Fall in Human Papillomavirus Prevalence Following a National Vaccination Program

MAJOR ARTICLE Fall in Human Papillomavirus Prevalence Following a National Vaccination Program Sepehr N. Tabrizi, 1,2,3,4 Julia M. L. Brotherton, 5,8 John M. Kaldor, 9 S. Rachel Skinner, 8 Eleanor Cummins, 4 Bette Liu, 9 Deborah Bateson, 10 Kathleen McNamee, 6,7 Maria Garefalakis, 11 and Suzanne M. Garland 1,2,3,4 1 Regional World Health Organization Human Papillomavirus Laboratory Network, Department of Microbiology and Infectious Diseases, The Royal Women s Hospital, Victoria, Australia; 2 Department of Obstetrics and Gynecology, University of Melbourne, Australia; 3 Department of Microbiology, and 4 Murdoch Children s Research Institute, Royal Children s Hospital, Parkville, Australia; 5 Registries, Victorian Cytology Service, East Melbourne, Australia; 6 Family Planning Victoria, Box Hill, and 7 Department of Obstetrics and Gynecology, Monash University, Clayton, Victoria, Australia; 8 Sydney University Discipline of Pediatrics and Child Health, Children s Hospital Westmead, Australia; 9 The Kirby Institute, University of New South Wales, Darlinghurst; 10 Family Planning New South Wales, Ashfield; and 11 Family Planning Western Australia, Northbridge, Western Australia (See the Editorial Commentary by Hariri and Markowitz, on pages 1633 5.) Background. In April 2007, Australia became the first country to introduce a national government-funded human papillomavirus (HPV) vaccination program. We evaluated the program s impact on genotype-specific HPV infection prevalence through a repeat survey of women attending clinical services. Methods. HPV genoprevalence in women aged 18 24 years attending family planning clinics in the prevaccine period (2005 2007) was compared with prevalence among women of the same age group in the postvaccine period (2010 2011). The same recruitment and testing strategies were utilized for both sets of samples, and comparisons were adjusted for potentially confounding variables. Results. The prevalence of vaccine HPV genotypes (6, 11, 16, and 18) was significantly lower in the postvaccine sample than in the prevaccine sample (6.7% vs 28.7%; P <.001), with lower prevalence observed in both and un women compared with the prevaccine population (5.0% [adjusted odds ratio, 0.11; 95% confidence interval, 0.06 0.21] and 15.8% [adjusted odds ratio, 0.42; 95% confidence interval, 0.19 0.93], respectively). A slightly lower prevalence of nonvaccine oncogenic HPV genotypes was also found in women (30.8% vs 37.6%; adjusted odds ratio, 0.68; 95% confidence interval, 0.46 0.99). Conclusions. Four years after the commencement of the Australian HPV vaccination program, a substantial decrease in vaccine-targeted genotypes is evident and should, in time, translate into reductions in HPV-related lesions. Australia was the first country to implement a national government-funded vaccination program to prevent cervical cancer. From April 2007 through December 2008, a school-based delivery strategy was used to offer free human papillomavirus (HPV) vaccination to girls aged 12 17 years, and from July 2007 through Received 17 April 2012; accepted 15 June 2012; electronically published 19 October 2012. A portion of this data was presented at Preventing Cervical Cancer: Integrating Screening and Vaccination Conference, on 9 11 November 2011 in Melbourne, Australia. Correspondence: Sepehr N. Tabrizi, PhD, Department of Microbiology and Infectious Diseases, The Royal Women s Hospital, Locked Bag 300, Parkville, Victoria 3052, Australia (sepehr.tabrizi@thewomens.org.au). The Journal of Infectious Diseases 2012;206:1645 51 The Author 2012. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. DOI: 10.1093/infdis/jis590 December 2009, general practitioners and other community providers offered free vaccination to women aged 26 years. Since 2009, routine HPV vaccination has continued for girls in the first year of high school (age, 12 13 years) as part of the National Immunization Schedule. During 2007 2009, an estimated 83% of girls aged 12 17 received at least 1 dose of HPV vaccine and 70% completed the 3-dose HPV vaccination course [1]. Among women aged 18 26 years, recorded coverage in this period was 55% and 32% for 1-dose and 3-dose coverage, respectively [2]. This was less than true coverage because notification in this age group to the national vaccine register was not compulsory, although it did attract a small notification payment per dose [2]. The Australian HPV vaccination program has exclusively used the quadrivalent vaccine, which protects against HPV genotypes HPV Prevalence Reduction JID 2012:206 (1 December) 1645

