A large-scale retrospective study on the prevalence of human papillomavirus and its genotypes in humans referred to a medical laboratory in Isfahan, central Iran

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It is the most important cause of cervical cancer. The present study aimed to determine the prevalence of HPV infection and HPV genotypes in the recordings of patients referred to Dr. Sharifi Medical Laboratory in Isfahan, central Iran. Materials and Methods In a retrospective study, the HPV PCR and genotyping results of 5643 patients including 4999 (88.6%) females and 644 (11.4%) males from May 2012 to August 2024 were studied. The available demographics, sex and age, were also recorded and analyzed. Results Of 5643 studied patient, 888 (15.7%) were HPV-positive. Genotype 6 was the most prevalent (9.1%), and genotypes 30 and 71 were the least prevalent (0.017%) identified genotypes. Out of 888, 470 (47.1%) and 418 (52.9%) were high-risk and low-risk HPV genotypes, respectively. HPV 16 was the most prevalent among high-risk genotypes followed by HPV 53 and 18. The HPV infection was significantly higher in patients under 20 years old and also in females compared to males. Conclusion Based on the results of the present study, the rate of HPV infection in Isfahan is close to that of most other regions in Iran. The prevalence of HPV infection with low- and high-risk genotypes was both higher in women. High-risk genotypes caused the majority of infections. Younger ages were the most at-risk group for the infection. Human papillomavirus Genotype Iran Figures Figure 1 1. Introduction Human papillomaviruses (HPVs) are members of the family of Papillomaviridae. These viruses are 50–60 nm in diameter, non-enveloped, with double-stranded circular genomic DNA ( 1 , 2 ). HPV infects epithelial cells in different mucous membranes and skin surfaces ( 3 ). HPV enters the body through cutaneous or mucosal trauma and is transmitted by mucosa-to-mucosa or skin-to-skin contact. Infection with HPV is the most common sexually transmitted disease, however, the immune system generally overcomes it. The HPV infection is related to common anogenital warts and other non-dermatological diseases. Studies have shown that HPV plays a role in the development of some types of cancer, especially cervical cancer and other neoplasms ( 4 ). Generally, the virus is genetically categorized into high-risk (HR-HPVs) and low-risk (LR-HPVs) genotypes. HR-HPVs are responsible for oropharyngeal and anogenital cancers, for instance; vaginal, anal, vulvar, penile, and cervical cancers in contrast to cutaneous and anogenital warts that are linked to LR-HPVs ( 5 ). More than 100 genotypes of HPVs have been identified, out of 100, anogenital epithelium infections linked to almost 40 genotypes ( 6 , 7 ). Of these, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68 HPV genotypes are oncogenic and are responsible for severe lesions and more than 98% of all cervical tumors ( 8 ). Among the mentioned HR-HPVs, HPV-16 and HPV-18 are the most prevalent oncogenic genotypes and are significantly related to the development of cervical, anal, vaginal, vulvar, penile, and oropharyngeal cancers. The latter two genotypes can persist in the body for a long time and cause the formation of precancerous lesions which may develop into cancer if left unmanaged ( 3 ). A diagnostic method for early detection of cervical cancer is HPV testing for the detection of high-risk genotypes. A prophylactic HPV vaccine is also available for HPV 16, 18, 31, 33, 45, 52, and 58 genotypes. Moreover, routine tests for early detection of cervical cancer can be performed such as cervical cytology testing. Studies have shown that women over thirty years old with abnormal cervical cytology have high rates of cervical lesions, mainly invasive cervical disease if they simultaneously occur with high-risk HPV infection ( 9 ). The pooled HPV prevalence in patients with cervical adenocarcinoma is estimated at 78.4% (95% CI: 76.2–80.3). The HPV16 and HPV18 were the most frequently viral genotypes with an estimated prevalence of 49.8% (95% CI: 46.9–52.6) and 45.3% (95% CI: 42.8–47.8), respectively ( 10 ). There was no comprehensive and updated study on the prevalence and genotypes of HPV in Isfahan, thus the present study aimed to determine the prevalence of HPV infection and genotypes in the HPV testing records of humans referred to a medical laboratory in Isfahan, central Iran. 2. Material & Methods 2.1. Study time and region The present retrospective study was carried out on HPV testing records of humans referred to Dr. Sharifi Medical Laboratory in Isfahan, central Iran, from May 2012 to August 2024. 2.2. Study population and analyses The recordings of 5643 humans with HPV screening tests were studied. All women were referred to the laboratory for HPV screening and had no cervical lesions at the time. A handful of cases were from external warts, of which the type and sample were not recorded. Thus, we could not exclude them. All available data including HPV positivity, genotyping results, and the two available demographics (sex and age) were analyzed. 2.3. Laboratory diagnosis method DNA extraction has been performed on pap-liquid, external genital warts, Urethral swabs, and semen, using commercial DNA purification kits, QIAamp® Viral DNA mini-Kit (Qiagen Co, Germany). For virus detection and genotyping, commercial kits such as SimReal™ HPV MLA Screening Kit (Simbiolab Co, Iran) and HPV Direct Flow CHIP kit (Master Dignostica Co, Spain) were used, respectively. The kits were able to identify 36 genotypes of HPV (high-risk HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73 and 82, and low-risk HPV 6, 11, 40, 42, 43, 44, 54, 55, 61, 62, 67, 69, 70, 71, 72, 81, 84 and 89) by PCR (polymerase chain reaction), followed by reverse hybridization on a membrane containing specific probes. High-risk cases are re-checked by HPV Genotyping 14 Real-Time Quant (Sacace Biotechnologies Co, Italy). The kit was able to identify 14 genotypes of HPV (high-risk HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68) by TaqMan real-time PCR method. 2.4. Statistical analysis Data were analyzed by IBM SPSS Statistics for Windows (Version 23.0) IBM Corp. using Chi-square and Mann–Whitney U tests. P values < 0.05 were considered statistically significant. Limitations : During 12 years some kits from different companies were used in the laboratory and there may be minor variations in their sensitivity and specificity. The patients’ age and sex were available to obtain and other variables were not recorded to be used in statistical analyses. Only a handful of patients with external warts were among the studied population and unfortunately, the type of sample was not recorded at reception and it is now not available for exclusion or statistical analysis. 