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Prevention of Human Papillomavirus–Associated Cancers
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Prevention Of Human Papillomavirus-Associated Cancers Joakim Dillner
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Cite this article as: Joakim Dillner, Prevention Of Human Papillomavirus-Associated Cancers, Semin Oncol, http://dx.doi.org/10.1053/j.seminoncol.2014.12.028 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
PREVENTION OF HUMAN PAPILLOMAVIRUS-ASSOCIATED CANCERS
Joakim Dillner1,2
1) International HPV Reference Center, Dept. of Laboratory Medicine and 2) Dept. of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, Sweden ABSTRACT The oncogenic, anogenital types of Human Papillomavirus (HPV) are established as causing about 4,8% of all human cancers worldwide, particularly cervical, anal, vulvar, vaginal, penile and oropharyngeal cancers. Quantitative knowledge of the HPV typespecific risks for these cancers as well as for the different cervical cancer precursors (cervical intraepithelial neoplasias, CIN) useful for estimating the effect of elimination of specific HPV types and clinical benefits of screening for specific HPV types. The present review has summarized both a worldwide systematic review on presence of specific HPV types in cervical cancer precursors and in invasive cervical cancers and also summarizes long-term follow-up data from a large randomized clinical trial of HPVbased cervical cancer screening. All 12 HPV types established to be Class I (established) carcinogens (HPV types 16/18/31/33/35/39/45/51/52/56/58/59) were more common in cervical cancers than among women without cervical lesions. A few rare HPV types were also more common in cervical cancers (namely HPV26, 67, 68, 69, 73 and 82). The follow-up studies found increased long-term risks particularly for HPV types 16/18/31/33 that had 14-year cumulative incidences for CIN3+ above 28%, HPV35/45/52/58 had 14 year risks between 14-18% and HPV39/51/56/59/66/68 had risks <10%. HPV16 contributed to the
greatest proportion of CIN2+ (first round PAR 36%), followed by types 31, 52, 45 and 58 (7%-11%). HPV16/18/31/33/45/52/58 together contributed 73.9% of CIN2+ lesions and all HR types contributed 86.9%. In summary, the different oncogenic HPV types have substantial differences in their oncogenic potential. These differences are relevant for design and evaluation of cervical screening tests and programs as well as for design and evaluation of the effect of vaccination programs using different HPV vaccines.
INTRODUCTION Human papillomaviruses (HPVs) are a large and diverse group of DNA viruses with 198 completely characterized types, with new HPV types being continuously found1-12 (www.hpvcenter.se).
There
are
five
major
HPV
genera:
Alphapapillomavirus,
Betapapillomavirus, Gammapapillomavirus, Mu papillomavirus and Nu papillomavirus, where alphapapillomaviruses infect epithelial cells in genital mucosa. HPV types belonging to different genera have less than 60% similarity, based on the nucleotide sequence of the capsid protein L1. Different viral species within a genus share between 60 and 70 % similarity. A novel HPV type has less than 90% similarity to any other HPV type13. Novel HPV types are given a number only after the whole genome has been cloned and deposited with the International HPV Reference Center1,13, which was established in Heidelberg by Dr. Ethel-Michele deVilliers in 1985 and transferred to the Karolinska Institutet in 2012 (www.hpvcenter.se). HPVs cause a wide range of diseases from benign lesions to invasive tumours14. In 2009, an International Agency for Research on Cancer (IARC) working group classified 12 mucosal HPV types (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58 and 59) as carcinogenic to humans (Group 1)15,16 for their association with cervical cancer. These
12 types cluster together in the same evolutionary branch or "high-risk clade" that includes Alphapapillomavirus species groups 5, 6, 7, 9 and 11. Eleven additional types in the high-risk clade were classified as possibly carcinogenic (Group 2B) based upon their phylogenetic relatedness to Group 1 types, with the exception of HPV68, which was upgraded to “probably carcinogenic” (Group 2A)16. Other mucosal HPV types in the Alphapapillomavirus genus e.g. HPV6 and 11, can cause benign genital condylomas1. There is a large diversity of cutaneous HPV types that have been suggested to be associated with cutaneous malignancies, but as this possible association is not established16, 17 these will not be further discussed in this review. Carcinogenicity of HPV types for cervical cancer & precursors: Meta-analyses Because of the diversity of HPV types, obtaining an exact epidemiologic definition of which individual HPV types are associated with which diseases is difficult. In the field of mucosal HPV types, the use of cross-sectional meta-analyses across different disease grades have long been key to describing HPV type-specific prevalences and establishing the causality of individual HPV types with cervical cancer15,18,19.
A
worldwide meta-analysis has reported the prevalence of all mucosal HPV types across the full spectrum of cervical diagnoses from normal cytology to cancer17. This study was based on 423 studies, including a total of 371,951 eligible women. HPV type-specific prevalences were extracted for 47 mucosal HPV types across eight grades of cervical diagnosis (Table 1). Overall HPV prevalence increased with increasing severity of cervical disease from 12.6% in normal cytology to 89.5% in ICC (Table 1). HPV16 was by far the most frequently detected type in every grade. All 13 HPV types classified as established or probably carcinogenic (Group 1/2A) by IARC were more commonly found among patients with ICC than among subjects with normal cytology (Table 1). Only 3 HPV types (HPV16, HPV18 and 45) were more
prevalent in ICC than in any other grade of cervical diagnosis. Other HR types, however, were more frequently detected in intermediate cervical diagnoses than in ICC. For example, HPV51 was detected in 9.4 and 8.1% of LSIL and CIN1 respectively compared to only in 1% of ICC, HPV52 was detected in 10.1, 14.1 and 9.6% of CIN1, 2 and 3 respectively, compared to 3.2% of ICC, and HPV31 was detected in 10.0 and 10.8% of CIN2 and CIN3 respectively compared to 3.5% of ICC. Some HPV types classified as probably or possibly carcinogenic (Group 2A/2B), namely HPV26, 67, 68, 69, 73 and 82, were also more common in ICC than in normal cytology. Other Group 2B types, for example HPV53 and 66, were more common in normal cytology than ICC and were also found in a higher proportion of low-grade diagnoses (e.g. 8.4 and 7.7% of LSIL respectively) than ICC (0.5 and 0.3% respectively). Among other HPV types, that were relatively uncommon in normal cytology and invasive cancer, many were commonly detected in intermediate diagnoses, in particular the alpha-9 types 61, 62, 84 and 89. The totals of type-specific HPV prevalences were well above above 100% for all diagnoses known to be caused by HPV, highlighting the frequent presence of multiple HPV types within the same women. Indeed, in a subset-analysis of studies providing the necessary data breakdown, the prevalence of multiple infections ranged from 12% in ICC up to 39% in CIN217. It should be noted that the world-wide meta-analysis confirms the WHO/IARC classification of 12 HPV types as carcinogenic to humans for cervical cancer. Some HPV types in the 2A/2B category (namely HPV26, 67, 68, 69, 73 and 82) also appeared to be more common in cervical cancer. Albeit these infections are rare, it is possible that thay may also ultimately be classified as oncogenic and become targets for cancer prevention. In contrast to HPV16, 18 and 45, all other HR HPV types were detected in a
larger proportion of intermediate diagnoses (e.g. HPV31, 52 and 58 each found in >10% of CIN3) than in ICC, highlighting that the relative potential of HR types to cause lowand high-grade abnormalities is not the same as their relative potential to cause ICC.
LONGITUDINAL ESTIMATION OF IMPORTANCE OF DIFFERENT HPV TYPES FOR DEVELOPMENT OF CERVICAL CANCER PRECURSORS While cervical cancer is the third most common female cancer worldwide, with an estimated 530,000 new cases diagnosed in 200820 organized cytological screening programs in Europe have reduced the number of annual cervical malignancy cases on the continent from 68,000 diagnosed in 199521 to 55,000 in 200820. However, cytology has limited sensitivity in detecting the high grade cervical intraepithelial neoplasias (CIN) grade 2 (CIN2) and 3 (CIN3) that are the precursor lesions of cervical cancer22,23. Infection with oncogenic (“high-risk”, HR) types of human papillomavirus (HPV) is a necessary risk factor in cervical carcinogenesis24, implying that screening with HPV testing would be more effective. Several randomised controlled trials (RCTs) have indeed found that screening with HPV DNA testing has higher sensitivity for detection of high-grade CIN23, 25-28. The estimated CIN2+ sensitivity is more than 90% for HPV testing, compared to an average of 55% for cytology23, 25-28. Screening with HPV testing affords better protection against invasive cervical cancer29.Which HPV types to include in HPV screening tests and whether there should be partial or complete or no HPV genotyping when doing cervical screening is therefore an essential question. A better knowledge on the contribution of different specific HPV types to cervical cancer precursor lesions is also of interest when considering the cost-effectiveness of use of different HPV vaccines. Two HPV vaccines containing HPV6/11/16 and 18 or HPV16/18
are also ready on the market30 and second generation HPV vaccines that include a broader range of types are forthcoming, for example a nonavalent vaccine against HPV types 6, 11, 16, 18, 31, 33, 45, 52, 58. However, estimation of the contribution of different HPV types to cervical precursor lesions has been difficult for several reasons. Most low-grade lesions contain multiple HPV types and attribution of the lesion to one or some of the HPV types present can be difficult, unless strong study designs such as longitudinal cohort studies with negligible losses to follow-up are used. Also, when HPV testing is used to identify the lesions, the type composition of the HPV tests used causes a systematic surveillance bias in the estimates. Using long-term follow-up of randomized clinical trials using nationwide and complete registries is therefore an attractive approach to arrive at reliable estimates. The longitudinal approach provides more reliable estimates, but does not have sufficient number of observations to provide estimates on invasive cervical cancer, where the systematic meta-analyses of case series or case-control studies is more informative17. We have performed such longitudinal follow-up using the Swedish nationwide RCT on HPV screening, Swedescreen27, 31-34. In this paper, we summarize the published data on the HPV type-specific risk estimates that are most relevant for medical issues regarding the design and use of HPV tests and HPV vaccines. The population attributable proportion (PAR) combines the infection prevalence with the strength of the association between HPV type and lesion risk. The PAR provides an estimate ofthe proportion of disease that would be eliminted if the infection was prevented in the population, e.g. by vaccination. Under a scenario where vaccination provides a long-lasting protection, the first screening round (prevalent)
PAR would be the best estimate of disease elimination, because the vaccine would also prevent new infection in subsequent screening rounds (Table 2). Overall, infection with any HR type contributed to 52.6% (95% CI: 43.5-60.3) of ASCUS risk in the first screening round, 62.6% (95% CI: 52.2-70.7) of LSIL risk, and 69.2% (95% CI: 53.3-79.7) of CIN1 risk. Type 16 contributed consistently to the greatest proportion of ASCUS, LSIL, and CIN1 risks in the population (ASCUS: 15.5% (95% CI: 9.7-21.9), LSIL: 14.7% (95% CI: 8.0-20.9), and CIN1: 13.4% (95% CI: 3.2-22.5)), followed by type 31 (8.4% (95% CI: 4.2-12.5) for ASCUS to 17.3% (95% CI: 6.8-26.6) for CIN1). The HPV-associated risks for ASCUS/LSIL were strongly time dependent, decreasing for each screening round and essentially disappearing by the 4th round of screening33. This implies that most of the ASCUS/LSIL lesions were caused by new HPV infections. Infection with any HR type caused 89.9% (95% CI: 83.6-93.8) of CIN2+ risk and 94.5% (95% CI: 87.0-97.7) of CIN3+ risk, respectively. HPV type 16 was the most important cause of CIN2+ in the population (35.9% (95% CI: 27.8-43.1)) followed by HPV types 31 (11.0% (95% CI: 5.9-15.8)) and 52 (9.3% (95% CI: 3.5-13.8)). HPV16 was also the most important cause of CIN3+ in the population (46.9% (95% CI: 35.6-56.2)), followed by HPV45 (8.9% (95% CI: 2.5-14.9)) HPV31 (8.8% (95% CI: 2.6-14-5)) and HPV52 (8.8% (95% CI: 2.6-14.5)). Infection with the 4 most important HPV types (HPV16, 18, 31, 33) contributed to 59.6% (95% CI: 50.8-66.8) of CIN2+ and 66.1% (95% CI:54.7-74.7) of CIN3+. Types HPV16/18/31/33/45/52/58 together caused 80.8% (95% CI: 73.3-86.3) of CIN2+ risk and 88.2% (95%CI: 79.3-93.3) of CIN3+ risk in the first screening round, respectively.