16 and 18 [3], the main causes of high-grade cervical intraepithelial neoplasia (CIN grades 2 and 3) in Australian women, and genotypes 6 and 11, which cause most genital warts [4, 5]. Definitive proof of the program s effectiveness in reducing cervical cancer will not be evident for several decades. However, there have already been early signs of success, manifested as substantially lower numbers of both new genital warts presentations at sexual health clinics [6, 7] and histologically confirmed diagnoses of high-grade cervical lesions [8] among young women in the vaccine cohort, compared with their predecessors at the same age. Another outcome measure that is increasingly being recognized as relevant for HPV vaccine evaluation is the prevalence of infection with vaccine-targeted genotypes. With placebocontrolled trials no longer ethically feasible, genotype prevalence has been endorsed as an appropriate surrogate outcome for comparative trials of new HPV vaccine constructs [9], as well as providing an important basis for population monitoring of vaccine program effectiveness [10 12]. We conducted Australia s first study of HPV genoprevalence, known as WHINURS (Women, Human papillomavirus prevalence, Indigenous, Non-Indigenous, Urban, Rural Study), just prior to the implementation of the national HPV vaccination program. This study involved recruitment of women at 34 sentinel clinical sites from around the country and provided estimates of the prevalence of specific genital HPV genotypes [13]. With 4 years having elapsed since implementation of the vaccination program, we initiated a follow-up survey to assess changes in the prevalence of HPV genotypes in young Australian women. Here we report on the first analysis of findings in women aged 18 24 years at participating clinics in 3 of Australia s major cities. METHODS Study Design and Participants We used a repeat cross-sectional design to compare HPV prevalence in 2 samples of women recruited from sentinel clinical sites. The first or pre vaccine implementation sample was made up of women aged 18 24 years (at the time of recruitment) who were recruited from participating family planning clinics (FPCs) for Papanicolaou screening during the recruitment period of 2005 2007 and had participated in the WHINURS study [13] in Sydney, Melbourne, and Perth, 3 of Australia s 4 largest cities and home to nearly one-half the Australian population. All FPCs in Australia are government funded and provide a wide range of reproductive and sexual health services, including clinical screening, diagnosis and treatment, professional education, and health promotion. Each of Australia s major cities has either 1 or 2 FPC sites that are recognized as attracting a wide range of clients from across the sociodemographic spectrum. The second or post vaccine implementation sample comprised women aged 18 24 years who had attended FPCs in the same cities during the recruitment period 2010 2011 for Papanicolaou screening. These women would have been aged 14 20 years at the time they were, if they participated in the school- or community-based components of the HPV vaccination program between 2007 and 2009. Any impact measured in this age group would most closely approximate the benefit that might be expected for future cohorts of adolescents. Based on vaccine registry data, the recorded HPV vaccine coverage among women aged 18 24 years in 2011 was 74% for 1 dose and 55% for 3 doses [1, 2]. Under Australian guidelines, cervical screening begins at age 18 years or 2 years after first intercourse, whichever is later. Therefore, on the basis of their age, the women in the second sample were in both the cohort and eligible for cervical screening at the time of recruitment. The recruitment for the postvaccine sample is ongoing, and the current study is based on an interim data analysis. Of 2 FPCs in Melbourne, only 1 participated in the prevaccine phase, whereas both joined the postvaccine phase. Participants were recruited from both Perth FPCs in both phases. The Sydney FPC that had participated in the prevaccine phase moved premises soon afterward to a nearby site within the city. Both this site and a second major Sydney FPC participated in the postvaccine phase. All the clinics participating in the prevaccine and postvaccine phases were located within the same metropolitan areas. The procedures to recruit participants were identical for the prevaccine and postvaccine samples. Clinic staff identified ageeligible women at the time of a consultation that included routine Papanicolaou testing. Invitation to participate depended on judgment by the clinician that there was sufficient time to raise the study in the context of the clinical visit. Written, informed consent was obtained from those who agreed to participate. At the time of the Papanicolaou test, each woman had a sample of exfoliated cervical cells collected in Preservcyt (Thin Prep, Cytyc) for HPV DNA testing. Information on age, current use of hormonal contraception, smoking status, and postcode of residence was collected. Those enrolled in the postvaccine group were also asked to provide information relating to HPV vaccination status, sexual and reproductive history, and knowledge of risk factors for cervical cancer. Approval to conduct the study was obtained from research and ethics committees at each of the sites that enrolled participants. Laboratory Testing Identical laboratory methods for HPV genotype detection were used for both the prevaccine and postvaccine groups [13]. Briefly, 1 ml of cervical cells in Preservcyt was pelleted and resuspended in 200 µl of phosphate-buffered saline for 1646 JID 2012:206 (1 December) Tabrizi et al

