, Hong Y, Sui L, You Z, Xie X: \u003cstrong\u003eDistribution of human papilloma virus genotype prevalence in invasive cervical carcinomas and precancerous lesions in the Yangtze River Delta area, China\u003c/strong\u003e. \u003cem\u003eBMC Cancer\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e18\u003c/strong\u003e(1).\u003c/p\u003e\n\u003cp\u003e13. Vinokurova S, Wentzensen N, Kraus I, Klaes R, Driesch C, Melsheimer P, Kisseljov F, D\u0026uuml;rst M, Schneider A, von Knebel Doeberitz M: \u003cstrong\u003eType-dependent integration frequency of human papillomavirus genomes in cervical lesions\u003c/strong\u003e. \u003cem\u003eCancer Res\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e68\u003c/strong\u003e(1):307-313.\u003c/p\u003e\n\u003cp\u003e14. Hammer A, Rositch A, Qeadan F, Gravitt PE, Blaakaer J: \u003cstrong\u003eAge-specific prevalence of HPV16/18 genotypes in cervical cancer: A systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eInt J Cancer\u0026nbsp;\u003c/em\u003e2016, \u003cstrong\u003e138\u003c/strong\u003e(12):2795-2803.\u003c/p\u003e\n\u003cp\u003e15. Li Y, Wang Y, Jia C, Ma Y, Lan Y, Wang S: \u003cstrong\u003eDetection of human papillomavirus genotypes with liquid bead microarray in cervical lesions of northern Chinese patients\u003c/strong\u003e. \u003cem\u003eCancer Genet Cytogenet\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e182\u003c/strong\u003e(1):12-17.\u003c/p\u003e\n\u003cp\u003e16. Kj\u0026aelig;r SK, Frederiksen K, Munk C, Iftner T: \u003cstrong\u003eLong-term absolute risk of cervical intraepithelial neoplasia grade 3 or worse following human papillomavirus infection: role of persistence\u003c/strong\u003e. \u003cem\u003eJ Natl Cancer Inst\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e102\u003c/strong\u003e(19):1478-1488.\u003c/p\u003e\n\u003cp\u003e17. de Sanjose S, Quint WG, Alemany L, Geraets DT, Klaustermeier JE, Lloveras B, Tous S, Felix A, Bravo LE, Shin HR\u003cem\u003e\u0026nbsp;et al\u003c/em\u003e: \u003cstrong\u003eHuman papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study\u003c/strong\u003e. \u003cem\u003eLancet Oncol\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e11\u003c/strong\u003e(11):1048-1056.\u003c/p\u003e\n\u003cp\u003e18. Li N, Franceschi S, Howell-Jones R, Snijders PJ, Clifford GM: \u003cstrong\u003eHuman papillomavirus type distribution in 30,848 invasive cervical cancers worldwide: Variation by geographical region, histological type and year of publication\u003c/strong\u003e. \u003cem\u003eInt J Cancer\u0026nbsp;\u003c/em\u003e2011, \u003cstrong\u003e128\u003c/strong\u003e(4):927-935.\u003c/p\u003e\n\u003cp\u003e19. Coutl\u0026eacute;e F, Ratnam S, Ramanakumar AV, Insinga RR, Bentley J, Escott N, Ghatage P, Koushik A, Ferenczy A, Franco EL: \u003cstrong\u003eDistribution of human papillomavirus genotypes in cervical intraepithelial neoplasia and invasive cervical cancer in Canada\u003c/strong\u003e. \u003cem\u003eJournal of Medical Virology\u0026nbsp;\u003c/em\u003e2011, \u003cstrong\u003e83\u003c/strong\u003e(6):1034-1041.\u003c/p\u003e\n\u003cp\u003e20. Bosch FX, Burchell AN, Schiffman M, Giuliano AR, de Sanjose S, Bruni L, Tortolero-Luna G, Kjaer SK, Mu\u0026ntilde;oz N: \u003cstrong\u003eEpidemiology and Natural History of Human Papillomavirus Infections and Type-Specific Implications in Cervical Neoplasia\u003c/strong\u003e. \u003cem\u003eVaccine\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e26\u003c/strong\u003e:K1-K16.\u003c/p\u003e\n\u003cp\u003e21. Li C, Wu M, Wang J, Zhang S, Zhu L, Pan J, Zhang W: \u003cstrong\u003eA population-based study on the risks of cervical lesion and human papillomavirus infection among women in Beijing, People's Republic of China\u003c/strong\u003e. \u003cem\u003eCancer Epidemiol Biomarkers Prev\u0026nbsp;\u003c/em\u003e2010, \u003cstrong\u003e19\u003c/strong\u003e(10):2655-2664.\u003c/p\u003e\n\u003cp\u003e22. Schiffman M, Castle PE, Jeronimo J, Rodriguez AC, Wacholder S: \u003cstrong\u003eHuman papillomavirus and cervical cancer\u003c/strong\u003e. \u003cem\u003eLancet\u0026nbsp;\u003c/em\u003e2007, \u003cstrong\u003e370\u003c/strong\u003e(9590):890-907.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"human papillomavirus (HPV), genotypes distribution, cervical intraepithelial neoplasia (CIN), age","lastPublishedDoi":"10.21203/rs.3.rs-667054/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-667054/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eHuman papillomavirus (HPV) has been confirmed as a major causative factor for malignant transformation of cervical epithelial cells and for the development of cervical intraepithelial neoplasia (CIN) and invasive cervical cancer. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe collected the cervical cell samples of women who visited the gynecological clinic of Peking Union Medical College Hospital between October 2017 and May 2020 and submitted them to the HPV genotyping test. We analyzed the distribution of single-type HPV genotypes in CIN of different severities and the age-dependent prevalence for single-type HPV infection. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In both CIN2 and CIN3 group, HPV 16, 58, 52, 33 and 31/18 were detected as top 5 HPV types, which accounts for 89.25% and 88.54% of single HPV infection incidence respectively. HPV 16 was the dominant genotype in both CIN2 and CIN3, accounted for 46.24% and 55.21%, respectively. The prevalence of HPV 16 was the most frequent in all the age groups, except \u0026gt;64 years group in CIN3. The prevalence of HPV 16 and 33 increased obviously with increasing grade of CIN (chi-squared test for trend, \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001), while HPV 18, 31, 52 and 58 showed the opposite trends. The peak of the incidence of CIN3 was observed at 25~34 years (33.68%), followed by 35-44 years (31.58%). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eHigh grade CIN peak at 25-44 years, women of this age are recommended for normative screening if conditions permit. HPV 16 was particularly aggressive in the development of cervical premalignant lesions and malignant lesions in almost all age groups, except \u0026gt;64 years group in CIN3. For women \u0026gt;64 years old, patients infected with other HPV types should be also taken seriously. In general, HPV 16, 58, 52, 33, 31 and 18 were the most common genotypes in high grade CIN, and vaccine including these predominant genotypes might be of great significance for cervical cancer prevention in China.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","manuscriptTitle":"Retrospective Analysis of the Association Between Cervical Squamous Intraepithelial Lesions and Human Papillomavirus Genotypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-07-02 17:45:15","doi":"10.21203/rs.3.rs-667054/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5b7dbec4-440b-404d-a2bf-ef04452a2a82","owner":[],"postedDate":"July 2nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":5423490,"name":"Immunology"},{"id":5423491,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2021-08-28T13:51:31+00:00","versionOfRecord":[],"versionCreatedAt":"2021-07-02 17:45:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-667054","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-667054","identity":"rs-667054","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}