3. Result In the present study, the recordings of HPV testing results of 5643 patients including 4999 (88.6%) females and 644 (11.4%) males were studied. The Mean age of the studied population was 34.39 ± 8.34 (Std) years. The minimum and maximum ages were 14 and 98 years old, respectively. Of 5643 patients, 888 (15.7%) and 4755 (84.3%) were HPV-positive and HPV-negative, respectively. HPV genotype 6 was the most prevalent (9.1%), and genotypes 30 and 71 were the least prevalent (0.017%) identified genotypes. (Table 1 ). Table 1 The prevalence of HPV genotypes in the studied patients in Isfahan, Central Iran. Genotype Frequency n (%) Total Of 888 HPVs High/Low Risk Positive Negative Genotype 6 514 (9.1%) 5129 (90.9%) 5643 57.88% Low Risk Genotype 11 133 (2.35%) 5510 (97.64%) 5643 15% Low Risk Genotype16 124 (2.19%) 5519 (97.80%) 5643 14% High Risk Genotype 18 54 (0.95%) 5589 (99.04%) 5643 6.08% High Risk Genotype 26 2 (0.03%) 5641 (99.96%) 5643 0.22% High Risk Genotype 30 1 (0.01%) 5642 (99.98%) 5643 0.11% Low Risk Genotype 31 41 (0.72%) 5602 (99.27%) 5643 4.61% High Risk Genotype 33 6 (0.10%) 5637 (99.89%) 5643 0.67% High Risk Genotype 35 24 (0.42%) 5619 (99.57%) 5643 2.70% High Risk Genotype 39 52 (0.92%) 5591 (99.07%) 5643 5.85% High Risk Genotype 40 30 (0.53%) 5613 (99.46%) 5643 3.37% Low Risk Genotype 42 103 (1.82%) 5540 (98.17%) 5643 11.60% Low Risk Genotype 43 20 (0.35%) 5623 (99.64%) 5643 2.25% Low Risk Genotype 44 18 (0.31%) 5625 (99.68%) 5643 2.02% Low Risk Genotype 45 26 (0.46%) 5617 (99.53%) 5643 2.92% High Risk Genotype 51 32 (0.56%) 5611 (99.43%) 5643 3.60% High Risk Genotype 52 40 (0.70%) 5603 (99.29%) 5643 4.50% High Risk Genotype 53 117 (2.07%) 5526 (97.92%) 5643 13.17% High Risk Genotype 54 50 (0.88%) 5593 (99.11%) 5643 5.63% Low Risk Genotype 55 9 (0.15%) 5634 (99.84%) 5643 1.01 Low Risk Genotype 56 43 (0.76%) 5600 (99.23%) 5643 4.84% High Risk Genotype 58 37 (0.65%) 5606 (99.34%) 5643 4.16% High Risk Genotype 59 22 (0.38%) 5621 (99.61%) 5643 2.47% High Risk Genotype 61 11 (0.19%) 5632 (99.80%) 5643 1.23% Low Risk Genotype 62 29 (0.51%) 5614 (99.48%) 5643 3.26% Low Risk Genotype 66 42 (0.74%) 5601 (99.25%) 5643 4.72% High Risk Genotype 67 18 (0.31%) 5625 (99.68%) 5643 2.02% Low Risk Genotype 68 32 (0.56%) 5611 (99.43%) 5643 3.6% High Risk Genotype 70 2 (0.03%) 5641 (99.96%) 5643 0.22% Low Risk Genotype 71 1 (0.01%) 5642 (99.98%) 5643 0.11% Low Risk Genotype 73 9 (0.15%) 5634 (99.84%) 5643 1.01% High Risk Genotype 74 9 (0.15%) 5634 (99.84%) 5643 1.01% Low Risk Genotype 81 17 (0.30%) 5626 (99.69%) 5643 1.57% Low Risk Genotype 82 12 (0.21%) 5631 (99.78%) 5643 1.35% High Risk Genotype 84 9 (0.15%) 5634 (99.84%) 5643 1.01% Low Risk Genotype 90 2 (0.03%) 5641 (99.96%) 5643 0.22% Low Risk Genotype 91 7 (0.12%) 5636 (99.87%) 5643 0.78% Low Risk Considering the HPV genotypes, 470 (47.1%) and 418 (52.9%) out of 888 were high- and low-risk HPV, respectively. The prevalence of HPV infection was significantly higher in women compared to men ( P < 0.001; OR = 1.7) (Table 2 ). Table 2 P value and odds ratio estimated for HPV positivity among sexes Sex HPV Total Odds ratio 95% CI P Positive Negative Female 821 (16.4%) 4178 (83.6%) 4999 1.7 1.3–2.2 < 0.001 Male 67 (10.4%) 577 (89.6%) 644 1 Total 888 (15.7%) 4755 (84.3%) 5643 The prevalence of high-risk HPV infections in females was significantly higher compared to males ( P < 0.001; OR = 2.05) (Table 3 ). Table 3 P value and odds ratio estimated for high and low-risk HPV genotypes positivity in different sexes Sex HPV Risk Total Odds ratio 95% CI P High Low Female 452 (55.1%) 369 (44.9%) 821 2.05 1.37–3.05 < 0.001 Male 18 (26.9%) 49 (73.1%) 67 1 Total 470 (52.9%) 418 (47.1%) 888 The mean age was 33 years in HPV-positive patients compared to 34.6 years in HPV-negative ones. The 1.6-year difference in mean age was significant statistically ( P < 0.001) (Table 4 ). Table 4 Mean age comparison in HPV positive and negative studied humans HPV Mean Std. Deviation Mean rank P Positive 33.054 8.188 2510.54 < 0.001 Negative 34.645 8.343 2838.77 The mean age was 33.18 years in patients infected with high-risk HPV genotypes compared to 32.9 years in low-risk HPV-infected ones. The difference in mean age was not significant statistically ( P = 0.25) (Table 5 ) Table 5 Mean age comparison in patients infected with high risk with low-risk HPV genotypes Risk Mean Std. Deviation Mean rank P Low 33.182 7.923 447.27 0.426 High 32.942 8.422 433.62 The highest HPV infection was observed in patients under 20 years old followed by the age group 20–40 years old (Table 6 ). However, the distribution of low-risk and high-risk genotypes in different age groups was not significantly different (Table 6 ) Table 6 HPV infection, high-risk and low-risk HPV genotypes prevalence in different age groups Age groups HPV positivity Total P HPV genotype Total P Positive Negative Low risk High risk < 20 12 (20.7%) 46 (79.3%) 58 0.014 6 (50%) 6 (50%) 12 0.825 20–40 707 (16.6%) 3554 (83.4%) 4261 325 (46%) 382 (54%) 706 40–60 154 (12.8%) 1052 (87.2%) 1206 77 (50%) 77 (50%) 154 60–80 6 (12.8%) 41 (87.2%) 47 3 (50%) 3 (50%) 6 > 80 0 (0%) 1 (100%) 1 - - - Total 879 (15.8%) 4694 (84.2%) 5573 411 (46.8%) 468 (53.2%) 879 Among 888 HPV-positive humans, 392 (44.1%), 215 (24.2%), 276 (31.1%), and 5 (0.6%) were infected by single, double, triple and quadruple genotypes, respectively. The peak prevalence was observed in 2015 followed by 2018 ( P < 0.001) shown in Table 7 and Fig. 1 . The HPV infection has dramatically decreased from 2022. Table 7 The detailed HPV infection rate as well as genotypes during the studied years. HPV Total samples P HPV-Risk out of 888 Of 888 P Year Positive Negative Low High 2012 0 (0%) 2 (100%) 2 < 0.001 0 0 0 < 0.001 2013 0 (0%) 6 (100%) 6 0 0 0 2014 0 (0%) 11 (100%) 11 0 0 0 2015 14 (24.6%) 43 (75.4%) 57 8 (57.1%) 6 (42.9%) 14 (100%) 2016 37 (16.7%) 185 (83.3%) 222 23 (62.2%) 14 (37.8%) 37 (100.0%) 2017 53 (16.7%) 265 (83.3%) 318 39 (73.6%) 14 (26.4%) 53 (100.0%) 2018 139 (20.7%) 533 (79.3%) 672 48 (34.5%) 91 (65.5%) 139 (100.0%) 2019 168 (19%) 716 (81%) 884 73 (43.5%) 95 (56.5%) 168 (100.0%) 2020 152 (20.4%) 594 (79.6%) 746 78 (51.3%) 74 (48.7%) 152 (100.0%) 2021 101 (20.4%) 394 (79.6%) 495 55 (54.5%) 46 (45.5%) 101 (100.0%) 2022 91 (16.6%) 458 (83.4%) 549 46 (50.5%) 45 (49.5%) 91 (100%) 2023 94 (9.4%) 903 (90.6%) 997 34 (36.2%) 60 (63.8%) 94 (100.0%) 2024 39 (5.7%) 645 (94.3%) 684 14 (35.9%) 25 (64.1%) 39 (100.0%) Total 888 (15.7%) 4755 (84.3%) 5643 418 (47.1%) 470 (52.9%) 888 (100.0%) The trend of high and total HPV, as well as low and high-risk genotypes during the studied years, is shown in Fig. 1 . Discussion In the present study, a considerable number of humans (5643 humans) were studied for HPV infection during 12 years, among which, 15.7% were infected by HPV. HPV genotype 6 was the most prevalent, and genotypes 30, 83, and 71 were the least prevalent identified ones. Furthermore, 47.1% of patients were infected by high-risk and 52.9% were infected by low-risk HPV genotypes. The prevalence of both HPV infection and high-risk genotypes was significantly higher in women compared to men. The highest HPV infection was observed in young patients, age under 20 years old. HPV 16 was the most prevalent high-risk genotype followed by HPV 53 and 18. Studies on the prevalence of HPV infection and its genotypes are important regarding designing monitoring programs for the diagnosis of cervical cancer and evaluation of HPV vaccine efficacy in women ( 11 ). In a meta-analysis, the overall prevalence of HPV in Iranian women was estimated as 23%. They reported the highest and the lowest prevalence in Tehran and Isfahan provinces as 97% and 2.2%, respectively ( 12 ). In the present study, in Isfahan, the prevalence of the infection in a large number of people was lower than the average prevalence in Iran. Vazifehdoost et al. (2022) ( 13 ), reported HPV infection in 57.8% of women in Tehran, Iran, which is considerably higher than our results in Isfahan (16.4%). Similarly they reported the highest prevalence of HPV infection in young patients, 25–34 years-old. Like our results, they reported the predominant genotype as HPV6. Farahmand et al. (2020) ( 14 ), studied 571 healthy Iranian women with cytology specimens and 113 cervical cancer tissues. They reported HPV infection in 24% of studied women among whom 3.3% were positive for high-risk HPV and 11.6% for low-risk HPV. In the present study, the prevalence of HPV infection in Isfahan was 15.7%, which is lower than the results of Farahmand et al. in Iranian women. Furthermore, contrary to their results, high-risk HPV genotypes were predominant in the present study (7.5% out of 5643). Similarly