DNA extraction using the automated MagNA Pure LC isolation and purification system (Roche Molecular Systems) with the DNA-I isolation kit [14]. Following nucleic acid isolation, all samples were initially assessed for the presence of 13 highrisk HPV (HR-HPV) genotypes using the Amplicor HPV test kit (Roche Molecular Systems). Any specimen shown to be negative for HR-HPV types was tested for the presence of mucosal HPV DNA using L1 consensus primer set PGMY09- PGMY11 [15]. Polymerase chain reaction (PCR) products were detected by enzyme-linked immunosorbent assay (ELISA) using a generic biotin-labeled probe for detection of the presence of mucosal HPV sequences in the sample [16]. Samples positive for HPV by either the Amplicor test or the PGMY09-PGMY11 PCR-ELISA were subsequently genotyped using the Linear Array HPV genotyping test (Roche) modified by using an automated blot processor, BeeBlot (Bee Robotics), for the hybridization and washing steps, as previously validated by our laboratory [17 19]. HPV genotyping profiles were manually interpreted and verified using the HPV reference guide provided with each test kit. Any sample positive for the HPV 52/33/35/58 probe line on the Linear Array test was further tested to confirm the presence or absence of HPV type 52 [20]. Statistical Analysis The primary analyses compared women in the prevaccine and postvaccine samples, with the latter being further stratified into 2 groups based on whether or not participants reported having received at least 1 dose of HPV vaccine. Comparisons of sociodemographic characteristics and HPV prevalence were then made across the 3 groups ( prevaccine, postvaccine un, and postvaccine ). It was hypothesized that if the groups had comparable sociodemographic profiles, we would see a lower prevalence of vaccine types in women who had received the vaccine, compared with both the prevaccine women and the postvaccine women who had not received the vaccine. We analyzed HPV prevalence as (1) any HPV genotype; (2) any HR-HPV genotype (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, or 68); (3) any HR-HPV genotype excluding the vaccine genotypes 16 and 18; (4) vaccine-preventable HPV genotypes (6, 11, 16, and 18); and (5) other prespecified groupings of nonvaccine genotypes. Vaccine effectiveness (VE) was calculated by comparing the prevalence of HPV infection between the and un group in the postvaccine sample using the standard formula VE = 1 RR, where RR is the ratio of the prevalences in these 2 postvaccine samples. We also compared the groups of women according to sociodemographic variables including age, socioeconomic status (upper or lower 50th percentile, based on the Socioeconomic Indexes for Areas, a score that ranks Australian residential postcodes according to information from the 2006 Census on indicators including median income, education level, and household numbers) [21], residential area (major city or other, based on the Accessibility/Remoteness Index of Australia [ARIA], classifies residential postcodes into major cities) [22], current use of hormonal contraceptives, and current smoking status. In addition, for postvaccine study participants, we also compared and un women with regard to their reported age at first sexual intercourse (in years), education (higher or lower, based on completion of at least high school or technical college), and whether they were Australian born. To test for differences in proportions or means between the groups of women, χ 2 tests or t tests and analysis of variance were used, respectively. We used logistic regression to adjust comparisons of prevalence by sociodemographic characteristics that were found to vary between the groups of women and report adjusted odds ratios (ORs). Statistical significance was tested at the level of P <.05. All analyses were conducted using Stata software (version 10.1). RESULTS During the prevaccine phase of recruitment, metropolitan FPCs in Sydney, Melbourne, and Perth recruited 202 women aged 18 24 years. During the postvaccine phase, FPCs recruited 404 women aged 18 24 years. In the postvaccine sample, 9 women reported that they did not know whether or not they had received any doses of the HPV vaccine and were excluded from analyses by vaccine status. Women from the prevaccine sample were slightly