ABSTRACT
To assess the pattern of multiple human papillomavirus infection to predict the type replacement postvaccination. A total of 7372 women aged 18–45y from a phase III trial of an Escherichia coli-produced HPV-16/18 vaccine were analyzed at enrollment visit before vaccination. Hierarchical multilevel logistic regression was used to evaluate HPV vaccine type and nonvaccine-type interactions with age as a covariate. Binary logistic regression was construed to compare multiple infections with single infections to explore the impact of multiple-type infections on the risk of cervical disease. Multiple HPV infections were observed in 25.2% of HPV-positive women and multiple infections were higher than expected by chance. Statistically significant negative associations were observed between HPV16 and 52, HPV18 and HPV51/52/58, HPV31 and HPV39/51/52/53/54/58, HPV33 and HPV52/58, HPV58 and HPV52, HPV6 and HPV 39/51/52/53/54/56/58. Multiple HPV infections increased the risk of CIN2+ and HSIL+, with the ORs of 2.27(95%CI: 1.41, 3.64) and 2.26 (95%CI: 1.29, 3.95) for multiple oncogenic HPV infection separately. However, no significant evidence for the type-type interactions on risk of CIN2+ or HSIL+. There is possibility of type replacement between several pairs of vaccine and nonvaccine HPV type. Multiple HPV infection increased the risk of cervical disease, but coinfection HPV types seem to follow independent disease processes. Continued post-vaccination surveillance for HPV 51/52/58 types and HPV 39/51 types separately was essential after the first and second generation of HPV vaccination implementation in China.
Introduction
Human papillomavirus (HPV) is a common sexually transmitted virus, and more than 200 HPV genotypes have been identified.Citation1 HPV infection is responsible for 100% of cervical cancers, 88% of anal cancers, 70% of vaginal cancers, 50% of penile cancers, 43% of vulvar cancers, and 13%~72% oropharyngeal cancers.Citation2 The relative contribution of HPV 16/18 or HPV6/11/16/18/31/33/45/52/58 to HPV-associated cancers were 73% and 90%, respectively.Citation3 Prophylactic HPV vaccines had been proven to be highly efficacious against vaccine-type persistent infection and precancerous cervical lesions in large phase III clinical trials.Citation4–6 However, existing HPV vaccines only cover partial important oncogenic types of HPV, including bivalent vaccine for HPV 16/18, quadrivalent vaccine for HPV16/18/6/11, and nonvalent vaccine which targets HPV6/11/16/18/31/33/45/52/58. There are concerns on the possibility of type-replacement by nontargeted oncogenic genotypes triggered by vaccination, which may hinder the success of HPV vaccination companion in reducing morbidity and mortality from diseases associated with HPV infection.Citation7
Currently, there is controversy over the existence of HPV genotype replacement. One meta-analysis analyzing the prevalence of HPV during prevaccination and postvaccination periods found slight increases in two nonvaccine oncogenic types, HPV 39 and HPV 52.Citation8 In other studies, non-vaccine-type HPV prevalence did not change significantly in the post-vaccination era.Citation9–11 The prevalence of coinfection with multiple types of HPV among unvaccinated women ranged from 4.6% to 26%.Citation12–14 Cross-sectional studies on the pattern of multiple HPV infection are essential to evaluate competition between HPV types during natural infection before vaccine introduction, that used the odds ratio (OR) to infer competitive interactions.Citation15,Citation16
HPV type distribution among women with normal cervical cytology, precancerous cervical lesions and cervical cancer varies widely in different regions.Citation17,Citation18 The five most frequent HPV oncogenic types were HPV-52, -16, -58, -33, and -18 among women with normal cervical cytology in China, compared with HPV-16, -52, -53, -31 and -18 in the world.Citation17,Citation18 Five prophylactic HPV vaccines had successively marketed in China since 2016, including three bivalent HPV vaccines, a quadrivalent one and a nonvalent kind. The HPV vaccine has not yet been incorporated into national immunization program in China, but some pilot regions gradually launch free human papillomavirus vaccinations for girls. Evaluation of HPV type-replacement is essential before and after massive vaccine introduction. In this cross-sectional study before vaccine introduction, we aim to assess the pattern of multiple human papillomavirus infection to predict the type replacement postvaccination.