The absolute risk (AR) provides the risk that a woman who has tested positive will develop the disease under study during the follow-up time specified. Conversely, the negative predictive value could be obtained by calculating the absolute risk among those that test negative. The cumulative incidence proportion (CIP), calculated using the complement of Kaplan Meier curves, allows for an estimation of the risk of developing the disease in the population while adjusting for censoring and is therefore a more precise risk estimate. Thus, AR or CIP are useful for making clinical predictions, but do not say anything of whether the infection caused the lesion (Table 3). The type-specific absolute risks were higher for ASCUS compared to LSIL except for types 18, 33, 56, 59, and 68. Comparing LSIL to CIN1, the absolute risks were higher for LSIL for all individual types separately and for any HR HPV type. For any HR HPV type, the AR for ASCUS was 18.0% (95% CI: 15.6-20.7), LSIL 15.6% (95% CI: 12.9-18.7) and CIN1 7.2% (95% CI: 5.6-9.2). The 14 year cumulative CIN3+ incidences tended to cluster in 3 distinct groups (Table 4). The four types with highest risks (HPV16, 18, 31 and 33) had 14-year cumulative incidences for CIN3+ above 28%, HPV35, 45, 52, 58 had 14 year risks between 14.0% and 18.3% and HPV39, 51, 56, 59, 66 and 68 had risks from 9.1% to 4.6% and HPV-negative women had as 0.9% risk (Table 3) The incidence rate ratio (IRR) describes how much the risk is increased among women positive for a specific HPV type and the adjusted IRR provides an estimate of how much of this risk increase is actually caused by the type-specific infection after adjusting for other co-infections. For example, if HPV 59 has an AR for ASCUS/LSIL of 10%, but an adjusted IRR of 1.0, this means that we can predict that 10% of HPV 59positive women will develop ASCUS/LSIL but that actually none of these lesions are
caused by HPV59 but rather by other risk-increasing factors associated with HPV 59 (it is merely acting as a marker for risk of disease, not as a cause) (Table 4). The adjusted IRR was highest for type 31 for all the low-grade outcomes (ASCUS: 4.8 (95% CI: 3.3-6.9), LSIL: 7.3 (95% CI: 4.8-11.3), and CIN1 9.0 (95% CI: 5.4-15.0). Comparison of the 14-year Cumulative Incidences (Table 3) with the 14-year adjusted IRRs found mostly similar results, with the different HPV types clustering in 3 different risk groups (Table 4). There were 2 notable exceptions: HPV33 had considerably lower adjusted IRR than what would have been expected from the high cumulative incidence and HPV39 had considerably higher adjusted IRR than what would have been expected from the low cumulative incidence (Table 4). Our study cannot distinguish between the possibilities that these may be chance fluctuations or may reflect biological phenomena. It should be noted that several supposedly “high risk” HPV types (HPV types 51, 56, 59, 66 and 68) had adjusted IRRs that were not significantly different from unity (Table 4) implying that their etiological contribution to high grade cervical cancer precursors is minimal.
Implications for cervical screening programs Screening with better specificity and lower risk for side effects Testing HPV-negative has a protective effect of longer duration than cervical cytology (about twice as long, for both CIN335 and invasive cervical cancer29), screening intervals can therefore be lengthened for HPV-negative women. In most populations >90% of women are HPV-negative and the lengthened intervals for the majority of women implies that much fewer tests and much fewer gynecological investigations need to be performed using HPV-based screening. The cumulative CIN3+ incidence is higher with HPV testing, when evaluated longitudinally36, meaning that HPV-based screening with
extended screening intervals has better specificity and lower risk for overtreatment and side effects than does cytology-based screening. Decreased use of resources Under most scenarios of increased screening interval, HPV test price and HPV prevalence, primary HPV screening is more cost-effective than primary screening with cytology37. Whether the better test should be used to increase the protective effectiveness of the screening program or should be used to save resources is a health policy decision. Triaging of HPV-positive women The evidence base that has demonstrated increased effectiveness has used cytology to triage HPV-positive women29, 38. Algorithms for referral to gynecological investigation/colposcopy are then exactly the same as those used in cytology-based screening programs, thus avoiding the need to develop new clinical algorithms. Most trials have triaged HPV-positive, cytology-negative women with a new HPV-test at least 1 year later. However, recent evidence found that there is no additional protective effect achieved by triaging HPV-positive, cytology-negative women until 3 years after the baseline test29. Although a large number of different triaging algorithms have been suggested, when invasive cancer is used as the endpoint, the only triaging algorithm that is evidence based is that HPV-positive, cytology-negative women should have a repeat test 3 years later. As this is the same interval as used in old cytology-based screening programs, the same systems for organized screening with 3-yearly intervals can be applied to HPV-positive, cytology-negative women. Organizational aspects
There are logistical challenges to implement HPV-based screening, such as the need to ensure that HPV tests are used only at increased screening intervals and in the correct age groups. This is best managed in organized, invitational screening programs38. There is a need to cope with the variety of different HPV tests that are on the market. A formal survey found no less than 34 different commercially available HPV tests39. Again, an organized screening program would easily manage this situation by issuing formal tenders for purchasing of a single HPV test to be used by the program, There has been limited international standardization and quality assurance. Indeed, consecutive annual issuing of global proficiency panels initiated by the WHO LabNet have documented that there is a global improvement in the performance of HPV genotyping services over time40-42. Continued issuing of such proficiency panels will be essential to ensure quality of HPV screening services. The need and logistical challenge to optimize and evaluate the method switch in the real-life setting has not been extensively discussed. All organization and evaluation of screening programs need population-based screening registries. The approach for a reliable real-life evaluation, namely randomized healthcare policies, has only recently been formalized43. Design of HPV screening tests, in terms of HPV types to be included Most HPV screening tests include testing for HPV66. This HPV type 66 was originally classified as oncogenic b the WHO/IARC (International Agency for Research on Cancer), but has since been re-evaluated to not be oncogenic16. This is also in line with the longitudinal data presented in this review33, 34. The inclusion of HPV66 in HPV screening tests thus adds nothing to the performance of the test, but does lower the specificity of the test.
The genotyping data presented in this review finds that HPV16, 18 and 45 have a greater risk for invasive cervical cancer17 and that HPV16, 18, 31 and 33 are the four HPV types with highest risk for CIN334. Several HPV tests that perform a partial HPV typing to also type for HPV16/18 are on the market and several algorithms that use this typing information have been proposed.
Implications for HPV vaccination programs
Two licensed HPV vaccines—the bivalent vaccine comprising HPV types 16 and 18, and the quadrivalent vaccine comprising HPV types 6, 11, 16 and 18— have proven to be safe and efficacious against 6-month-persistent cervical infections of HPV16 and HPV18 and associated precancerous lesions, and both have efficacies of 90–100%30. The major structural HPV protein self-assembles into immunogenic virus-like particles and both vaccines are based on this principle. Because of the ease of making effective HPV vaccines by simply adding more virus-like particles from more HPV types to the vaccines, the composition of second generation vaccines that contain more HPV types is of interest.
Initially, HPV vaccine trials and indications for vaccination focused on prevention of clinical diseases caused by HPV (e.g., cervical cancer, cervical cancer precursors, condylomas, anal cancer, anal cancer precursors and precursors of vulvar, vaginal and penile cancers). However, with the finding that the vaccines are extremely efficacious prophylactic vaccines for prevention of HPV infections as such, the focus has shifted to establishing exactly how much disease is caused by infection with the different HPV types30.