older than those from the postvaccine sample (mean age, 21.6 vs 21.2 years; P =.005) and less likely to be using hormonal contraceptives at the time of recruitment (60.9% vs 74.2%; P =.001), but other characteristics were similar between groups (Table 1). Of women recruited to the postvaccine sample, 85.6% (n = 338) reported that they had been with at least 1 dose, and of those who recalled the number of doses, 279 (86.4%) of 323 women stated that they received all 3, giving a self-reported 3-dose coverage rate of 70.6%. Within the postvaccine sample, women who stated that they had been were slightly younger than un women (mean age, 21.1 vs 21.8 years; P =.009), had a higher education status (95.0% vs 87.7% completed high school or technical college; P =.03), and were more likely to be born in Australia (88.5% vs 59.7%; P <.001). These 2 groups were similar for other characteristics including their age at first reported sexual intercourse (mean age, 16.5 vs 16.7 years; P =.3), socioeconomic status, use of hormonal contraceptives, and smoking status. Across the 3 categories of women ( prevaccine, postvaccine un, and postvaccine ), the only HPV Prevalence Reduction JID 2012:206 (1 December) 1647

Table 1. Characteristics of Women According to Study and Vaccination Status Characteristic Prevaccine (n = 202) (n = 404) P a Un (n = 57) Vaccinated (n = 338) Age, mean years (SD) 21.6 (1.8) 21.2 (1.8).005 c 21.8 (1.9) 21.1 (1.8).001 c Residing in major city 192 (95.1) 362 (90.9).08 c 49 (87.5) 304 (91.3).1 Higher socioeconomic 159 (78.7) 312 (78.0).8 40 (71.4) 266 (79.4).4 group Hormonal contraceptive use 123 (60.9) 299 (74.2).001 c 36 (63.2) 257 (76.3) <.001 c Current smoker 60 (29.7) 109 (27.6).6 15 (26.8) 90 (27.3).8 Data are no. (%) of women, unless otherwise indicated. Percentages do not include missing values. a P value for difference between prevaccine and postvaccine groups. b P value for difference across 3 groups: prevaccine, postvaccine un, and postvaccine. c P <.05. P b characteristics which differed significantly were age and hormonal contraceptive use (Table 1); we therefore adjusted for these when comparing HPV prevalence across these 3 groups. There were highly significant differences in crude HPV prevalence between the prevaccine and postvaccine samples (Figure 1). The prevalence of any HPV genotype was 59.9% vs 48.0% in the prevaccine and postvaccine groups, respectively (P =.006). For the vaccine-targeted HPV genotypes, the difference was even greater at 28.7% vs 6.7%, respectively (P <.001). When the postvaccine sample was stratified according to self-reported vaccination status, there were highly significant differences across the 3 groups in the proportions of women positive for any type of HPV, HR-HPV types, and HPV vaccine genotypes (Table 2). Vaccinated women consistently had the lowest prevalences of HPV, and the differences were particularly striking for the HPV genotypes covered by the vaccine, with only 5.0% of women in the postvaccine sample having 1 of these genotypes. We also found significant differences between the 3 groups in the prevalence of HPV types 6, 16, and 18 (Table 2) and no significant differences for selected other HR-HPV genotypes. Vaccine effectiveness against vaccine-type HPV infection was 73% (95% confidence interval [CI], 48% 86%; P <.001). After adjusting for age and use of hormonal contraceptives, compared with women in the prevaccine sample, those in the postvaccine sample who reported being were significantly less likely to be positive for any HPV genotype (OR, 0.49; 95% CI, 0.34 0.71), HR-HPV genotypes (OR, 0.48; 95% Figure 1. Differences in human papillomavirus (HPV) genoprevalence between prevaccine and postvaccine populations. *P <.05 for difference in percentages between groups. Abbreviations: CI, confidence interval; excl, excluding; HR-HPV, high-risk HPV. 1648 JID 2012:206 (1 December) Tabrizi et al

Table 2. Prevalence of Human Papillomavirus (HPV) Genotypes According to Study and Vaccination Status HPV Genotype Prevaccine (n = 202) (n = 404) P a Un (n = 57) Vaccinated (n = 338) Any 121 (59.9) 194 (48.0).006 33 (57.9) 157 (46.5).007 High-risk 95 (47.0) 138 (34.2).002 24 (42.1) 111 (32.8).004 High-risk excluding 16 and 18 76 (37.6) 126 (31.2).1 20 (35.1) 104 (30.8).3 Vaccine types 58 (28.7) 27 (6.7) <.001 9 (15.8) 17 (5.0) <.001 16 43 (21.3) 20 (4.9) <.001 6 (10.5) 13 (3.9) <.001 18 17 (8.4) 9 (2.2) <.001 5 (8.8) 4 (1.2) <.001 6 11 (5.5) 2 (0.5) <.001 2 (3.5) 0 (0.0) <.001 11 3 (1.5) 1 (0.3).08 0 (0.0) 1 (0.3).2 31, 33, 35, and 45 21 (10.4) 37 (9.2).6 9 (15.8) 26 (7.7).1 Data are no. (%) of women. a P value for difference between prevaccine and postvaccine groups. b P value for difference across 3 groups: prevaccine, postvaccine un, and postvaccine. P b CI, 0.33 0.70), and vaccine-preventable HPV genotypes (OR, 0.11; 95% CI, 0.06 0.21) (Table 3). There was also a reduction