Methods
Study population and design
This study was derived from a phase III trial of an Escherichia coli-produced HPV-16/18 vaccine in adult women (NCT01735006), of which the design and methods had been described elsewhere.Citation6,Citation19 In brief, this phase III trial was a multicenter, randomized, double-blinded, controlled study which enrolled 7372 women age 18–45 y from 5 provinces in China.Citation6 Healthy women age 18–45 year who were sexually active, willing to avoid vaginal douching and vaginal medication for 48 hours before each visit were eligible for this study. Exclusion criteria were pregnancy or lactation at enrollment, any previous HPV vaccination or previous immunological diseases. The current study analyzed the cross-sectional data from all the enrolled women at entry before vaccination.
The study was approved by the Independent Ethics Committees of each center (12-72/606, 2012-48, 2012044, IRB00001594) and conducted in accordance with principles of Good Clinical Practice.
Specimen collection
Cervical cytology specimens from all women were collected in PreservCyt™ solution for ThinPrep® Pap test (Cytyc Corporation, Boxborough, MA, USA). Liquid-based cytology results were reported according to the Bethesda 2001 classification system. Women with abnormal cytology results were referred for colposcopy, with the exception of ASC-US with negative results on the Hybrid capture® 2 (HC2) test. Biopsy was performed according the predefined algorithms as pervious described.Citation6 Histological specimens were evaluated by a blinded independent pathology panel at the Cancer Institute of the Chinese Academy of Medical Sciences (CICAMS).
HPV DNA testing
Cervical cytology and biopsy samples were first tested by HPV DNA enzyme immunoassay method (DEIA) (Labo Biomedical Products, the Netherlands). DEIA positive samples were then genotyped for 13 oncogenic (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 and 68) and 12 non-oncogenic (6, 11, 34, 40, 42, 43, 44, 53, 54, 66, 70 and 74) HPV types using a linear probe assay (LiPA25, Labo Biomedical Products, Netherlands).Citation6,Citation19 Additionally, HPV DNA-positive samples were also tested by HPV types 16 and 18 specific polymerase chain reactions (PCRs) (HPV TS16/18, Labo Biomedical Products, Netherlands). For HPV-16 or HPV-18 testing, a positive for either LiPA or HPV TS16/18 was considered as positive.
Statistical analysis
Firstly, the observed frequency of number of HPV types per woman were compared with the null frequency expected by chance, and observed/expected ratios (O/E) with exact 95% confidence interval (CI) for the counts of multiple infections were calculated according Poisson distribution.Citation16,Citation20
Only HPV type with prevalence of at least 0.5% were included in the type interactions analysis, with 11 oncogenic type (16, 18, 31, 33, 35, 39, 51, 52, 56, 58, 59 and 68) and 6 non-oncogenic type (6, 43, 53, 54, 66 and 74). Hierarchical multilevel logistic regression was used to evaluating HPV vaccine type (HPV16/18 and HPV31/33/52/58/6) and nonvaccine-type interactions with age as a covariate. Two-level model was constructed, allowing adjustment for clustering of HPV infections within women, with woman-level random effects as pervious study described.Citation20 The odds ratio (OR) with 95% CI for each pairwise association was calculated after adjustment for age. Negative associations being considered indicative of competitive interactions, while positive associations indicate synergistic effects between specific HPV types.Citation15,Citation16 Bonferroni-corrected P-value thresholds to assess statistical significance of coinfection patterns were p < .003(0.05/16) for coinfection of each vaccine type.
Binary logistic regression was construed to compare multiple infections with single infections to explore the impact of multiple-type infections on the risk of cervical disease, with histology (cervical intraepithelial neoplasia grade 2 or above, CIN2+) or cytology (high-grade squamous intraepithelial lesions or worse, HSIL+) as the dependent variable. Synergy indices with 95%CI were calculated to explore the type-type additive statistical interactions on risk of CIN2+ or HSIL+.Citation21,Citation22
All statistical analyses were conducted using SAS version 9.4 software (SAS Institute, Cary, North Carolina).
Results
Of 7372 women enrolled in this study, 7367 (99.9%) had satisfied cervical cytology samples with valid HPV typing results included in this analysis. The overall prevalence of the 25 HPV types was 19.4%(1434/7367), among them 25.2% (362/1434) were multiple HPV infections. As shown in , multiple HPV infections were more common among young women aged 18–26 y than older women aged 27–45 y (27.6% vs 22.7%, p = .03). In addition, women with abnormal cervical cytology were more likely to harbor multiple HPV infection than women with normal cervical cytology (31.1% vs 22.7%, p = .002). However, the proportion of multiple infection is lower in women diagnosed with CIN2+ than with CIN1(28.0% vs 15.5%, p = .045). The prevalence of single and multiple infections of each HPV type is shown in , with HPV-52 having the highest prevalence of single (3.0%) and multiple infections (2.0%), followed by HPV16.