The WHO/International Agency for Research on Cancer has a formal approach for systematically evaluating whether the available evidence from epidemiological studies and mechanistic studies allow concluding that an environmental exposure is carcinogenic to man or not. As mentioned before, HPV types HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58 and 59 are classified as established carcinogens (Class I carcinogens) for humans in the case of cervical cancer16. For anal cancer, vulvar cancer, vaginal cancer, penile cancer, oropharyngeal cancer, tonsillar cancer and oral cavity cancer only HPV type 16 is classified as established Class I carcinogen to man16. Although some of the other HPV types are sometimes also found in non-cervical tumors, they are not sufficiently common and there is not sufficient evidence to conclude that any other type than HPV16 can cause cancers outside of the cervix. Still, the total sum of human cancers that is attributable to HPV is considerable. A formal assessment by the IARC has concluded that prevention of oncogenic HPVs would prevent globally every year the following number of cases of cancer: cervical: 530,000; vulvar: 12,000; anal: 24,000; penile: 11,000; vaginal: 9,000 and oropharyngeal: 22,000 (Total sum: 608,000 preventable cases of cancer every year)44. This estimation has taken into account that the proportion of cancers attributable to HPV is different for the different cancer sites (Cervical: 100%; vulvar:43%; anal: 88%; penile: 50%; vaginal: 70% and oropharyngeal: 26%)44. It should be noted that the disease burden is quite different in different countries, particularly depending on whether effective organized screening programs exist and depending on sexual practices and spread of HPV in the population. For example, in the Western world, the non-cervical cancers constitute a much larger proportion of the total preventable number of cancer cases caused by HPV. The Catalan Institute of Oncology has assembled a website where the exact burden of HPV-
associated cancers has been estimated for every country in the world (www.hpvcentre.net). The data in Table 2 in this paper allows an estimation of how much of the different cervical cancer precursors that would be preventable by different HPV vaccines. This information strongly affects the evaluation of the cost-effectiveness of different vaccination programs. With the highly effective HPV vaccines available, most programs are shifting from merely having disease control as an aim to having elimination of infection with the major oncogenic HPV types as a goal. The numbers in Table 2 give the estimated proportion of precursor lesions that are expected to disappear if infection with a particular HPV types can be eliminated. Dynamic transmission models predict that such elimination will not be very difficult, but is likely to require both-sex vaccination programs45.
Conclusion The role of different HPV types as major human carcinogens is today well established and formally quantified by the WHO/IARC. This information has been exploited to design better cervical cancer screening tests and effective prophylactic HPV vaccines, thus providing us with new methods for cancer prevention. As the global burden of cancers is expected to rise dramatically in the future, good examples on how research can find new ways to prevent cancers are needed46. The HPV field has indeed provided a highly successful example of this.
Acknowledgement Supported by the Swedish Cancer Society and the Swedish Research Council. In the field of screening, JD declares no conflict of interest. In the field of HPV vaccines, JD
has received grants to his institution for research on HPV vaccines from Merck/SPMSD, a manufacturer of HPV vaccines.
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30. Lehtinen, M., Dillner, J. Clinical trials of human papillomavirus vaccines and beyond. Nature Reviews Clinical Oncology. 2013;10:400-410. 31. Naucler P, Ryd W, Törnberg S, Strand A, Wadell G, Hansson BG, Rylander E, Dillner J. HPV type-specific risks of high-grade CIN during 4 years of follow-up: a population-based prospective study. Br J Cancer. 2007b Jul 2;97(1):129-32. 32. Elfstrom KM, Smelov V, Johansson AL, Eklund C, Naucler P, Arnheim-Dahlstrom L, Dillner J. Long term duration of protective effect for HPV negative women: follow-up of primary HPV screening randomised controlled trial. BMJ 2014a;348: g130. 33. Elfström KM, Smelov V, Johansson AL, Eklund C, Naucler P, Arnheim-Dahlström L, Dillner J. Long-term HPV type-specific risks for ASCUS and LSIL: A 14-year follow-up of a randomized primary HPV screening trial. Int J Cancer. 2014b May 20. doi: 10.1002/ijc.28984. 34. Smelov V, Elfström KM; Johansson ALV, Eklund C, Naucler P, Arnheim-Dahlström L, and Dillner J. Long-term HPV type-specific risks for high-grade cervical intraepithelial lesions: A 14-year follow-up of a randomized primary HPV screening trial. Int J Cancer. 2014 Jul 19. doi: 10.1002/ijc.29085. 35. Dillner J, Rebolj M, Birembaut P, Petry KU, Szarewski A, Munk C, de Sanjose S, Naucler P, Lloveras B, Kjaer S, Cuzick J, van Ballegooijen M, Clavel C, Iftner T; Joint European Cohort Study. Long term predictive values of cytology and human papillomavirus testing in cervical cancer screening: joint European cohort study. BMJ. 2008 Oct 13;337:a1754. 36. Katki HA, Kinney WK, Fetterman B, Lorey T, Poitras NE, Cheung L, Demuth F, Schiffman M, Wacholder S, Castle PE. Cervical cancer risk for women undergoing concurrent testing for human papillomavirus and cervical cytology: a population-based study in routine clinical practice.
Lancet Oncol. 2011 Jul;12(7):663-72. 37. de Kok, I.M., van Rosmalen, J., Dillner, J., Arbyn, M., Sasieni, P., Iftner, T., van Ballegooijen, M. Primary screening for human papillomavirus compared with cytology screening for cervical cancer in European settings: cost effectiveness analysis based on a Dutch microsimulation model. British Medical Journal. 344:e670. 2012. 38. Dillner, J. Primary human papillomavirus testing in organized cervical screening. Current Opinion in Obstetrics and Gynecology. 2013;25:11-16. 39. Poljak, M., Cuzick, J., Kocjan, B.J., Iftner, T., Dillner, J., Arbyn, M. Nucleic acid tests for the detection of alpha Human Papillomaviruses. Vaccine. 2012;S5: F100-106. 40. Eklund C, Zhou T, Dillner J; WHO Human Papillomavirus Laboratory Network. Global proficiency study of human papillomavirus genotyping. J Clin Microbiol. 2010 Nov;48(11):4147-55. 41. Eklund C, Forslund O, Wallin KL, Zhou T, Dillner J; WHO Human Papillomavirus Laboratory Network. The 2010 global proficiency study of human papillomavirus genotyping in vaccinology. J Clin Microbiol. 2012 Jul;50(7):2289-98. 42. Eklund, C., Forslund, O., Wallin, K.L., Dillner, J. Global improvement in genotyping of Human Papillomavirus DNA: The 2011 HPV LabNet International Proficiency Study. Journal of Clinical Microbiology. 2014;52:449-459. 43. Hakama, M., Malila, N., Dillner, J. Randomised healthservice studies. Int J Cancer. 2012;131: 2898-2902. 44. de Martel C, Ferlay J, Franceschi S, Vignat J, Bray F, Forman D, Plummer M. Global burden of cancers attributable to infections in 2008: a review and synthetic analysis. Lancet Oncol. 2012 Jun;13(6):607-15. 45. Baussano, I., Dillner, J., Lazzarato, F., Ronco, G., Franceschi, S. Upscaling human papillomavirus vaccination in high-income countries: impact assessment based on
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Table 1. Type-specific prevalence of mucosal HPV DNA, by grade of cervical diagnosis. World-wide meta-analysis, adapted from17. Abbreviations: ASCUS: atypical squamous cells of undetermined significance; LSIL: low-grade squamous intraepithelial neoplasia; HSIL: high-grade squamous intraepithelial neoplasia; CIN: cervical intraepithelial neoplasia; ICC: invasive cervical cancer. ASCU LSIL HSIL CIN1 CIN2 CIN3 IAR Normal S HP C N N N N N N V classi N % % % % % % % Te Te Te Te Te Te type ficati Tes po po po po po po po ste ste ste ste ste ste on s s s s s s s ted d d d d d d 10 11 13 19 263 12 52 75 77 85 74 48 85 92 45 03 67 17 Any 971 .6 .1 .2 27 .3 .2 09 .4 .4 8 6 0 9 13 19 10 11 HP 263 2. 19 77 40 19 48 53 1 17 12 45 03 34 67 V16 971 6 .5 27 .5 .2 09 .8 8 6 0 9 13 19 11 HP 263 4. 6. 77 8. 98 47 8. 6. 1 1 16 44 7 58 V18 702 7 3 11 2 83 35 7 9 1 7 3 11 14 10 HP 243 0. 2. 3. 59 3. 85 43 4. 3. 1 59 95 3 03 V45 656 6 9 3 01 9 27 44 3 4 1 7 0 12 18 11 HP 254 0. 4. 74 7. 91 3. 46 7. 8. 1 21 3 61 12 V33 120 6 9 31 1 76 7 17 1 5 8 7 1 11 15 10 HP 247 0. 3. 5. 61 6. 87 7. 44 10 8. 1 79 05 32 V58 990 8 9 5 08 9 62 1 20 .3 4 0 2 2 HP 1 252 1 12 4. 18 7. 72 9. 91 6. 47 10 11 10
ICC N Te ste d 41 10 1 41 10 1 41 16 4 33 99 7 37 70 0 35 53 9 36
% po s 89 .5 * 55 .8 * 14 .3 * 4. 8* 4. 0* 4. 0* 3.