they reported HPV6 (9.3%) as the most prevalent genotype. Furthermore, they found a 78.8% HPV positivity among patients with cervical cancer, consisting of 43.4% HPV16, 8% HPV18, and 27.4% an unknown genotype. In 2019 the most prevalent low-risk HPV genotypes referred from different provinces of Iran to Tehran in males and females were reported as HPV-6 (77.7% and 43.3%) and HPV-11 (13.7% and 11.4%). The most prevalent high-risk HPV genotypes were HPV-16 (5.5% and 16.6%) ( 15 ). Similarly, in the present study, the most prevalent low-risk and high-risk genotypes in HPV-positive patients were HPV6 (56.6%) and 16 (14%) in Isfahan. Contrary to our findings, a high number of HPV infections was observed in 30–44 years of age (51.8%), peaking between 30 and 32 years ( 15 ). Our results showed the highest prevalence in patients under 20 years old, followed by the age group 20–40 years old. Jason P Trama et al. (2022) ( 16 ), studied the result of 23580 patients' HPV testing in Medical Diagnostic Laboratories, LLC (Hamilton, NJ, USA) between August 2020 and August 2021. The high-risk HPV genotypes were reported in 9.8%, with HPV 52 (1.4%), HPV 39 (1.3%), HPV 51 (1.3%), and HPV 16 (1.2%) being the most frequent. Multiple high-risk HPV infection was observed in 1.3% of all patients. High-risk HPV was more prevalent in patients under 25 years old (< 21-year-olds, 24.6%, and 21-25-year-olds, 25.4%). Their results were very close to our findings that 418 (7.4%) out of 5643 were high-risk HPVs and the young patients were the most affected age groups. Bakhshani et al. (2023) ( 11 ) studied the HPV infection and the genotypes in Mashhad. They reported HPV infection in 31.8% of women. HPV 31 (3%), HPV 16 (2.5%), HPV 51 (2.2%), HPV 18 (2%), and HPV 66 (1.8%) were the most frequently found high-risk HPV. Moreover, HPV 6 (9.2%), HPV 53 (4.7%), and HPV 42 (2.8%) were the most prevalent low-risk HPV genotypes. In the present study, 15.7% of a large population in Isfahan were HPV-positive, which is considerably lower than their findings in Mashhad. Genotype 6 was the most prevalent 9.1%, and genotypes 30, 83, and 71 were the least prevalent 0.017% identified genotypes in Isfahan. In a meta-analysis in 2020 ( 17 ), all data from Iran on HPV prevalence and genotypes among women with normal cervical cytology, premalignant lesions, and cervical cancer were analyzed and published. The HPV prevalence in the studied population in Iran was found to be 9% in women with a normal cervix, 55% in atypical squamous cells, and 58% and 69% in women with low and high-grade squamous intraepithelial lesions, respectively. Furthermore, the prevalence was 81% among patients with invasive cervical cancer. HPV 16 was the most reported HPV type, followed by HPV 18 in all studied groups. In the present study, HPV 16 was the most prevalent among high-risk genotypes followed by HPV 53 and 18. The rate of HPV infection in Isfahan increased to 2015 and then it was steady until 2021 and decreased afterward. The decrease in the prevalence of HPV infection in recent years could be a result of massive health education on HPV and its danger among the general population of Iran by different media thus awareness has increased. This may also show the increase in knowledge and applying preventive measures such as vaccination by the human population in the country. Conclusion According to the results of the present study, the rate of HPV positivity in Isfahan is close to or in some cases lower than most of other regions in Iran. During the last three years, the HPV infection has decreased dramatically in Isfahan. The prevalence of HPV infection with low- and high-risk genotypes was both higher in women. More than half of HPV infections were caused by high-risk genotypes. Younger ages are the most at-risk group for the infection, and HPV 16 and HPV 6 were the most prevalent high-risk and low-risk HPV genotypes, respectively. Declarations Ethics approval and consent to participate The present study was ethically approved by the ethical committee of the Urmia Branch, Islamic Azad University under the ethical code of IR.IAU.URMIA.REC.1403.012. Data including test results, age, and sex of the patients were obtained from the medical laboratory without their names and reported as frequency and percentage. Clinical Trial Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no conflict of interest. Funding The present study was not financially supported. Author Contribution B.B. and M.S. Performed the laboratory work. A.H. and S.V. collected the data. R.J. analyzed the data, and edited the manuscript. M.S. and M.V. wrote the main manuscript. Acknowledgement The authors would like to thank Dr. Forough Sharifi, the supervisor of Dr. Sharifi Medical Laboratory in Isfahan, for her help and contribution. Data Availability Data would be available from corresponding author in a reasonable request. References Cubie HA. Diseases associated with human papillomavirus infection. Virology. 2013;445(1–2):21–34. Harden ME, Munger K. Human papillomavirus molecular biology. Mutat Res Reviews Mutat Res. 2017;772:3–12. Wolf J, Kist LF, Pereira SB, Quessada MA, Petek H, Pille A, et al. Human papillomavirus infection: Epidemiology, biology, host interactions, cancer development, prevention, and therapeutics. Rev Med Virol. 2024;34(3):e2537. Brianti P, De Flammineis E, Mercuri SR. 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J Med Virol. 2022;94(7):3376–85. Farahmand Z, Soleimanjahi H, Garshasbi M, Hasanzadeh M, Zafari E. Distribution of the most common types of HPV in Iranian women with and without cervical cancer. Women Health. 2021;61(1):73–82. Mobini Kesheh M, Keyvani H. The Prevalence of HPV Genotypes in Iranian Population: An Update. Iran J Pathol. 2019;14(3):197–205. Trama JP, Trikannad C, Yang JJ, Adelson ME, Mordechai E. High-Risk HPV Genotype Distribution According to Cervical Cytology and Age. Open forum Infect Dis. 2022;9(11):ofac595. Salavatiha Z, Farahmand M, Shoja Z, Jalilvand S. A meta-analysis of human papillomavirus prevalence and types among Iranian women with normal cervical cytology, premalignant lesions, and cervical cancer. J Med Virol. 2021;93(8):4647–58. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5262865","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":385019370,"identity":"20e2a8a8-c230-4b93-bac5-3848a5742e67","order_by":0,"name":"Bahram Bagherpour","email":"","orcid":"","institution":"Isfahan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Bahram","middleName":"","lastName":"Bagherpour","suffix":""},{"id":385019371,"identity":"adce319e-6a98-4d40-9ca1-00c018e7aa93","order_by":1,"name":"Rasool Jafari","email":"","orcid":"","institution":"Urmia University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Rasool","middleName":"","lastName":"Jafari","suffix":""},{"id":385019372,"identity":"608d737e-2fd7-477b-ad48-63a2e44370be","order_by":2,"name":"Alireza Hassanpour","email":"","orcid":"","institution":"Urmia Branch, Islamic Azad University, Urmia","correspondingAuthor":false,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Hassanpour","suffix":""},{"id":385019373,"identity":"22802a58-ef2c-41bb-ad9d-41e5963f04e0","order_by":3,"name":"Sevda Valilou","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sevda","middleName":"","lastName":"Valilou","suffix":""},{"id":385019374,"identity":"5d3cdc7f-aa71-49c0-812c-2aeaf86ad848","order_by":4,"name":"Mohammadreza Valilou","email":"","orcid":"","institution":"Tabriz Branch, Islamic Azad University, Tabriz","correspondingAuthor":false,"prefix":"","firstName":"Mohammadreza","middleName":"","lastName":"Valilou","suffix":""},{"id":385019375,"identity":"04e8298c-243e-43a6-8113-3cf703fdb0e5","order_by":5,"name":"Marzieh Safari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIie2PP0vEMBiH3xCoS8C15Y7rV3hdxIJ4XyUlUMdz7CCS6aaC632cQOBuqXbNcQ4nhc4nLhVFfBUPXNKuDnmG/CF58vsFIBD4h6ChQYKBVLM9bS/F70HsVbKjgoYjKcW4Mjc/EynwrYAdL3a+eWgP+/IJ8MSy1/KmmZ6uJDv0cLHwKvU1oqw7SCvFkxp3InaSJxXEmfYppgCZL6mPWZhEkwJOwoT+gr4UbDow+ScpTcvfND6KlFLeBxVXMJ1rUpyKKMUIdDIaTnEdB7m2dLONMo1KnNXPy6zCoWIFf+lv7Sy9V3yrP67ms42yri/vvMoR8WfNND01JgQCgUBgiC99lVdupKGHjAAAAABJRU5ErkJggg==","orcid":"","institution":"Urmia Branch, Islamic Azad University, Urmia","correspondingAuthor":true,"prefix":"","firstName":"Marzieh","middleName":"","lastName":"Safari","suffix":""}],"badges":[],"createdAt":"2024-10-14 17:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5262865/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5262865/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71805345,"identity":"53ff0b70-88c3-4880-9dec-25424e14c1d9","added_by":"auto","created_at":"2024-12-18 17:24:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":60547,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe HPV infection rate during studied years.