Figure 1. Type-specific HPV prevalence in women at enrollment visit before vaccination.
Table 1. Single, multiple HPV infection of women at enrollment visit before vaccination.
The number of HPV type detected in a woman ranged from 0 to 5 infections. Under the assumption that infections are independent following Poisson distribution, the observed frequency of zero infection and two or more infections were higher than expected, whereas the occurrence of singer infection was less than expected (). This indicates that multiple infections were higher than expected by chance.
Table 2. Observed-to-expected ratio (O/E) of multiple infections.
The OR with 95% CI of the pairwise comparisons among HPV coinfections were shown in . Statistically significant negative associations were observed between HPV16 and 52, HPV18 and HPV51/52/58, HPV31 and HPV39/51/52/53/54/58, HPV33 and HPV52/58, HPV58 and HPV52, HPV6 and HPV 39/51/52/53/54/56/58.
Figure 2. The log odds ratio with 95% CI for HPV vaccine type and nonvaccine-type interactions. (a) HPV 16, (b) HPV 18, (c) HPV 31, (d) HPV 33, (e) HPV 52, (f) HPV 58, (g) HPV6.
As shown in , multiple HPV infections increased the risk of CIN2+, the OR was 2.06(95%CI: 1.30, 3.25), 2.27(95%CI: 1.41, 3.64) and 2.04(95%CI: 1.08, 3.86) for multiple any, oncogenic, and a9 species HPV type. Likewise, for HSIL+, multiple infection of any (OR = 2.21, 95%CI: 1.29, 3.78), oncogenic (OR = 2.26, 95%CI: 1.29, 3.95), and a9 species (OR = 3.42, 95%CI: 1.76, 6.66) HPV type were also significantly increased the risk.
Table 3. The risk of cervical disease of multiple HPV infection.
The impact of multiple-type infections on the risk of cervical disease was calculated by synergy indices with 95%CI (). None of the synergy indices was statistically significant, indicating no significant evidence for the type-type interactions on risk of CIN2+ or HSIL+. The risk of CIN2+ and HSIL+ for multiple HPV infection was similar to sum of the risks for each single infection.
Table 4. The impact of multiple-type infections on the risk of cervical disease.
Discussion
This cross-sectional study with large sample size showed that the prevalence of multiple HPV infections is 25.2% in HPV-positive Chinese women aged 18–45 y and multiple infections were higher than expected by chance. Negative interactions were observed between HPV16 and 52, HPV18 and HPV51/52/58, HPV31 and HPV39/51/52/53/54/58, HPV33 and HPV52/58, HPV58 and HPV52, HPV6 and HPV 39/51/52/53/54/56/58, indicating competitive interactions between these types, which warrant further attention. Multiple HPV infection increased the risk of CIN2+ and HSIL+. However, the risk of CIN2+ and HSIL+ for multiple HPV infection was similar to sum of the risks for each single infection, with no evidence for the type-type interactions.
The prevalence of multiple HPV infection in this study was similar to that of a cross-sectional study of women from East Coast of the United States (19.0%),Citation12 while lower than other studies of women in New Mexico (41.1%)Citation14 and the Netherlands (55.2%).Citation13 Multiple infections were more common than expected by chance,Citation12–14 which may be driven by the common route of transmission and risk factors.Citation23 However, negative interactions were observed between HPV16 and 52, HPV18 and HPV51/52/58, HPV31 and HPV39/51/52/53/54/58, HPV33 and HPV52/58, HPV58 and HPV52, HPV6 and HPV 39/51/52/53/54/56/58, suggesting the possibility of type replacement between these paired types. Negative associations were also observed for HPV16-52Citation24 and HPV16-51Citation25 in Chinese and Danish study respectively. While in other studies, multiple positive associations were observed with no statistically significant negative associations.Citation12–14 One meta-analysis found a slight increase in the prevalence of HPV 39 and HPV52 after the introduction of first generation of HPV vaccination in a population.Citation26 Recently a post-hoc analysis of a community randomized clinical up to 9 y post-implementation found an increase of HPV51 and HPV52 occurrence in the core-groups of HPV16/18 vaccinated.Citation27 Gargano et al.Citation28 analyzed population-based cross-sectional data from 2008 to 2016 in the United States and found a significant increase in CIN2+ attributable to non-vaccine types (including 39/45/51/52/58/59) among 25–29 year olds post quadrivalent HPV vaccination. Currently, there is a lack of non-vaccine HPV types trends post vaccination data due to a relatively short period of marketed use of non-valent HPV vaccine. Given the high prevalence of HPV39, HPV51, HPV52 and HPV58 in women in China,Citation19 it is necessary to conduct continued post-vaccination surveillance for HPV 51/52/58 types and HPV 39/51 types separately following the introduction of bivalent/quadrivalent and non-valent HPV vaccination in a population.