V31
392
19 1 10 28 8 10 18 1 10 30 6
7
9
93
4
93
8
54
25 4 10 39 9 10 22 1
.8
6. 5
52 68
8. 6
85 10 46 .1
44 14 86 .1
3. 8
54 65
5
87 63
2. 8
44 29
4. 3
5. 5
50 03
3. 8
82 14
4. 9
42 06
4. 7
97 30
3. 1
4. 3
52 70
2. 7
81 28
3. 7
41 18
4
97 67
2. 1
9. 4
54 10
6
83 20
8. 1
42 30
8. 4
98 33
5. 1
7
51 19
3. 1
83 27
5. 6
42 61
3. 7
10 04 4
2. 3
2. 2
47 01
1. 8
83 15
2. 3
39 88
2. 5
79 56
1. 9
HP V52
1
239 298
1
HP V35
1
237 554
0. 4
HP V39
1
235 758
0. 6
HP V59
1
235 145
0. 4
HP V51
1
235 223
0. 9
HP V56
1
241 829
0. 6
HP V68
2A
231 085
0. 4
95 93
1. 8
HP V53
2B
138 289
1. 1
84 09
5. 4
95 02
8. 4
44 04
4
74 45
6. 4
37 14
4. 5
86 44
3. 1
HP V73
2B
116 913
0. 3
72 16
1. 9
84 52
2. 7
37 82
2. 5
49 54
2. 3
31 84
2. 1
59 23
1. 8
HP V6
144 585
0. 8
5. 9
52 40
2. 7
63 54
6
37 10
3
87 62
1. 7
HP V11
144 039
0. 5
2. 9
51 86
0. 9
62 05
2. 5
35 47
1. 4
83 60
0. 8
HP V62
657 61
1. 0
10 30 9 10 27 8 60 92
4. 1
27 98
3. 3
32 64
6. 1
24 04
4. 1
57 11
2. 3
HP V54
128 177
0. 6
99 98 10 49 0 10 54 1
5. 4
54 6 13 01 6 14 56 6 12 72 3 12 69 1 12 68 1 12 94 9 11 64 7
3 4. 2 3. 1 4. 8 3. 5
9. 6 3. 3
4. 4
12 94 5 12 73 8 57 19
79 14
2. 4
85 70
2. 9
36 36
2. 7
61 52
2. 6
28 73
3. 2
69 45
2
3. 1 1. 6
HP V66
2B
204 436
0. 6
94 46
4
11 60 2
7. 7
47 88
3. 5
76 42
5. 9
38 71
4. 6
93 17
2. 4
HP V67
2B
839 10
0. 2
62 42
1. 2
59 75
1. 8
24 61
1. 1
33 04
1. 9
24 72
1. 5
60 14
0. 7
106 816 107 818
0. 5 0. 1
72 73 70 43
2. 8 0. 5
73 65 71 34
3. 1 0. 4
30 86 32 26
3. 2 0. 5
38 95 49 97
3. 3 0. 6
27 39 28 22
59 64 66 92
1. 8 0. 5
HP V84 HP V26
2B
3 1. 1
76 9 34 93 9 33 69 0 32 27 7 33 27 7 32 33 3 32 38 3 29 47 1 28 86 4 25 84 8 32 07 4 31 12 6 64 90 12 17 4 30 95 9 20 66 1 81 11 26 45
5* 3. 2* 1. 6* 1. 3* 1. 2* 1. 0* 0. 8* 0. 5* 0. 5 0. 5* 0. 4 0. 4 0. 4 0. 3 0. 3 0. 3* 0. 3 0. 2*
HP V30
2B
265 59
0. 1
62 0
0. 5
16 03
0. 3
47 7
0
81 1
0. 6
24 4
0. 4
40 8
0. 5
HP V69
2B
767 97
0. 1
52 10
0. 2
58 88
0. 3
23 36
0. 3
33 20
0. 3
22 19
0. 4
56 15
0. 4
HP V70
2B
117 590
0. 8
65 96
2. 4
75 87
2. 3
33 48
2. 1
58 19
1. 5
29 94
1. 7
74 80
1. 1
100 495
0. 6
67 85
2. 3
68 84
2. 8
30 26
1. 8
34 10
2. 9
23 19
3. 1
59 18
1. 1
HP V81 HP V82
2B
132 350
0. 1
67 83
1. 2
82 53
1. 8
38 86
2
50 38
1. 5
33 16
1. 8
74 63
1. 7
HP V34 /64
2B
672 41
0. 1
53 77
0. 3
64 62
0. 3
25 92
0. 2
38 69
0. 2
20 90
0
56 82
0. 1
HP V42
127 999
0. 5
72 35
4. 3
83 88
4. 8
40 24
1. 6
59 66
3. 3
29 38
2. 4
71 62
1. 2
HP V44
103 820
0. 4
22 67
0. 1
33 99
0. 3
21 94
0. 3
39 97
1. 2
20 34
0. 9
55 00
0. 4
HP V55
860 33
0. 3
68 60
1. 2
61 84
2. 2
28 89
1. 8
32 10
1. 4
18 25
1. 4
50 74
1. 2
HP V61
100 536
0. 6
62 43
3. 5
65 61
3. 8
30 13
3. 5
43 99
2. 7
26 11
2. 9
63 22
2. 2
HP V71 HP V72 HP V83 HP V89 HP V90
889 89 944 06 111 587 705 78 249 01
0. 4 0. 3 0. 4 0. 4 0. 6
57 14 60 46 68 43 45 63 32 2
0. 7 0. 7 2. 1
1. 9
51 89 61 33 73 77 51 61 10 78
0. 4 0. 8 1. 9 3. 4 1. 9
24 21 26 40 30 89 24 00 28 7
35 24 31 98 40 92 30 92 47 9
0. 3 0. 5 2. 2 5. 2 0. 8
23 47 22 04 23 60 18 25 13 2
0. 4 0. 5 1. 4 3. 1 0. 8
58 05 57 45 56 96 52 42 23 0
0. 4 0. 6 1. 5 2. 3 0. 9
HP V32
568 02
0. 1
26 75
0. 3
24 15
0. 1
10 66
0. 3 0. 8 1. 8 2. 9 0. 7 < 0. 1
89 4
0. 1
89 5
0. 6
23 14
0. 1
HP V40
915 96
0. 2
73 28
0. 9
79 40
1. 6
36 85
0. 6
54 00
0. 8
26 22
1
63 83
0. 4
HP V43
897 87
0. 3
21 98
0. 5
34 98
0. 3
21 60
0. 1
21 82
0. 4
82 2
0. 2
40 44
0. 1
HP V57
641 70
< 0.
35 26
0. 1
44 48
< 0.
18 48
< 0.
13 31
< 0.
58 9
< 0.
38 54
0. 1
3
9 13 0. 76 2* 3 17 0. 92 2* 9 27 0. 80 2 2 90 0. 48 2 28 0. 10 2* 5 22 0. 23 1 3 22 0. 66 1 7 21 0. 16 1 2 79 0. 13 1 20 0. 87 1 4 83 0. 89 1 91 0. 73 1 95 0. 25 1 85 0. 65 1 18 0. 53 1 < 36 0. 40 1 11 < 22 0. 4 1 < 95 0. 35 1 67 < 64 0.
1 HP V74
1
1
1
1
606 97
0. 5
47 62
0. 2
37 20
0. 6
12 88
0. 8
13 02
0. 5
68 5
0. 7
35 40
0. 1
48 82
301 97
0. 2
16 95
0. 4
10 36
0. 4
56 1
0. 5
11 34
0. 2
10 18
0. 3
10 53
0. 2
25 49
HP V86
152 99
0. 1
25 4
0. 4
56 2
0. 4
22 0
< 0. 1
47 9
< 0. 1
13 2
18 4
< 0. 1
18 01
HP V87
598 7
0. 1
18 9
0. 5
10 32
0. 2
26 0
0. 4
47 8
0. 4
12 9
22 2
0. 5
96 3
HP V91
540 3
0. 2
88 2
3. 6
10 69
4. 2
35 5
3. 1
60 3
2. 5
27 2
28 1
2. 5
11 70 6
HP V85
Tota l
2B
13 18 18 18 6. 9. 5. 3. 6 1 0 4 * = higher prevalence in ICC than in normal cytology 28 .3
< 0. 1 < 0. 1 2. 6 21 0. 2
18 2. 9
1 < 0. 1 < 0. 1 < 0. 1 < 0. 1 < 0. 1 11 3. 6
Table 2. 1st Screening Round Population Attributable Proportion (PAR) (% with (95% confidence interval of the proportion) for different oncogenic HPV types. Follow-up up to 14 years of the Swedish nationwide randomized HPV screening trial of 12527 women. Adapted from33, 34.
HR HPV negative HPV 16 HPV 18 HPV 31 HPV 33 HPV 35 HPV 39 HPV 45 HPV 51 HPV 52 HPV 56
CIN2+
CIN3+
-46.9 (35.6-56.2) 7.1 (1.6-12.4) 8.8 (2.6-14.5) 3.2 (0.0-7.2) 1.8 (0.0-4.5) 0.8 (0.0-2.7) 8.9 (2.5-14.9) 2.7 (0.0-6.3) 8.8 (2.6-14.6) 1.3
-35.9 (27.8-43.1) 6.6 (2.6-10.5) 10.9 (5.8-15.8) 5.5 (1.6-9.2) 0.9 (0.0-2.4) 2.1 (0.0-4.4) 7.2 (2.7-11.4) 2.3 (0.0-4.9) 9.3 (4.5-13.8) 2.2
ASCUS
LSIL
CIN1
-15.5 (9.721.0) 4.2 (1.17.2) 8.5 (4.312.6) 3.1 (0.35.8) 1.8 (0.03.7) 1.7 (0.03.7) 5.9 (2.39.5) 3.8 (0.86.7) 6.3 (2.510.0) 0.8 (0.0-
-14.7 (8.020.9) 6.7 (2.311.0) 11.5 (6.016.8) 3.4 (0.16.5) 1.8 (0.04.1) 2.5 (0.05.1) 4.4 (0.58.1) 3.0 (0.06.1) 4.0 (0.37.6) 4.2 (0.7-
-13.4 (3.222.5) 7.3 (0.014.0) 17.3 (6.826.6) 3.9 (0.09.2) 3.0 (0.07.5) 1.3 (0.04.4) 6.8 (0.013.5) 5.2 (0.011.3) 8.6 (0.716.0) 4.4 (0.0-
HPV 58
(0.0-3.9) 5.3 (0.05-9.9)
HPV 59
--
HPV 66
--
HPV 68
--
(0.0-4.7) 5.2 (1.7-8.7) 0.1 (0.0-0.5) 0.3 (0.0-1.4) 0.3 (0.0-1.2)
2.3) 2.0 (0.04.2) -0.7 (0.02.2)
-19.9 54.0 42.9 (13.3HPV 16/18 (42.5-63.2) (34.4-50.3) 25.7) 32.6 66.1 59.6 (24.9HPV 16/18/31/33 (54.7-74.7) (50.8-66.8) 39.5) 33.9 88.2 80.8 (20.9HPV16/18/31/33/45/52/58* (79.3-93.3) (73.3-86.2) 44.8) 52.4 94.5 89.9 (43.1Any HR type (87.1-97.7) (83.7-93.8) 60.2) *For the low-grade lesions (ASCUS, LSIL and CIN1), the estimates for HPV16/18/31/33/45/52/58 also include HPV6/11.