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5262865/v1/7ea8c987960ab71bc1f7de14.png"},{"id":80281612,"identity":"492e08eb-c361-4bc7-abd5-8913d32cc417","added_by":"auto","created_at":"2025-04-10 06:02:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1370818,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5262865/v1/f0b33e46-7107-423e-b2b1-260e1cdfcc56.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A large-scale retrospective study on the prevalence of human papillomavirus and its genotypes in humans referred to a medical laboratory in Isfahan, central Iran","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHuman papillomaviruses (HPVs) are members of the family of Papillomaviridae. These viruses are 50\u0026ndash;60 nm in diameter, non-enveloped, with double-stranded circular genomic DNA (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). HPV infects epithelial cells in different mucous membranes and skin surfaces (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). HPV enters the body through cutaneous or mucosal trauma and is transmitted by mucosa-to-mucosa or skin-to-skin contact. Infection with HPV is the most common sexually transmitted disease, however, the immune system generally overcomes it.\u003c/p\u003e \u003cp\u003eThe HPV infection is related to common anogenital warts and other non-dermatological diseases. Studies have shown that HPV plays a role in the development of some types of cancer, especially cervical cancer and other neoplasms (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Generally, the virus is genetically categorized into high-risk (HR-HPVs) and low-risk (LR-HPVs) genotypes.\u003c/p\u003e \u003cp\u003eHR-HPVs are responsible for oropharyngeal and anogenital cancers, for instance; vaginal, anal, vulvar, penile, and cervical cancers in contrast to cutaneous and anogenital warts that are linked to LR-HPVs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). More than 100 genotypes of HPVs have been identified, out of 100, anogenital epithelium infections linked to almost 40 genotypes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Of these, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68 HPV genotypes are oncogenic and are responsible for severe lesions and more than 98% of all cervical tumors (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Among the mentioned HR-HPVs, HPV-16 and HPV-18 are the most prevalent oncogenic genotypes and are significantly related to the development of cervical, anal, vaginal, vulvar, penile, and oropharyngeal cancers. The latter two genotypes can persist in the body for a long time and cause the formation of precancerous lesions which may develop into cancer if left unmanaged (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA diagnostic method for early detection of cervical cancer is HPV testing for the detection of high-risk genotypes. A prophylactic HPV vaccine is also available for HPV 16, 18, 31, 33, 45, 52, and 58 genotypes. Moreover, routine tests for early detection of cervical cancer can be performed such as cervical cytology testing. Studies have shown that women over thirty years old with abnormal cervical cytology have high rates of cervical lesions, mainly invasive cervical disease if they simultaneously occur with high-risk HPV infection (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The pooled HPV prevalence in patients with cervical adenocarcinoma is estimated at 78.4% (95% CI: 76.2\u0026ndash;80.3). The HPV16 and HPV18 were the most frequently viral genotypes with an estimated prevalence of 49.8% (95% CI: 46.9\u0026ndash;52.6) and 45.3% (95% CI: 42.8\u0026ndash;47.8), respectively (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). There was no comprehensive and updated study on the prevalence and genotypes of HPV in Isfahan, thus the present study aimed to determine the prevalence of HPV infection and genotypes in the HPV testing records of humans referred to a medical laboratory in Isfahan, central Iran.\u003c/p\u003e"},{"header":"2. Material \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study time and region\u003c/h2\u003e \u003cp\u003eThe present retrospective study was carried out on HPV testing records of humans referred to Dr. Sharifi Medical Laboratory in Isfahan, central Iran, from May 2012 to August 2024.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study population and analyses\u003c/h2\u003e \u003cp\u003eThe recordings of 5643 humans with HPV screening tests were studied. All women were referred to the laboratory for HPV screening and had no cervical lesions at the time. A handful of cases were from external warts, of which the type and sample were not recorded. Thus, we could not exclude them. All available data including HPV positivity, genotyping results, and the two available demographics (sex and age) were analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. \u003cem\u003eLaboratory diagnosis method\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eDNA extraction has been performed on pap-liquid, external genital warts, Urethral swabs, and semen, using commercial DNA purification kits, QIAamp\u0026reg; Viral DNA mini-Kit (Qiagen Co, Germany). For virus detection and genotyping, commercial kits such as SimReal\u0026trade; HPV MLA Screening Kit (Simbiolab Co, Iran) and HPV Direct Flow CHIP kit (Master Dignostica Co, Spain) were used, respectively. The kits were able to identify 36 genotypes of HPV (high-risk HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73 and 82, and low-risk HPV 6, 11, 40, 42, 43, 44, 54, 55, 61, 62, 67, 69, 70, 71, 72, 81, 84 and 89) by PCR (polymerase chain reaction), followed by reverse hybridization on a membrane containing specific probes. High-risk cases are re-checked by HPV Genotyping 14 Real-Time Quant (Sacace Biotechnologies Co, Italy). The kit was able to identify 14 genotypes of HPV (high-risk HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68) by TaqMan real-time PCR method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed by IBM SPSS Statistics for Windows (Version 23.0) IBM Corp. using Chi-square and Mann\u0026ndash;Whitney U tests. \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eDuring 12 years some kits from different companies were used in the laboratory and there may be minor variations in their sensitivity and specificity. The patients\u0026rsquo; age and sex were available to obtain and other variables were not recorded to be used in statistical analyses. Only a handful of patients with external warts were among the studied population and unfortunately, the type of sample was not recorded at reception and it is now not available for exclusion or statistical analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cp\u003eIn the present study, the recordings of HPV testing results of 5643 patients including 4999 (88.6%) females and 644 (11.4%) males were studied. The Mean age of the studied population was 34.39\u0026thinsp;\u0026plusmn;\u0026thinsp;8.34 (Std) years. The minimum and maximum ages were 14 and 98 years old, respectively. Of 5643 patients, 888 (15.7%) and 4755 (84.3%) were HPV-positive and HPV-negative, respectively. HPV genotype 6 was the most prevalent (9.1%), and genotypes 30 and 71 were the least prevalent (0.017%) identified genotypes. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe prevalence of HPV genotypes in the studied patients in Isfahan, Central Iran.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eFrequency n (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eOf 888 HPVs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHigh/Low Risk\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative\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\u003eGenotype 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e514 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5129 (90.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e133 (2.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5510 (97.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e124 (2.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5519 (97.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54 (0.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5589 (99.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (0.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5641 (99.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5642 (99.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (0.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5602 (99.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (0.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5637 (99.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24 (0.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5619 (99.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52 (0.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5591 (99.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30 (0.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5613 (99.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103 (1.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5540 (98.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20 (0.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5623 (99.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18 (0.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5625 (99.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26 (0.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5617 (99.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32 (0.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5611 (99.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 (0.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5603 (99.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e117 (2.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5526 (97.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50 (0.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5593 (99.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (0.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5634 (99.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43 (0.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5600 (99.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37 (0.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5606 (99.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (0.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5621 (99.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11 (0.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5632 (99.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29 (0.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5614 (99.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42 (0.74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5601 (99.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.72%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18 (0.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5625 (99.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32 (0.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5611 (99.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (0.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5641 (99.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (0.01%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5642 (99.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (0.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5634 (99.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (0.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5634 (99.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17 (0.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5626 (99.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (0.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5631 (99.78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (0.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5634 (99.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (0.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5641 (99.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenotype 91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (0.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5636 (99.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eConsidering the HPV genotypes, 470 (47.1%) and 418 (52.9%) out of 888 were high- and low-risk HPV, respectively. The prevalence of HPV infection was significantly higher in women compared to men (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;1.7) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value and odds ratio estimated for HPV positivity among sexes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHPV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative\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\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e821 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4178 (83.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.3\u0026ndash;2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" 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\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e577 (89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e888 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4755 (84.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe prevalence of high-risk HPV infections in females was significantly higher compared to males (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;2.05) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value and odds ratio estimated for high and low-risk HPV genotypes positivity in different sexes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHPV Risk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\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\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e452 (55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e369 (44.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.37\u0026ndash;3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" 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\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (73.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e470 (52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e418 (47.