Compared with single infection, multiple HPV infections increased the risk of CIN2+ and HSIL+.Citation29 However, the risk of cervical disease for multiple HPV infection was similar to sum of the risks for each single infection, suggesting coinfection HPV types seem to follow independent disease processes.Citation21 In the natural environment, each HPV type appeared to be associated with an independent CIN lesion--one virus, one lesion.Citation30 Therefore, though there is possibility type-replacement after HPV vaccination implementation, the carcinogenicity of non-vaccine targeted HPV genotypes will not be affected.Citation21 In term of public health impact, HPV16/18 were the two most risky oncogenic HPV types,Citation31 while HPV 51/52 were more prevalent in normal cytological status, low-grade squamous intraepithelial lesion or cervical intraepithelial neoplasia grade 1 with low capacity to progress to cervical cancer.Citation19,Citation27 So HPV vaccination is still recommended to protect against the most risky oncogenic HPV vaccine type, and continued post-vaccination surveillance of non-vaccine type is also essential.
This study was subject to several limitations. First, the information on sexual behaviors of participants was not collected, which was not adjusted in type-type interaction assessment. Second, the sample sizes for CIN2+ and HSIL+ were limited, and synergy indices may be affected by low statistical power. Third, the sensitivity for HPV58 by LiPA is relatively low, which may lead to inaccurate analysis of this type.Citation32 In addition, this is a cross-sectional study which cannot distinguish concurrently or sequentially acquired infections.
In conclusion, this large sample cross-sectional study found that multiple infections were higher than expected by chance. There is possibility of type replacement between several pairs of vaccine and nonvaccine HPV types. Multiple HPV infections increased the risk of cervical disease, but coinfection HPV types seem to follow independent disease processes. Continued post-vaccination surveillance for HPV 51/52/58 types and HPV 39/51 types separately are essential after the first and second generation of HPV vaccination implement, and follow-up documents are also needed to inform on the vaccination recommendations in China.
Author contribution
Yingying Su, Youlin Qiao, Ting Wu, Jun Zhang, and Ningshao Xia contributed to the study conception and design. Data collection and analysis were performed by Yingying Su, Tingquan Zheng, Zhaofeng Bi, Xinhua Jia, Yufei Li, Xuefeng Kuang, Yuan Yang, Qi Chen, Hongyan Lin, and Yue Huang. Yingying Su and Ting Wu drafted manuscript. All authors critically reviewed the manuscript and approved the final version. The work reported in the paper has been performed by the authors, unless clearly specified in the text.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data will be available beginning 6 months after the major findings from the final analysis of the study have been published, ending 2 y after. Proposals should be directed to [email protected]. To gain access, data requestors will need to sign a data access agreement.
Additional information
Funding
References
- Burd EM. Human papillomavirus laboratory testing: the changing paradigm. Clin Microbiol Rev. 2016;29(2):291–8. doi:10.1128/CMR.00013-15.
- Giuliano AR, Nyitray AG, Kreimer AR, Pierce Campbell CM, Goodman MT, Sudenga SL, Monsonego J, Franceschi S. EUROGIN 2014 roadmap: differences in human papillomavirus infection natural history, transmission and human papillomavirus-related cancer incidence by gender and anatomic site of infection. Int J Cancer. 2015;136(12):2752–2760. doi:10.1002/ijc.29082.
- de Martel C, Plummer M, Vignat J, Franceschi S. Worldwide burden of cancer attributable to HPV by site, country and HPV type. Int J Cancer. 2017;141(4):664–670. doi:10.1002/ijc.30716.
- Herrero R, Gonzalez P, Markowitz LE. Present status of human papillomavirus vaccine development and implementation. Lancet Oncol. 2015;16(5):e206–e216. doi:10.1016/S1470-2045(14)70481-4.
- World Health Organization. Human papillomavirus vaccines: WHO position paper, May 2017. Wkly Epidemiol Rec. 2017;92(19):241–268.