7.7) 5.1 (1.38.8) 0.6 (0.02.1) -1.1 (0.83.0) 21.5 (13.828.6) 36.2 (26.944.3) 43.4 (28.855.0) 62.5 (52.170.7)
9.7) 2.1 (0.06.3) 1.1 (0.04.1) 0.6 (0.03.2) -21.2 (8.931.9) 43.7 (28.455.7) 43.9 (20.060.7) 69.1 (53.279.6)
Table 3. The cumulative incidence proportions to develop cervical lesions on an on average 11 years followup after testing HPV-positive for different HR-HPV types. % with (95% confidence interval). Follow-up up to 14 years of the Swedish nationwide randomized HPV screening trial of 12527 women. Adapted from33, 34. HPV type
HR HPV negative
HPV 16
HPV 18
HPV 31
HPV 33
HPV 35
HPV 39
HPV 45
HPV 51
CIN2+
1.9 (1.5-2.5)
42.8 (36.4-49.8)
39.4 (28.4-52.8)
41.9 (31.1-54.6)
54.2 (37.6-72.5)
15.6 (6.1-36.9)
17.6 (8.3-35.1)
24.1 (17.2-33.1)
10.5 (5.6-19.2)
HPV 52
27.7 (20.3-37.0)
HPV 56
13.8 (7.4-25.0)
HPV 58
HPV 59
HPV 66 HPV 68
32.1 (20.4-48.2)
8.1 (2.7-23.2)
16.0 (8.1-30.3) 12.1 (3.1-41.5)
CIN3+ ASCUS 0.9 (0.61.3) 34.5 (28.441.5) 29.7 (19.643.4) 28.4 (18.242.7) 34.1 (19.255.6) 15.6 (6.136.9) 9.1 (3.025.8) 16.0 (10.424.2) 7.0 (3.214.9) 14.0 (8.821.8) 4.6 (1.513.6) 18.3 (9.633.3) 5.6 (1.420.5) 5.9 (1.917.2) 7.1
LSIL
CIN1
7.9 (7.0–9.0)
2.8 (2.3–3.4)
2.0 (1.5–2.6)
19.2 (14.7– 24.7)
17.0 (12.8– 22.3)
7.1 (4.3–11.6)
16.8 (9.9– 27.6)
23.2 (14.4– 36.2)
7.1 (3.0–16.2)
27.3 (20.0– 36.6)
25.1 (15.5– 39.2)
14.6(9.3– 22.4)
21.4 (11.7– 37.3)
32.6 (19.3– 51.5)
14.2 (5.3– 27.3)
17.4 (7.6– 36.9)
13.8 (5.4–32.7)
6.9 (1.8–24.9)
11.4 (4.5– 27.6)
11.5 (4.5–27.9)
2.9 (0.4–18.6)
19.2 (12.7– 28.6)
11.8 (7.0–19.5)
6.2 (3.0–12.6)
14.2 (7.9– 25.0)
9.5 (4.8–18.0)
4.7 (1.8–12.1)
24.7 (17.3– 34.6)
14.9 (9.4–23.3)
13.6 (7.9– 22.8)
9.9 (4.5–20.9)
11.6 (6.0–21.9)
5.8 (2.2–14.7)
21.0 (11.5– 36.5)
20.3 (11.1– 35.3)
4.6 (1.2–17.0)
2.8 (0.4–18.1)
10.5 (4.1–25.6)
2.6 (0.4–16.8)
18.2 (10.2– 31.3)
11.8 (5.4–24.7)
5.9 (1.9–17.7)
10.1 (2.6–
17.1 (5.6–45.5)
–
HPV 16/18
HPV 16/18/31/33
Any HR type
(1.040.9) 32.7 (27.441.5 (36.0-47.6) 38.8) 31.7 (26.542.2 (36.8-48.0) 37.7) 20.7 (17.629.9 (26.5-33.5) 24.2)
34.7) 18.7 (14.8– 23.6)
17.7 (13.9– 22.5)
7.2 (4.7–11.1)
21.0 (17.5– 25.1)
20.6 (16.2– 25.9)
9.1 (6.7–12.3)
18.0 (15.6– 20.7)
15.6 (12.9– 18.7)
7.2 (5.6–9.2)
Table 4. The adjusted incidence rate ratio (IRR) to develop cervical lesions on an on average 11 years followup after testing HPV-positive for different HR-HPV types. % with (95% confidence interval). Follow-up up to 14 years of the Swedish nationwide randomized HPV screening trial of 12527 women. Adjusted for follow-up time (1-year intervals), age at entry, study arm, and individual HPV type data. Adapted from33, 34.
HPV type HR HPV negative
CIN2+ Reference
HPV 16
13.1 (10.3-16.7)
HPV 18
7.4 (4.8-11.4)**
HPV 31
11.0 (7.9-15.3)
HPV 33
4.5 (2.7-7.4)**
HPV 35
3.2 (1.2-8.9)**
HPV 39
7.2 (3.2-16.3)
HPV 45
4.6 (3.0-7.0)**
HPV 51
1.8 (0.9-3.6)**
HPV 52
6.4 (4.4-9.4)**
HPV 56
3.4 (1.7-6.5)**
HPV 58
7.0 (4.0-12.2)
HPV 59
1.7 (0.5-5.3)**
HPV 66
1.0 (0.5-2.1)**
HPV 68
1.7 (0.4-6.9)**
HPV 16/18
15.5 (12.3-19.4)
HPV 16/18/31/33
23.1 (18.8-28.5)
Any HR type **
30.7 (24.6-38.1)
CIN3+ Reference 19.5 (14.625.9) 9.4 (5.715.5)** 9.6 (6.314.8)** 2.4 (1.24.7)** 6.8 (2.518.7)** 6.2 (2.019.6) 4.6 (2.77.8)** 2.0 (0.84.6)** 4.9 (2.98.2)** 1.7 (0.65.4)** 4.2 (1.99.0)** 1.8 (0.57.4)** 0.6 (0.22.0)** 1.3 (0.29.5)** 22.9 (17.430.3) 32.3 (24.742.4) 42.0 (30.957.1)
ASCUS Reference
LSIL Reference
CIN1 Reference
3.2 (2.3–4.2) 4.6 (3.3–6.4) 2.9 (1.7–4.8) 2.6 (1.4–4.6) 5.4 (3.1–9.3) 3.2 (1.2–8.2) 4.8 (3.3–6.9) 2.6 (1.3–5.2)
7.3 (4.8– 11.3) 6.4 (3.4– 11.9)
2.7 (1.1–6.6) 3.4 (1.2–9.5) 2.1 (0.8–5.7)
4.9 (1.8– 13.2)
9.0 (5.4– 15.0)** 4.7 (1.9– 12.0) 3.2 (0.7– 13.5) 1.5 (0.2– 10.6)
3.1 (2.0–4.9) 2.9 (1.6–5.0) 2.9 (1.3–6.3) 2.3 (1.3–4.3) 2.4 (1.1–4.9) 1.9 (0.6–5.5) 3.6 (2.4–5.4) 3.5 (2.1–5.8)
5.8 (3.2– 10.4)
1.4 (0.6–3.0) 3.5 (1.7–7.2) 3.1 (1.2–8.5) 3.8 (1.9–7.3) 0.3 (0.0– 2.4)** 1.8 (0.9–3.4) 1.1 (0.3–4.4)
7.3 (3.7– 14.4)
1.9 (0.4–7.9)
2.1 (0.7–5.7) 1.1 (0.2–8.0) 1.3 (0.5– 3.0)** 3.4 (1.1– 11.0)
1.2 (0.4–4.0)
3.2 (2.5–4.2) 5.5 (4.1–7.4) 3.2 (2.0–5.2) 4.3 (3.5–5.4) 7.7 (6.0–9.9) 5.8 (4.0–8.2) 4.3 (3.6–5.2)
8.5 (6.8– 10.6)
Type-specific IRR that was significantly different from HPV 16 IRR, p < 0.05
6.1 (4.5–8.3)
Prevention Of Human Papillomavirus-Associated Cancers Joakim Dillner
www.elsevier.de/endend
PII: DOI: Reference:
S0093-7754(14)00299-1 http://dx.doi.org/10.1053/j.seminoncol.2014.12.028 YSONC51798
To appear in:
Semin Oncol
Cite this article as: Joakim Dillner, Prevention Of Human Papillomavirus-Associated Cancers, Semin Oncol, http://dx.doi.org/10.1053/j.seminoncol.2014.12.028 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
PREVENTION OF HUMAN PAPILLOMAVIRUS-ASSOCIATED CANCERS
Joakim Dillner1,2
1) International HPV Reference Center, Dept. of Laboratory Medicine and 2) Dept. of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, Sweden ABSTRACT The oncogenic, anogenital types of Human Papillomavirus (HPV) are established as causing about 4,8% of all human cancers worldwide, particularly cervical, anal, vulvar, vaginal, penile and oropharyngeal cancers. Quantitative knowledge of the HPV typespecific risks for these cancers as well as for the different cervical cancer precursors (cervical intraepithelial neoplasias, CIN) useful for estimating the effect of elimination of specific HPV types and clinical benefits of screening for specific HPV types. The present review has summarized both a worldwide systematic review on presence of specific HPV types in cervical cancer precursors and in invasive cervical cancers and also summarizes long-term follow-up data from a large randomized clinical trial of HPVbased cervical cancer screening. All 12 HPV types established to be Class I (established) carcinogens (HPV types 16/18/31/33/35/39/45/51/52/56/58/59) were more common in cervical cancers than among women without cervical lesions. A few rare HPV types were also more common in cervical cancers (namely HPV26, 67, 68, 69, 73 and 82). The follow-up studies found increased long-term risks particularly for HPV types 16/18/31/33 that had 14-year cumulative incidences for CIN3+ above 28%, HPV35/45/52/58 had 14 year risks between 14-18% and HPV39/51/56/59/66/68 had risks <10%. HPV16 contributed to the
greatest proportion of CIN2+ (first round PAR 36%), followed by types 31, 52, 45 and 58 (7%-11%). HPV16/18/31/33/45/52/58 together contributed 73.9% of CIN2+ lesions and all HR types contributed 86.9%. In summary, the different oncogenic HPV types have substantial differences in their oncogenic potential. These differences are relevant for design and evaluation of cervical screening tests and programs as well as for design and evaluation of the effect of vaccination programs using different HPV vaccines.
INTRODUCTION Human papillomaviruses (HPVs) are a large and diverse group of DNA viruses with 198 completely characterized types, with new HPV types being continuously found1-12 (www.hpvcenter.se).