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe mean age was 33 years in HPV-positive patients compared to 34.6 years in HPV-negative ones. The 1.6-year difference in mean age was significant statistically (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean age comparison in HPV positive and negative studied humans\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\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean rank\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\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\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2510.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" 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\u003e\u003cstrong\u003eNegative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2838.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe mean age was 33.18 years in patients infected with high-risk HPV genotypes compared to 32.9 years in low-risk HPV-infected ones. The difference in mean age was not significant statistically (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.25) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean age comparison in patients infected with high risk with low-risk 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\u003eRisk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStd. Deviation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean rank\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\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\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e447.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" align=\"char\"\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e433.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003eThe highest HPV infection was observed in patients under 20 years old followed by the age group 20\u0026ndash;40 years old (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e). However, the distribution of low-risk and high-risk genotypes in different age groups was not significantly different (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e)\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHPV infection, high-risk and low-risk HPV genotypes prevalence in different age groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eAge groups\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHPV positivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHPV genotype\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow risk\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh risk\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\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (20.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (79.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" align=\"char\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" align=\"char\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e20\u0026ndash;40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e707 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3554 (83.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e325 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e382 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e706\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e40\u0026ndash;60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1052 (87.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e60\u0026ndash;80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (87.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;\u0026thinsp;80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e879 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4694 (84.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e411 (46.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e468 (53.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong 888 HPV-positive humans, 392 (44.1%), 215 (24.2%), 276 (31.1%), and 5 (0.6%) were infected by single, double, triple and quadruple genotypes, respectively. The peak prevalence was observed in 2015 followed by 2018 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The HPV infection has dramatically decreased from 2022.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe detailed HPV infection rate as well as genotypes during the studied years.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHPV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eTotal samples\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eHPV-Risk out of 888\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eOf 888\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2 (100%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"13\" align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth rowspan=\"13\" align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6 (100%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e11 (100%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e14 (24.6%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e43 (75.4%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e8 (57.1%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6 (42.9%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e14 (100%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e37 (16.7%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e185 (83.3%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e23 (62.2%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e14 (37.8%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e37 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e53 (16.7%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e265 (83.3%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e318\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e39 (73.6%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e14 (26.4%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e53 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e139 (20.7%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e533 (79.3%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e672\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e48 (34.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e91 (65.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e139 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e168 (19%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e716 (81%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e884\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e73 (43.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95 (56.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e168 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e152 (20.4%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e594 (79.6%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e746\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e78 (51.3%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e74 (48.7%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e152 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e101 (20.4%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e394 (79.6%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e495\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e55 (54.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e46 (45.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e101 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e91 (16.6%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e458 (83.4%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e549\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e46 (50.