- Qiao YL, Wu T, Li RC, Hu YM, Wei LH, Li CG, Chen W, Huang S-J, Zhao F-H, Li M-Q, et al. Efficacy, safety, and immunogenicity of an escherichia coli-produced bivalent human papillomavirus vaccine: an interim analysis of a randomized clinical trial. J Natl Cancer Inst. 2020;112(2):145–153. doi:10.1093/jnci/djz074.
- Man I, Vänskä S, Lehtinen M, Bogaards JA. Human papillomavirus genotype replacement: still too early to tell? J Infect Dis. 2021;224(3):481–491. doi:10.1093/infdis/jiaa032.
- Mesher D, Soldan K, Lehtinen M, Beddows S, Brisson M, Brotherton JM, Chow EPF, Cummings T, Drolet M, Fairley CK, et al. Population-level effects of human papillomavirus vaccination programs on infections with nonvaccine genotypes. Emerg Infect Dis. 2016;22(10):1732–1740. doi:10.3201/eid2210.160675.
- Covert C, Ding L, Brown D, Franco EL, Bernstein DI, Kahn JA. Evidence for cross-protection but not type-replacement over the 11 years after human papillomavirus vaccine introduction. Hum Vaccin Immunother. 2019;15(7–8):1962–1969. doi:10.1080/21645515.2018.1564438.
- Saccucci M, Franco EL, Ding L, Bernstein DI, Brown D, Kahn JA. Non-vaccine-type human papillomavirus prevalence after vaccine introduction: no evidence for type replacement but evidence for cross-protection. Sex Transm Dis. 2018;45(4):260–265. doi:10.1097/olq.0000000000000731.
- Carozzi F, Puliti D, Ocello C, Anastasio PS, Moliterni EA, Perinetti E, Serradell L, Burroni E, Confortini M, Mantellini P, et al. Monitoring vaccine and non-vaccine HPV type prevalence in the post-vaccination era in women living in the Basilicata region, Italy. BMC Infect Dis. 2018;18(1):38. doi:10.1186/s12879-018-2945-8.
- Dickson EL, Vogel RI, Bliss RL, Downs LS Jr. Multiple-type human papillomavirus (HPV) infections: a cross-sectional analysis of the prevalence of specific types in 309,000 women referred for HPV testing at the time of cervical cytology. Int J Gynecol Cancer. 2013;23(7):1295–1302. doi:10.1097/IGC.0b013e31829e9fb4.
- Mollers M, Vriend HJ, van der Sande MA, van Bergen JE, King AJ, Lenselink CH, Bekkers RLM, Meijer CJLM, de Melker HE, Bogaards JA, et al. Population- and type-specific clustering of multiple HPV types across diverse risk populations in the Netherlands. Am J Epidemiol. 2014;179(10):1236–1246. doi:10.1093/aje/kwu038.
- Yang Z, Cuzick J, Hunt WC, Wheeler CM. Concurrence of multiple human papillomavirus infections in a large US population-based cohort. Am J Epidemiol. 2014;180(11):1066–1075. doi:10.1093/aje/kwu267.
- Man I, Wallinga J, Bogaards JA. Inferring pathogen type interactions using cross-sectional prevalence data: opportunities and pitfalls for predicting type replacement. Epidemiology. 2018;29(5):666–674. doi:10.1097/EDE.0000000000000870.
- Tota JE, Ramanakumar AV, Jiang M, Dillner J, Walter SD, Kaufman JS, Coutlee F, Villa LL, Franco EL. Epidemiologic approaches to evaluating the potential for human papillomavirus type replacement postvaccination. Am J Epidemiol. 2013;178(4):625–634. doi:10.1093/aje/kwt018.
- Bruni LAG, Serrano B, Mena M, Gómez D, Muñoz J, Bosch FX, de Sanjosé S. Human papillomavirus and related diseases in the world. ICO/IARC information centre on HPV and cancer (HPV information centre). Summary Report; 2019 Jan 22.
- Bruni LAG, Serrano B, Mena M, Gómez D, Muñoz J, Bosch FX, de Sanjosé S. Human papillomavirus and related diseases in China. ICO/IARC information centre on HPV and cancer (HPV information centre). Summary Report; 2018 Dec 10.
- Wei LH, Su YY, Hu YM, Li RC, Chen W, Pan QJ, Zhang X, Zhao F-H, Zhao Y-Q, Li Q, et al. Age distribution of human papillomavirus infection and neutralizing antibodies in healthy Chinese women aged 18–45 years enrolled in a clinical trial. Clin Microbiol Infect. 2020;26(8):1069–1075. doi:10.1016/j.cmi.2019.12.010.