There
are
five
major
HPV
genera:
Alphapapillomavirus,
Betapapillomavirus, Gammapapillomavirus, Mu papillomavirus and Nu papillomavirus, where alphapapillomaviruses infect epithelial cells in genital mucosa. HPV types belonging to different genera have less than 60% similarity, based on the nucleotide sequence of the capsid protein L1. Different viral species within a genus share between 60 and 70 % similarity. A novel HPV type has less than 90% similarity to any other HPV type13. Novel HPV types are given a number only after the whole genome has been cloned and deposited with the International HPV Reference Center1,13, which was established in Heidelberg by Dr. Ethel-Michele deVilliers in 1985 and transferred to the Karolinska Institutet in 2012 (www.hpvcenter.se). HPVs cause a wide range of diseases from benign lesions to invasive tumours14. In 2009, an International Agency for Research on Cancer (IARC) working group classified 12 mucosal HPV types (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58 and 59) as carcinogenic to humans (Group 1)15,16 for their association with cervical cancer. These
12 types cluster together in the same evolutionary branch or "high-risk clade" that includes Alphapapillomavirus species groups 5, 6, 7, 9 and 11. Eleven additional types in the high-risk clade were classified as possibly carcinogenic (Group 2B) based upon their phylogenetic relatedness to Group 1 types, with the exception of HPV68, which was upgraded to “probably carcinogenic” (Group 2A)16. Other mucosal HPV types in the Alphapapillomavirus genus e.g. HPV6 and 11, can cause benign genital condylomas1. There is a large diversity of cutaneous HPV types that have been suggested to be associated with cutaneous malignancies, but as this possible association is not established16, 17 these will not be further discussed in this review. Carcinogenicity of HPV types for cervical cancer & precursors: Meta-analyses Because of the diversity of HPV types, obtaining an exact epidemiologic definition of which individual HPV types are associated with which diseases is difficult. In the field of mucosal HPV types, the use of cross-sectional meta-analyses across different disease grades have long been key to describing HPV type-specific prevalences and establishing the causality of individual HPV types with cervical cancer15,18,19.
A
worldwide meta-analysis has reported the prevalence of all mucosal HPV types across the full spectrum of cervical diagnoses from normal cytology to cancer17. This study was based on 423 studies, including a total of 371,951 eligible women. HPV type-specific prevalences were extracted for 47 mucosal HPV types across eight grades of cervical diagnosis (Table 1). Overall HPV prevalence increased with increasing severity of cervical disease from 12.6% in normal cytology to 89.5% in ICC (Table 1). HPV16 was by far the most frequently detected type in every grade. All 13 HPV types classified as established or probably carcinogenic (Group 1/2A) by IARC were more commonly found among patients with ICC than among subjects with normal cytology (Table 1). Only 3 HPV types (HPV16, HPV18 and 45) were more
prevalent in ICC than in any other grade of cervical diagnosis. Other HR types, however, were more frequently detected in intermediate cervical diagnoses than in ICC. For example, HPV51 was detected in 9.4 and 8.1% of LSIL and CIN1 respectively compared to only in 1% of ICC, HPV52 was detected in 10.1, 14.1 and 9.6% of CIN1, 2 and 3 respectively, compared to 3.2% of ICC, and HPV31 was detected in 10.0 and 10.8% of CIN2 and CIN3 respectively compared to 3.5% of ICC. Some HPV types classified as probably or possibly carcinogenic (Group 2A/2B), namely HPV26, 67, 68, 69, 73 and 82, were also more common in ICC than in normal cytology. Other Group 2B types, for example HPV53 and 66, were more common in normal cytology than ICC and were also found in a higher proportion of low-grade diagnoses (e.g. 8.4 and 7.7% of LSIL respectively) than ICC (0.5 and 0.3% respectively). Among other HPV types, that were relatively uncommon in normal cytology and invasive cancer, many were commonly detected in intermediate diagnoses, in particular the alpha-9 types 61, 62, 84 and 89. The totals of type-specific HPV prevalences were well above above 100% for all diagnoses known to be caused by HPV, highlighting the frequent presence of multiple HPV types within the same women. Indeed, in a subset-analysis of studies providing the necessary data breakdown, the prevalence of multiple infections ranged from 12% in ICC up to 39% in CIN217. It should be noted that the world-wide meta-analysis confirms the WHO/IARC classification of 12 HPV types as carcinogenic to humans for cervical cancer. Some HPV types in the 2A/2B category (namely HPV26, 67, 68, 69, 73 and 82) also appeared to be more common in cervical cancer. Albeit these infections are rare, it is possible that thay may also ultimately be classified as oncogenic and become targets for cancer prevention. In contrast to HPV16, 18 and 45, all other HR HPV types were detected in a
larger proportion of intermediate diagnoses (e.g. HPV31, 52 and 58 each found in >10% of CIN3) than in ICC, highlighting that the relative potential of HR types to cause lowand high-grade abnormalities is not the same as their relative potential to cause ICC.
LONGITUDINAL ESTIMATION OF IMPORTANCE OF DIFFERENT HPV TYPES FOR DEVELOPMENT OF CERVICAL CANCER PRECURSORS While cervical cancer is the third most common female cancer worldwide, with an estimated 530,000 new cases diagnosed in 200820 organized cytological screening programs in Europe have reduced the number of annual cervical malignancy cases on the continent from 68,000 diagnosed in 199521 to 55,000 in 200820. However, cytology has limited sensitivity in detecting the high grade cervical intraepithelial neoplasias (CIN) grade 2 (CIN2) and 3 (CIN3) that are the precursor lesions of cervical cancer22,23. Infection with oncogenic (“high-risk”, HR) types of human papillomavirus (HPV) is a necessary risk factor in cervical carcinogenesis24, implying that screening with HPV testing would be more effective. Several randomised controlled trials (RCTs) have indeed found that screening with HPV DNA testing has higher sensitivity for detection of high-grade CIN23, 25-28. The estimated CIN2+ sensitivity is more than 90% for HPV testing, compared to an average of 55% for cytology23, 25-28. Screening with HPV testing affords better protection against invasive cervical cancer29.Which HPV types to include in HPV screening tests and whether there should be partial or complete or no HPV genotyping when doing cervical screening is therefore an essential question. A better knowledge on the contribution of different specific HPV types to cervical cancer precursor lesions is also of interest when considering the cost-effectiveness of use of different HPV vaccines. Two HPV vaccines containing HPV6/11/16 and 18 or HPV16/18
are also ready on the market30 and second generation HPV vaccines that include a broader range of types are forthcoming, for example a nonavalent vaccine against HPV types 6, 11, 16, 18, 31, 33, 45, 52, 58. However, estimation of the contribution of different HPV types to cervical precursor lesions has been difficult for several reasons. Most low-grade lesions contain multiple HPV types and attribution of the lesion to one or some of the HPV types present can be difficult, unless strong study designs such as longitudinal cohort studies with negligible losses to follow-up are used. Also, when HPV testing is used to identify the lesions, the type composition of the HPV tests used causes a systematic surveillance bias in the estimates. Using long-term follow-up of randomized clinical trials using nationwide and complete registries is therefore an attractive approach to arrive at reliable estimates. The longitudinal approach provides more reliable estimates, but does not have sufficient number of observations to provide estimates on invasive cervical cancer, where the systematic meta-analyses of case series or case-control studies is more informative17. We have performed such longitudinal follow-up using the Swedish nationwide RCT on HPV screening, Swedescreen27, 31-34. In this paper, we summarize the published data on the HPV type-specific risk estimates that are most relevant for medical issues regarding the design and use of HPV tests and HPV vaccines. The population attributable proportion (PAR) combines the infection prevalence with the strength of the association between HPV type and lesion risk. The PAR provides an estimate ofthe proportion of disease that would be eliminted if the infection was prevented in the population, e.g. by vaccination. Under a scenario where vaccination provides a long-lasting protection, the first screening round (prevalent)
PAR would be the best estimate of disease elimination, because the vaccine would also prevent new infection in subsequent screening rounds (Table 2). Overall, infection with any HR type contributed to 52.6% (95% CI: 43.5-60.3) of ASCUS risk in the first screening round, 62.6% (95% CI: 52.2-70.7) of LSIL risk, and 69.2% (95% CI: 53.3-79.7) of CIN1 risk. Type 16 contributed consistently to the greatest proportion of ASCUS, LSIL, and CIN1 risks in the population (ASCUS: 15.5% (95% CI: 9.7-21.9), LSIL: 14.7% (95% CI: 8.0-20.9), and CIN1: 13.4% (95% CI: 3.2-22.5)), followed by type 31 (8.4% (95% CI: 4.2-12.5) for ASCUS to 17.3% (95% CI: 6.8-26.6) for CIN1). The HPV-associated risks for ASCUS/LSIL were strongly time dependent, decreasing for each screening round and essentially disappearing by the 4th round of screening33. This implies that most of the ASCUS/LSIL lesions were caused by new HPV infections. Infection with any HR type caused 89.9% (95% CI: 83.6-93.8) of CIN2+ risk and 94.5% (95% CI: 87.0-97.7) of CIN3+ risk, respectively. HPV type 16 was the most important cause of CIN2+ in the population (35.9% (95% CI: 27.8-43.1)) followed by HPV types 31 (11.0% (95% CI: 5.9-15.8)) and 52 (9.3% (95% CI: 3.5-13.8)). HPV16 was also the most important cause of CIN3+ in the population (46.9% (95% CI: 35.6-56.2)), followed by HPV45 (8.9% (95% CI: 2.5-14.9)) HPV31 (8.8% (95% CI: 2.6-14-5)) and HPV52 (8.8% (95% CI: 2.6-14.5)). Infection with the 4 most important HPV types (HPV16, 18, 31, 33) contributed to 59.6% (95% CI: 50.8-66.8) of CIN2+ and 66.1% (95% CI:54.7-74.7) of CIN3+. Types HPV16/18/31/33/45/52/58 together caused 80.8% (95% CI: 73.3-86.3) of CIN2+ risk and 88.2% (95%CI: 79.3-93.3) of CIN3+ risk in the first screening round, respectively.