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e45 (49.5%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e91 (100%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2023\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e94 (9.4%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e903 (90.6%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e997\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e34 (36.2%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e60 (63.8%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e94 (100.0%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2024\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e39 (5.7%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e645 (94.3%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e684\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e14 (35.9%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e25 (64.1%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e39 (100.0%)\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\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e888 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4755 (84.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e418 (47.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e470 (52.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e888 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe trend of high and total HPV, as well as low and high-risk genotypes during the studied years, is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, a considerable number of humans (5643 humans) were studied for HPV infection during 12 years, among which, 15.7% were infected by HPV. HPV genotype 6 was the most prevalent, and genotypes 30, 83, and 71 were the least prevalent identified ones. Furthermore, 47.1% of patients were infected by high-risk and 52.9% were infected by low-risk HPV genotypes. The prevalence of both HPV infection and high-risk genotypes was significantly higher in women compared to men. The highest HPV infection was observed in young patients, age under 20 years old. HPV 16 was the most prevalent high-risk genotype followed by HPV 53 and 18.\u003c/p\u003e\n\u003cp\u003eStudies on the prevalence of HPV infection and its genotypes are important regarding designing monitoring programs for the diagnosis of cervical cancer and evaluation of HPV vaccine efficacy in women (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e). In a meta-analysis, the overall prevalence of HPV in Iranian women was estimated as 23%. They reported the highest and the lowest prevalence in Tehran and Isfahan provinces as 97% and 2.2%, respectively (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e). In the present study, in Isfahan, the prevalence of the infection in a large number of people was lower than the average prevalence in Iran.\u003c/p\u003e\n\u003cp\u003eVazifehdoost et al. (2022) (\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e), reported HPV infection in 57.8% of women in Tehran, Iran, which is considerably higher than our results in Isfahan (16.4%). Similarly they reported the highest prevalence of HPV infection in young patients, 25\u0026ndash;34 years-old. Like our results, they reported the predominant genotype as HPV6.\u003c/p\u003e\n\u003cp\u003eFarahmand et al. (2020) (\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e), studied 571 healthy Iranian women with cytology specimens and 113 cervical cancer tissues. They reported HPV infection in 24% of studied women among whom 3.3% were positive for high-risk HPV and 11.6% for low-risk HPV. In the present study, the prevalence of HPV infection in Isfahan was 15.7%, which is lower than the results of Farahmand et al. in Iranian women. Furthermore, contrary to their results, high-risk HPV genotypes were predominant in the present study (7.5% out of 5643). Similarly they reported HPV6 (9.3%) as the most prevalent genotype. Furthermore, they found a 78.8% HPV positivity among patients with cervical cancer, consisting of 43.4% HPV16, 8% HPV18, and 27.4% an unknown genotype.\u003c/p\u003e\n\u003cp\u003eIn 2019 the most prevalent low-risk HPV genotypes referred from different provinces of Iran to Tehran in males and females were reported as HPV-6 (77.7% and 43.3%) and HPV-11 (13.7% and 11.4%). The most prevalent high-risk HPV genotypes were HPV-16 (5.5% and 16.6%) (\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e). Similarly, in the present study, the most prevalent low-risk and high-risk genotypes in HPV-positive patients were HPV6 (56.6%) and 16 (14%) in Isfahan. Contrary to our findings, a high number of HPV infections was observed in 30\u0026ndash;44 years of age (51.8%), peaking between 30 and 32 years (\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e). Our results showed the highest prevalence in patients under 20 years old, followed by the age group 20\u0026ndash;40 years old.\u003c/p\u003e\n\u003cp\u003eJason P Trama et al. (2022) (\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e), studied the result of 23580 patients' HPV testing in Medical Diagnostic Laboratories, LLC (Hamilton, NJ, USA) between August 2020 and August 2021. The high-risk HPV genotypes were reported in 9.8%, with HPV 52 (1.4%), HPV 39 (1.3%), HPV 51 (1.3%), and HPV 16 (1.2%) being the most frequent. Multiple high-risk HPV infection was observed in 1.3% of all patients. High-risk HPV was more prevalent in patients under 25 years old (\u0026lt;\u0026thinsp;21-year-olds, 24.6%, and 21-25-year-olds, 25.4%). Their results were very close to our findings that 418 (7.4%) out of 5643 were high-risk HPVs and the young patients were the most affected age groups.\u003c/p\u003e\n\u003cp\u003eBakhshani et al. (2023) (\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e) studied the HPV infection and the genotypes in Mashhad. They reported HPV infection in 31.8% of women. HPV 31 (3%), HPV 16 (2.5%), HPV 51 (2.2%), HPV 18 (2%), and HPV 66 (1.8%) were the most frequently found high-risk HPV. Moreover, HPV 6 (9.2%), HPV 53 (4.7%), and HPV 42 (2.8%) were the most prevalent low-risk HPV genotypes. In the present study, 15.7% of a large population in Isfahan were HPV-positive, which is considerably lower than their findings in Mashhad. Genotype 6 was the most prevalent 9.1%, and genotypes 30, 83, and 71 were the least prevalent 0.017% identified genotypes in Isfahan.\u003c/p\u003e\n\u003cp\u003eIn a meta-analysis in 2020 (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e), all data from Iran on HPV prevalence and genotypes among women with normal cervical cytology, premalignant lesions, and cervical cancer were analyzed and published. The HPV prevalence in the studied population in Iran was found to be 9% in women with a normal cervix, 55% in atypical squamous cells, and 58% and 69% in women with low and high-grade squamous intraepithelial lesions, respectively. Furthermore, the prevalence was 81% among patients with invasive cervical cancer. HPV 16 was the most reported HPV type, followed by HPV 18 in all studied groups. In the present study, HPV 16 was the most prevalent among high-risk genotypes followed by HPV 53 and 18.\u003c/p\u003e\n\u003cp\u003eThe rate of HPV infection in Isfahan increased to 2015 and then it was steady until 2021 and decreased afterward. The decrease in the prevalence of HPV infection in recent years could be a result of massive health education on HPV and its danger among the general population of Iran by different media thus awareness has increased. This may also show the increase in knowledge and applying preventive measures such as vaccination by the human population in the country.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAccording to the results of the present study, the rate of HPV positivity in Isfahan is close to or in some cases lower than most of other regions in Iran. During the last three years, the HPV infection has decreased dramatically in Isfahan. The prevalence of HPV infection with low- and high-risk genotypes was both higher in women. More than half of HPV infections were caused by high-risk genotypes. Younger ages are the most at-risk group for the infection, and HPV 16 and HPV 6 were the most prevalent high-risk and low-risk HPV genotypes, respectively.