- Vaccarella S, Franceschi S, Snijders PJ, Herrero R, Meijer CJ, Plummer M, IARC HPV Prevalence Surveys Study Group. Concurrent infection with multiple human papillomavirus types: pooled analysis of the IARC HPV prevalence surveys. Cancer Epidemiol Biomarkers Prev. 2010;19(2):503–510. doi:10.1158/1055-9965.EPI-09-0983.
- Chaturvedi AK, Katki HA, Hildesheim A, Rodriguez AC, Quint W, Schiffman M, Van Doorn L-J, Porras C, Wacholder S, Gonzalez P, et al. Human papillomavirus infection with multiple types: pattern of coinfection and risk of cervical disease. J Infect Dis. 2011;203(7):910–920. doi:10.1093/infdis/jiq139.
- Assmann SF, Hosmer DW, Lemeshow S, Mundt KA. Confidence intervals for measures of interaction. Epidemiology. 1996;7(3):286–290. doi:10.1097/00001648-199605000-00012.
- Plummer M, Vaccarella S, Franceschi S. Multiple human papillomavirus infections: the exception or the rule? J Infect Dis. 2011;203(7):891–893. doi:10.1093/infdis/jiq146.
- Nie J, Liu J, Xie H, Sun Z, Zhao J, Chen Q, Liu Y, Huang W, Ruan Q, Wang Y, et al. Multiple human papillomavirus infections and type-competition in women from a clinic attendee population in China. J Med Virol. 2016;88(11):1989–1998. doi:10.1002/jmv.24542.
- Mejlhede N, Pedersen BV, Frisch M, Fomsgaard A. Multiple human papilloma virus types in cervical infections: competition or synergy? Apmis. 2010;118(5):346–352. doi:10.1111/j.1600-0463.2010.2602.x.
- Gray P, Palmroth J, Luostarinen T, Apter D, Dubin G, Garnett G, Eriksson T, Natunen K, Merikukka M, Pimenoff V, et al. Evaluation of HPV type-replacement in unvaccinated and vaccinated adolescent females— post-hoc analysis of a community-randomized clinical trial (II). Int J Cancer. 2018;142(12):2491–2500. doi:10.1002/ijc.31281.
- Gray P, Luostarinen T, Vanska S, Eriksson T, Lagheden C, Man I, Palmroth J, Pimenoff VN, Söderlund‐Strand A, Dillner J, et al. Occurrence of human papillomavirus (HPV) type replacement by sexual risk-taking behaviour group: post-hoc analysis of a community randomized clinical trial up to nine years after vaccination (IV). Int J Cancer. 2019;145:785–796. doi:10.1002/ijc.32189.
- Gargano JW, McClung N, Lewis RM, Park IU, Whitney E, Castilho JL, Pemmaraju M, Niccolai LM, Brackney M, DeBess E, et al. HPV type-specific trends in cervical precancers in the United States, 2008 to 2016. Int J Cancer. 2023;152(2):137–150. doi:10.1002/ijc.34231.
- Trottier H, Mahmud S, Costa MC, Sobrinho JP, Duarte-Franco E, Rohan TE, Ferenczy A, Villa LL, Franco EL, et al. Human papillomavirus infections with multiple types and risk of cervical neoplasia. Cancer Epidemiol Biomarkers Prev. 2006;15(7):1274–1280. doi:10.1158/1055-9965.Epi-06-0129.
- Quint W, Jenkins D, Molijn A, Struijk L, van de Sandt M, Doorbar J, Mols J, Van Hoof C, Hardt K, Struyf F, et al. One virus, one lesion—individual components of CIN lesions contain a specific HPV type. J Pathology. 2012;227(1):62–71. doi:10.1002/path.3970.
- Khan MJ, Castle PE, Lorincz AT, Wacholder S, Sherman M, Scott DR, Rush BB, Glass AG, Schiffman M. The elevated 10-year risk of cervical precancer and cancer in women with human papillomavirus (HPV) type 16 or 18 and the possible utility of type-specific HPV testing in clinical practice. J Natl Cancer Inst. 2005;97(14):1072–1079. doi:10.1093/jnci/dji187.
- Yin J, Peng S, Li X, Zhang C, Hu F, Chen W, Qiao Y. Head-to-head comparison of genotyping of human papillomavirus by GP5+/6±PCR-based reverse dot blot hybridization assay and SPF10-PCR-based line probe assay. J Med Virol. 2023;95(2):e28435. doi:10.1002/jmv.28435.