The absolute risk (AR) provides the risk that a woman who has tested positive will develop the disease under study during the follow-up time specified. Conversely, the negative predictive value could be obtained by calculating the absolute risk among those that test negative. The cumulative incidence proportion (CIP), calculated using the complement of Kaplan Meier curves, allows for an estimation of the risk of developing the disease in the population while adjusting for censoring and is therefore a more precise risk estimate. Thus, AR or CIP are useful for making clinical predictions, but do not say anything of whether the infection caused the lesion (Table 3). The type-specific absolute risks were higher for ASCUS compared to LSIL except for types 18, 33, 56, 59, and 68. Comparing LSIL to CIN1, the absolute risks were higher for LSIL for all individual types separately and for any HR HPV type. For any HR HPV type, the AR for ASCUS was 18.0% (95% CI: 15.6-20.7), LSIL 15.6% (95% CI: 12.9-18.7) and CIN1 7.2% (95% CI: 5.6-9.2). The 14 year cumulative CIN3+ incidences tended to cluster in 3 distinct groups (Table 4). The four types with highest risks (HPV16, 18, 31 and 33) had 14-year cumulative incidences for CIN3+ above 28%, HPV35, 45, 52, 58 had 14 year risks between 14.0% and 18.3% and HPV39, 51, 56, 59, 66 and 68 had risks from 9.1% to 4.6% and HPV-negative women had as 0.9% risk (Table 3) The incidence rate ratio (IRR) describes how much the risk is increased among women positive for a specific HPV type and the adjusted IRR provides an estimate of how much of this risk increase is actually caused by the type-specific infection after adjusting for other co-infections. For example, if HPV 59 has an AR for ASCUS/LSIL of 10%, but an adjusted IRR of 1.0, this means that we can predict that 10% of HPV 59positive women will develop ASCUS/LSIL but that actually none of these lesions are
caused by HPV59 but rather by other risk-increasing factors associated with HPV 59 (it is merely acting as a marker for risk of disease, not as a cause) (Table 4). The adjusted IRR was highest for type 31 for all the low-grade outcomes (ASCUS: 4.8 (95% CI: 3.3-6.9), LSIL: 7.3 (95% CI: 4.8-11.3), and CIN1 9.0 (95% CI: 5.4-15.0). Comparison of the 14-year Cumulative Incidences (Table 3) with the 14-year adjusted IRRs found mostly similar results, with the different HPV types clustering in 3 different risk groups (Table 4). There were 2 notable exceptions: HPV33 had considerably lower adjusted IRR than what would have been expected from the high cumulative incidence and HPV39 had considerably higher adjusted IRR than what would have been expected from the low cumulative incidence (Table 4). Our study cannot distinguish between the possibilities that these may be chance fluctuations or may reflect biological phenomena. It should be noted that several supposedly “high risk” HPV types (HPV types 51, 56, 59, 66 and 68) had adjusted IRRs that were not significantly different from unity (Table 4) implying that their etiological contribution to high grade cervical cancer precursors is minimal.
Implications for cervical screening programs Screening with better specificity and lower risk for side effects Testing HPV-negative has a protective effect of longer duration than cervical cytology (about twice as long, for both CIN335 and invasive cervical cancer29), screening intervals can therefore be lengthened for HPV-negative women. In most populations >90% of women are HPV-negative and the lengthened intervals for the majority of women implies that much fewer tests and much fewer gynecological investigations need to be performed using HPV-based screening. The cumulative CIN3+ incidence is higher with HPV testing, when evaluated longitudinally36, meaning that HPV-based screening with
extended screening intervals has better specificity and lower risk for overtreatment and side effects than does cytology-based screening. Decreased use of resources Under most scenarios of increased screening interval, HPV test price and HPV prevalence, primary HPV screening is more cost-effective than primary screening with cytology37. Whether the better test should be used to increase the protective effectiveness of the screening program or should be used to save resources is a health policy decision. Triaging of HPV-positive women The evidence base that has demonstrated increased effectiveness has used cytology to triage HPV-positive women29, 38. Algorithms for referral to gynecological investigation/colposcopy are then exactly the same as those used in cytology-based screening programs, thus avoiding the need to develop new clinical algorithms. Most trials have triaged HPV-positive, cytology-negative women with a new HPV-test at least 1 year later. However, recent evidence found that there is no additional protective effect achieved by triaging HPV-positive, cytology-negative women until 3 years after the baseline test29. Although a large number of different triaging algorithms have been suggested, when invasive cancer is used as the endpoint, the only triaging algorithm that is evidence based is that HPV-positive, cytology-negative women should have a repeat test 3 years later. As this is the same interval as used in old cytology-based screening programs, the same systems for organized screening with 3-yearly intervals can be applied to HPV-positive, cytology-negative women. Organizational aspects
There are logistical challenges to implement HPV-based screening, such as the need to ensure that HPV tests are used only at increased screening intervals and in the correct age groups. This is best managed in organized, invitational screening programs38. There is a need to cope with the variety of different HPV tests that are on the market. A formal survey found no less than 34 different commercially available HPV tests39. Again, an organized screening program would easily manage this situation by issuing formal tenders for purchasing of a single HPV test to be used by the program, There has been limited international standardization and quality assurance. Indeed, consecutive annual issuing of global proficiency panels initiated by the WHO LabNet have documented that there is a global improvement in the performance of HPV genotyping services over time40-42. Continued issuing of such proficiency panels will be essential to ensure quality of HPV screening services. The need and logistical challenge to optimize and evaluate the method switch in the real-life setting has not been extensively discussed. All organization and evaluation of screening programs need population-based screening registries. The approach for a reliable real-life evaluation, namely randomized healthcare policies, has only recently been formalized43. Design of HPV screening tests, in terms of HPV types to be included Most HPV screening tests include testing for HPV66. This HPV type 66 was originally classified as oncogenic b the WHO/IARC (International Agency for Research on Cancer), but has since been re-evaluated to not be oncogenic16. This is also in line with the longitudinal data presented in this review33, 34. The inclusion of HPV66 in HPV screening tests thus adds nothing to the performance of the test, but does lower the specificity of the test.
The genotyping data presented in this review finds that HPV16, 18 and 45 have a greater risk for invasive cervical cancer17 and that HPV16, 18, 31 and 33 are the four HPV types with highest risk for CIN334. Several HPV tests that perform a partial HPV typing to also type for HPV16/18 are on the market and several algorithms that use this typing information have been proposed.
Implications for HPV vaccination programs
Two licensed HPV vaccines—the bivalent vaccine comprising HPV types 16 and 18, and the quadrivalent vaccine comprising HPV types 6, 11, 16 and 18— have proven to be safe and efficacious against 6-month-persistent cervical infections of HPV16 and HPV18 and associated precancerous lesions, and both have efficacies of 90–100%30. The major structural HPV protein self-assembles into immunogenic virus-like particles and both vaccines are based on this principle. Because of the ease of making effective HPV vaccines by simply adding more virus-like particles from more HPV types to the vaccines, the composition of second generation vaccines that contain more HPV types is of interest.
Initially, HPV vaccine trials and indications for vaccination focused on prevention of clinical diseases caused by HPV (e.g., cervical cancer, cervical cancer precursors, condylomas, anal cancer, anal cancer precursors and precursors of vulvar, vaginal and penile cancers). However, with the finding that the vaccines are extremely efficacious prophylactic vaccines for prevention of HPV infections as such, the focus has shifted to establishing exactly how much disease is caused by infection with the different HPV types30.
The WHO/International Agency for Research on Cancer has a formal approach for systematically evaluating whether the available evidence from epidemiological studies and mechanistic studies allow concluding that an environmental exposure is carcinogenic to man or not. As mentioned before, HPV types HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58 and 59 are classified as established carcinogens (Class I carcinogens) for humans in the case of cervical cancer16. For anal cancer, vulvar cancer, vaginal cancer, penile cancer, oropharyngeal cancer, tonsillar cancer and oral cavity cancer only HPV type 16 is classified as established Class I carcinogen to man16. Although some of the other HPV types are sometimes also found in non-cervical tumors, they are not sufficiently common and there is not sufficient evidence to conclude that any other type than HPV16 can cause cancers outside of the cervix. Still, the total sum of human cancers that is attributable to HPV is considerable. A formal assessment by the IARC has concluded that prevention of oncogenic HPVs would prevent globally every year the following number of cases of cancer: cervical: 530,000; vulvar: 12,000; anal: 24,000; penile: 11,000; vaginal: 9,000 and oropharyngeal: 22,000 (Total sum: 608,000 preventable cases of cancer every year)44. This estimation has taken into account that the proportion of cancers attributable to HPV is different for the different cancer sites (Cervical: 100%; vulvar:43%; anal: 88%; penile: 50%; vaginal: 70% and oropharyngeal: 26%)44. It should be noted that the disease burden is quite different in different countries, particularly depending on whether effective organized screening programs exist and depending on sexual practices and spread of HPV in the population. For example, in the Western world, the non-cervical cancers constitute a much larger proportion of the total preventable number of cancer cases caused by HPV. The Catalan Institute of Oncology has assembled a website where the exact burden of HPV-
associated cancers has been estimated for every country in the world (www.hpvcentre.net). The data in Table 2 in this paper allows an estimation of how much of the different cervical cancer precursors that would be preventable by different HPV vaccines. This information strongly affects the evaluation of the cost-effectiveness of different vaccination programs. With the highly effective HPV vaccines available, most programs are shifting from merely having disease control as an aim to having elimination of infection with the major oncogenic HPV types as a goal. The numbers in Table 2 give the estimated proportion of precursor lesions that are expected to disappear if infection with a particular HPV types can be eliminated. Dynamic transmission models predict that such elimination will not be very difficult, but is likely to require both-sex vaccination programs45.
Conclusion The role of different HPV types as major human carcinogens is today well established and formally quantified by the WHO/IARC. This information has been exploited to design better cervical cancer screening tests and effective prophylactic HPV vaccines, thus providing us with new methods for cancer prevention. As the global burden of cancers is expected to rise dramatically in the future, good examples on how research can find new ways to prevent cancers are needed46. The HPV field has indeed provided a highly successful example of this.
Acknowledgement Supported by the Swedish Cancer Society and the Swedish Research Council. In the field of screening, JD declares no conflict of interest. In the field of HPV vaccines, JD
has received grants to his institution for research on HPV vaccines from Merck/SPMSD, a manufacturer of HPV vaccines.