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The present study was ethically approved by the ethical committee of the Urmia Branch, Islamic Azad University under the ethical code of IR.IAU.URMIA.REC.1403.012. Data including test results, age, and sex of the patients were obtained from the medical laboratory without their names and reported as frequency and percentage.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical Trial\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe present study was not financially supported.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eB.B. and M.S. Performed the laboratory work. A.H. and S.V. collected the data. R.J. analyzed the data, and edited the manuscript. M.S. and M.V. wrote the main manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank Dr. Forough Sharifi, the supervisor of Dr. Sharifi Medical Laboratory in Isfahan, for her help and contribution.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData would be available from corresponding author in a reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCubie HA. Diseases associated with human papillomavirus infection. Virology. 2013;445(1\u0026ndash;2):21\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarden ME, Munger K. Human papillomavirus molecular biology. Mutat Res Reviews Mutat Res. 2017;772:3\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolf J, Kist LF, Pereira SB, Quessada MA, Petek H, Pille A, et al. Human papillomavirus infection: Epidemiology, biology, host interactions, cancer development, prevention, and therapeutics. Rev Med Virol. 2024;34(3):e2537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrianti P, De Flammineis E, Mercuri SR. Review of HPV-related diseases and cancers. new Microbiol. 2017;40(2):80\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Martel C, Ferlay J, Franceschi S, Vignat J, Bray F, Forman D, et al. Global burden of cancers attributable to infections in 2008: a review and synthetic analysis. Lancet Oncol. 2012;13(6):607\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBernard HU, Burk RD, Chen Z, van Doorslaer K, zur Hausen H, de Villiers EM. Classification of papillomaviruses (PVs) based on 189 PV types and proposal of taxonomic amendments. Virology. 2010;401(1):70\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMu\u0026ntilde;oz N, Castellsagu\u0026eacute; X, Berrington de Gonz\u0026aacute;lez A, Gissmann L. Chapter 1: HPV in the etiology of human cancer. Vaccine. 2006;24(Suppl 3):S31\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Sanjose S, Quint WG, Alemany L, Geraets DT, Klaustermeier JE, Lloveras B, et al. Human papillomavirus genotype attribution in invasive cervical cancer: a retrospective cross-sectional worldwide study. Lancet Oncol. 2010;11(11):1048\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUijterwaal MH, Polman NJ, Van Kemenade FJ, Van Den Haselkamp S, Witte BI, Rijkaart D et al. Five-Year Cervical (Pre)Cancer Risk of Women Screened by HPV and Cytology Testing. Cancer prevention research (Philadelphia, Pa). 2015;8(6):502-8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReynders C, Lerho T, Goebel EA, Crum CP, Vandenput S, Beaudart C, et al. Prevalence and genotype distribution of human papillomavirus in cervical adenocarcinoma (usual type and variants): A systematic review and meta-analysis. J Med Virol. 2023;95(10):e29190.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBakhshani A, Ganjali R, Tabatabaeizadeh SE. Prevalence of Human Papillomavirus (HPV) Genotypes among Women During 2015\u0026ndash;2020 in Mashhad, Iran. Arch Iran Med. 2023;26(8):419\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHojjati M, Reshadati M, Rashidi M, Moghadam AG, Salari N, Abdolmaleki A, et al. The Prevalence of Human Papillomavirus in Iranian Women\u0026rsquo;s: A Comprehensive Systematic Review and Meta-Analysis. Indian J Gynecologic Oncol. 2024;22(1):8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVazifehdoost M, Eskandari F, Sohrabi A. Trends in cocirculation of oncogenic HPV genotypes in single and multiple infections among the unvaccinated community. J Med Virol. 2022;94(7):3376\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarahmand Z, Soleimanjahi H, Garshasbi M, Hasanzadeh M, Zafari E. Distribution of the most common types of HPV in Iranian women with and without cervical cancer. Women Health. 2021;61(1):73\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMobini Kesheh M, Keyvani H. The Prevalence of HPV Genotypes in Iranian Population: An Update. Iran J Pathol. 2019;14(3):197\u0026ndash;205.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrama JP, Trikannad C, Yang JJ, Adelson ME, Mordechai E. High-Risk HPV Genotype Distribution According to Cervical Cytology and Age. Open forum Infect Dis. 2022;9(11):ofac595.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalavatiha Z, Farahmand M, Shoja Z, Jalilvand S. A meta-analysis of human papillomavirus prevalence and types among Iranian women with normal cervical cytology, premalignant lesions, and cervical cancer. J Med Virol. 2021;93(8):4647\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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, Genotype, Iran","lastPublishedDoi":"10.21203/rs.3.rs-5262865/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5262865/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eHuman papillomavirus (HPV) causes the most prevalent sexually transmitted infection. It is the most important cause of cervical cancer. The present study aimed to determine the prevalence of HPV infection and HPV genotypes in the recordings of patients referred to Dr. Sharifi Medical Laboratory in Isfahan, central Iran.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eIn a retrospective study, the HPV PCR and genotyping results of 5643 patients including 4999 (88.6%) females and 644 (11.4%) males from May 2012 to August 2024 were studied. The available demographics, sex and age, were also recorded and analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 5643 studied patient, 888 (15.7%) were HPV-positive. Genotype 6 was the most prevalent (9.1%), and genotypes 30 and 71 were the least prevalent (0.017%) identified genotypes. Out of 888, 470 (47.1%) and 418 (52.9%) were high-risk and low-risk HPV genotypes, respectively. HPV 16 was the most prevalent among high-risk genotypes followed by HPV 53 and 18. The HPV infection was significantly higher in patients under 20 years old and also in females compared to males.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBased on the results of the present study, the rate of HPV infection in Isfahan is close to that of most other regions in Iran. The prevalence of HPV infection with low- and high-risk genotypes was both higher in women. High-risk genotypes caused the majority of infections. Younger ages were the most at-risk group for the infection.\u003c/p\u003e","manuscriptTitle":"A large-scale retrospective study on the prevalence of human papillomavirus and its genotypes in humans referred to a medical laboratory in Isfahan, central Iran","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-18 17:24:44","doi":"10.21203/rs.3.rs-5262865/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":"821af1d1-568e-4f81-a352-e028cc1fd0d2","owner":[],"postedDate":"December 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-10T05:38:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-18 17:24:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5262865","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5262865","identity":"rs-5262865","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}