of borderline significance in the prevalence of HR-HPV types excluding 16 and 18 (OR, 0.68; 95% CI, 0.46 0.99). The un postvaccine women were also less likely than the prevaccine women to be positive for the HPV genotypes 6, 11, 16, and 18 (OR, 0.42; 95% CI, 0.19 0.93). These differences in HPV prevalence were not materially affected by additionally adjusting for socioeconomic status, region of residence, and smoking status (Table 3). DISCUSSION Using a repeat cross-sectional design involving sentinel clinical sites, we have shown that a substantial and statistically significant decrease in the prevalence of vaccine-preventable HPV genotype infections has occurred following implementation of Australia s national HPV vaccination program. The decrease was almost entirely restricted to the HPV genotypes that the quadrivalent vaccine is designed to prevent, occurred primarily in women who said that they had received the vaccine, and could not be explained by other differences in the characteristics of the women in the samples being compared. As far as we are aware, this finding is the first genoprevalencebased evidence of the protective effect of HPV vaccination outside the setting of a clinical trial. Our observation follows recent Australian reports of postvaccination decreases in genital warts and high-grade cervical lesions among young women [6, 8]. It is consistent with the high levels of vaccine coverage achieved under the Australian program, combined with the efficacy of the HPV vaccine observed in the prelicensure trials. Table 3. Association Between Human Papillomavirus (HPV) Prevalence, by s of HPV Genotypes, and Study and Vaccination Status Status, OR (95% CI) a OR (95% CI) b HPV positive 0.54 (0.38 0.78) 0.56 (0.39 0.80), not 0.92 (0.50 1.69) 0.97 (0.52 1.80), 0.49 (0.34 0.71) 0.50 (0.34 0.73) High-risk HPV types 0.53 (0.37 0.75) 0.55 (0.38 0.79), not 0.82 (0.45 1.51) 0.88 (0.48 1.64), 0.48 (0.33 0.70) 0.50 (0.34 0.74) High-risk HPV types excluding 16 and 18 0.70 (0.49 1.01) 0.74 (0.51 1.07), not 0.92 (0.49 1.71) 0.97 (0.52 1.84), 0.68 (0.46 0.99) 0.71 (0.48 1.04) Vaccine types (6, 11, 16, and 18) 0.16 (0.09 0.26) 0.16 (0.09 0.26), not 0.42 (0.19 0.93) 0.40 (0.18 0.90), 0.11 (0.06 0.21) 0.11 (0.06 0.21) a Adjusted for age and hormonal contraceptive use. b Adjusted for age, hormonal contraceptive use, region, socioeconomic group, and smoking status. HPV Prevalence Reduction JID 2012:206 (1 December) 1649

The main question arising from our finding is whether the large reduction in the prevalence of HPV vaccine genotypes, observed in samples of women recruited from FPCs in 3 major cities in 3 Australian states, is indicative of an effect in the population of young Australian women as a whole. We have confidence that the finding can be generalized, for several reasons. First, we recruited the prevaccine and postvaccine samples from the same geographic locations and category of service provider, to minimize changes in HPV risk-related characteristics between the 2 periods. Although strict comparability of samples between the 2 periods is a general weakness of nonrandomized comparative studies, we have adjusted for all the available variables in comparing the 2 groups. Clinicians at participating sites were encouraged to recruit age-eligible women having Papanicolaou tests, and we have no evidence that participation was related to any factor that might be associated with HPV prevalence, or that it may have differed between the 2 sample periods. We also found that the decrease in HPV prevalence was maintained after adjusting for differences between the samples in demographic and other characteristics. Finally, although the proportion of women in the postvaccine group who self-reported that they had been was higher than national coverage estimates, there is evidence of underreporting to the national registry that provides these estimates. An ongoing study validating self-reported vaccination status among women in the same age group against notifications held on the register and, where details were available, through follow-up with providers has found 91% of selfreported doses were recorded on the register, 6% were confirmed on follow-up with providers, and 3% were not able to be confirmed on follow-up (Brotherton and Liu, unpublished data). It is likely, therefore, that the self-reported coverage in our sample is slightly higher than the true coverage, but also that women attending for screening may be more regular healthcare attendees and hence more likely to be than the general population of women. Overreporting of vaccination status among the vaccinees would tend to minimize the true effect of vaccination on HPV infection, but HPV status among un women in the sample will still reflect HPV exposure within the community in which they reside. The prevaccine survey [13] did not collect a sexual history from participants, so we could not formally adjust for sexual behavior. However, all participants are highly likely to have been sexually active for at least 2 years, as they were attending clinics for Papanicolaou screening. If there are differences in sexual behavior between the 2 survey periods, they would be expected to be in the direction of increasing levels of sexual activity over time, based on the serial surveys of Australian adolescent females between 2002 and 2008 demonstrating a continuing trend of earlier age of first sexual intercourse and higher numbers of sexual partners [23, 24]. Thus it is unlikely that the drop in HPV prevalence demonstrated in our data is due to a reduction in sexual exposure to infection. In addition, recent data from United States has found that HPV vaccination status does not influence sexual risk behavior in adolescents [25]. This early sign of a major reduction in HPV prevalence, only 4 years after implementation of a national vaccination program, provides further evidence in favor of Australia s substantial national investment in the program. As highly cohorts from the national HPV vaccination school program move into adulthood, this reduction should continue. A reduction in prevalence of HPV genotype infections responsible for 70% of cervical cancers and >50% of high-grade lesions should translate over time in reductions in the rate of cervical abnormalities, with subsequent decreases in treatment episodes, and ultimately reduction in the burden of illness and death due to cervical cancer, as well as other anogenital HPVrelated cancers [8]. Our analyses also suggest the possibility that there has already been a reduction in vaccine-related HPV genotypes among un women living in the Australian community. We are continuing to recruit from participating FPCs, to reach a sample size that will allow us to estimate vaccine effectiveness according to the number of validated vaccine doses received, and examine the extent of any herd immunity with more precision. Notes Acknowledgments. We thank the study s research nurses Jennifer Jolly, Mandy Johnson, and Tracey Rose, who have assisted with recruitment at each of the FPCs in New South Wales, Victoria, and Western Australia, respectively, as well as all of the staff involved in the baseline WHINURS study. Author contribution. S. N. T., J. M. L. B., and J. M. K. contributed to study design, data analysis, data interpretation, and writing of the manuscript. S. R. S. and S. M. G. contributed to study design, data interpretation, and writing of the manuscript. B. L. contributed to data analysis, data interpretation, and writing of the manuscript. D. B., K. M., and M. G. contributed to study design, site enrolment, and writing of the manuscript. E. C. performed laboratory testing and contributed to data analysis and writing of the manuscript. Financial support. This work was supported by Australian National Health and Medical Research Council Project Grant [APP1007685] and Anti- Cancer Council for Victoria Grant in Aid [628754]. John Kaldor and Bette Liu are supported by Fellowships from the National Health and Medical Research Council. Potential conflicts of interest. S. N. T. was an investigator on a national HPV prevalence study that received partial, equal, and unrestricted funding from CSL Biotherapies and GlaxoSmithKline (GSK). J. M. L. B. is an investigator on an Australian Research Council Linkage Grant, for which CSL Biotherapies is a partner organization. J. M. L. B. was also an investigator on a national HPV prevalence study that received partial, equal, and unrestricted funding from CSL Biotherapies and GSK. B. L. owns shares in Commonwealth Serum Laboratories, supplier of HPV vaccine in Australia. S. M. G. has received advisory board fees and grant support from CSL and GSK, and lecture and consultancy fees from Merck. S. M. G. also reports having previously owned stock in CSL. S. G. has received grant support from Merck and GSK to carry out clinical trials 1650 JID 2012:206 (1 December) Tabrizi et al

for HPV/cervical cancer vaccines, and she is a member of the Merck global advisory and scientific advisory boards. S. R. S. is or has been an investigator on several clinical trials evaluating GSK s HPV vaccine, and her institution has received funding to collect data for these studies. S. R. S. s institution has also received honoraria for Advisory Board membership, and reimbursement for attendance at conferences to present clinical trials data from GSK Biologicals; and has received unrestricted research funds from GSK Australia and CSL. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed. References 1. Gertig DM, Brotherton JM, Saville M. Measuring human papillomavirus (HPV) vaccination coverage and the role of the National HPV Vaccination Program Register, Australia. Sex Health 2011; 8:171 78. 2. 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