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30. Lehtinen, M., Dillner, J. Clinical trials of human papillomavirus vaccines and beyond. Nature Reviews Clinical Oncology. 2013;10:400-410. 31. Naucler P, Ryd W, Törnberg S, Strand A, Wadell G, Hansson BG, Rylander E, Dillner J. HPV type-specific risks of high-grade CIN during 4 years of follow-up: a population-based prospective study. Br J Cancer. 2007b Jul 2;97(1):129-32. 32. Elfstrom KM, Smelov V, Johansson AL, Eklund C, Naucler P, Arnheim-Dahlstrom L, Dillner J. Long term duration of protective effect for HPV negative women: follow-up of primary HPV screening randomised controlled trial. BMJ 2014a;348: g130. 33. Elfström KM, Smelov V, Johansson AL, Eklund C, Naucler P, Arnheim-Dahlström L, Dillner J. Long-term HPV type-specific risks for ASCUS and LSIL: A 14-year follow-up of a randomized primary HPV screening trial. Int J Cancer. 2014b May 20. doi: 10.1002/ijc.28984. 34. Smelov V, Elfström KM; Johansson ALV, Eklund C, Naucler P, Arnheim-Dahlström L, and Dillner J. Long-term HPV type-specific risks for high-grade cervical intraepithelial lesions: A 14-year follow-up of a randomized primary HPV screening trial. Int J Cancer. 2014 Jul 19. doi: 10.1002/ijc.29085. 35. Dillner J, Rebolj M, Birembaut P, Petry KU, Szarewski A, Munk C, de Sanjose S, Naucler P, Lloveras B, Kjaer S, Cuzick J, van Ballegooijen M, Clavel C, Iftner T; Joint European Cohort Study. Long term predictive values of cytology and human papillomavirus testing in cervical cancer screening: joint European cohort study. BMJ. 2008 Oct 13;337:a1754. 36. Katki HA, Kinney WK, Fetterman B, Lorey T, Poitras NE, Cheung L, Demuth F, Schiffman M, Wacholder S, Castle PE. Cervical cancer risk for women undergoing concurrent testing for human papillomavirus and cervical cytology: a population-based study in routine clinical practice.
Lancet Oncol. 2011 Jul;12(7):663-72. 37. de Kok, I.M., van Rosmalen, J., Dillner, J., Arbyn, M., Sasieni, P., Iftner, T., van Ballegooijen, M. Primary screening for human papillomavirus compared with cytology screening for cervical cancer in European settings: cost effectiveness analysis based on a Dutch microsimulation model. British Medical Journal. 344:e670. 2012. 38. Dillner, J. Primary human papillomavirus testing in organized cervical screening. Current Opinion in Obstetrics and Gynecology. 2013;25:11-16. 39. Poljak, M., Cuzick, J., Kocjan, B.J., Iftner, T., Dillner, J., Arbyn, M. Nucleic acid tests for the detection of alpha Human Papillomaviruses. Vaccine. 2012;S5: F100-106. 40. Eklund C, Zhou T, Dillner J; WHO Human Papillomavirus Laboratory Network. Global proficiency study of human papillomavirus genotyping. J Clin Microbiol. 2010 Nov;48(11):4147-55. 41. Eklund C, Forslund O, Wallin KL, Zhou T, Dillner J; WHO Human Papillomavirus Laboratory Network. The 2010 global proficiency study of human papillomavirus genotyping in vaccinology. J Clin Microbiol. 2012 Jul;50(7):2289-98. 42. Eklund, C., Forslund, O., Wallin, K.L., Dillner, J. Global improvement in genotyping of Human Papillomavirus DNA: The 2011 HPV LabNet International Proficiency Study. Journal of Clinical Microbiology. 2014;52:449-459. 43. Hakama, M., Malila, N., Dillner, J. Randomised healthservice studies. Int J Cancer. 2012;131: 2898-2902. 44. de Martel C, Ferlay J, Franceschi S, Vignat J, Bray F, Forman D, Plummer M. Global burden of cancers attributable to infections in 2008: a review and synthetic analysis. Lancet Oncol. 2012 Jun;13(6):607-15. 45. Baussano, I., Dillner, J., Lazzarato, F., Ronco, G., Franceschi, S. Upscaling human papillomavirus vaccination in high-income countries: impact assessment based on
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Table 1. Type-specific prevalence of mucosal HPV DNA, by grade of cervical diagnosis. World-wide meta-analysis, adapted from17. Abbreviations: ASCUS: atypical squamous cells of undetermined significance; LSIL: low-grade squamous intraepithelial neoplasia; HSIL: high-grade squamous intraepithelial neoplasia; CIN: cervical intraepithelial neoplasia; ICC: invasive cervical cancer. ASCU LSIL HSIL CIN1 CIN2 CIN3 IAR Normal S HP C N N N N N N V classi N % % % % % % % Te Te Te Te Te Te type ficati Tes po po po po po po po ste ste ste ste ste ste on s s s s s s s ted d d d d d d 10 11 13 19 263 12 52 75 77 85 74 48 85 92 45 03 67 17 Any 971 .6 .1 .2 27 .3 .2 09 .4 .4 8 6 0 9 13 19 10 11 HP 263 2. 19 77 40 19 48 53 1 17 12 45 03 34 67 V16 971 6 .5 27 .5 .2 09 .8 8 6 0 9 13 19 11 HP 263 4. 6. 77 8. 98 47 8. 6. 1 1 16 44 7 58 V18 702 7 3 11 2 83 35 7 9 1 7 3 11 14 10 HP 243 0. 2. 3. 59 3. 85 43 4. 3. 1 59 95 3 03 V45 656 6 9 3 01 9 27 44 3 4 1 7 0 12 18 11 HP 254 0. 4. 74 7. 91 3. 46 7. 8. 1 21 3 61 12 V33 120 6 9 31 1 76 7 17 1 5 8 7 1 11 15 10 HP 247 0. 3. 5. 61 6. 87 7. 44 10 8. 1 79 05 32 V58 990 8 9 5 08 9 62 1 20 .3 4 0 2 2 HP 1 252 1 12 4. 18 7. 72 9. 91 6. 47 10 11 10
ICC N Te ste d 41 10 1 41 10 1 41 16 4 33 99 7 37 70 0 35 53 9 36
% po s 89 .5 * 55 .8 * 14 .3 * 4. 8* 4. 0* 4. 0* 3.
V31
392
19 1 10 28 8 10 18 1 10 30 6
7
9
93
4
93
8
54
25 4 10 39 9 10 22 1
.8
6. 5
52 68
8. 6
85 10 46 .1
44 14 86 .1
3. 8
54 65
5
87 63
2. 8
44 29
4. 3
5. 5
50 03
3. 8
82 14
4. 9
42 06
4. 7
97 30
3. 1
4. 3
52 70
2. 7
81 28
3. 7
41 18
4
97 67
2. 1
9. 4
54 10
6
83 20
8. 1
42 30
8. 4
98 33
5. 1
7
51 19
3. 1
83 27
5. 6
42 61
3. 7
10 04 4
2. 3
2. 2
47 01
1. 8
83 15
2. 3
39 88
2. 5
79 56
1. 9
HP V52
1
239 298
1
HP V35
1
237 554
0. 4
HP V39
1
235 758
0. 6
HP V59
1
235 145
0. 4
HP V51
1
235 223
0. 9
HP V56
1
241 829
0. 6
HP V68
2A
231 085
0. 4
95 93
1. 8
HP V53
2B
138 289
1. 1
84 09
5. 4
95 02
8. 4
44 04
4
74 45
6. 4
37 14
4. 5
86 44
3. 1
HP V73
2B
116 913
0. 3
72 16
1. 9
84 52
2. 7
37 82
2. 5
49 54
2. 3
31 84
2. 1
59 23
1. 8
HP V6
144 585
0. 8
5. 9
52 40
2. 7
63 54
6
37 10
3
87 62
1. 7
HP V11
144 039
0. 5
2. 9
51 86
0. 9
62 05
2. 5
35 47
1. 4
83 60
0. 8
HP V62
657 61
1. 0
10 30 9 10 27 8 60 92
4. 1
27 98
3. 3
32 64
6. 1
24 04
4. 1
57 11
2. 3
HP V54
128 177
0. 6
99 98 10 49 0 10 54 1
5. 4
54 6 13 01 6 14 56 6 12 72 3 12 69 1 12 68 1 12 94 9 11 64 7
3 4. 2 3. 1 4. 8 3. 5
9. 6 3. 3
4. 4
12 94 5 12 73 8 57 19
79 14
2. 4
85 70
2. 9
36 36
2. 7
61 52
2. 6
28 73
3. 2
69 45
2
3. 1 1. 6
HP V66
2B
204 436
0. 6
94 46
4
11 60 2
7. 7
47 88
3. 5
76 42
5. 9
38 71
4. 6
93 17
2. 4
HP V67
2B
839 10
0. 2
62 42
1. 2
59 75
1. 8
24 61
1. 1
33 04
1. 9
24 72
1. 5
60 14
0. 7
106 816 107 818
0. 5 0. 1
72 73 70 43
2. 8 0. 5
73 65 71 34
3. 1 0. 4
30 86 32 26
3. 2 0. 5
38 95 49 97
3. 3 0. 6
27 39 28 22
59 64 66 92
1. 8 0. 5
HP V84 HP V26
2B
3 1. 1
76 9 34 93 9 33 69 0 32 27 7 33 27 7 32 33 3 32 38 3 29 47 1 28 86 4 25 84 8 32 07 4 31 12 6 64 90 12 17 4 30 95 9 20 66 1 81 11 26 45
5* 3. 2* 1. 6* 1. 3* 1. 2* 1. 0* 0. 8* 0. 5* 0. 5 0. 5* 0. 4 0. 4 0. 4 0. 3 0. 3 0. 3* 0. 3 0. 2*
HP V30
2B
265 59
0. 1
62 0
0. 5
16 03
0. 3
47 7
0
81 1
0. 6
24 4
0. 4
40 8
0. 5
HP V69
2B
767 97
0. 1
52 10
0. 2
58 88
0. 3
23 36
0. 3
33 20
0. 3
22 19
0. 4
56 15
0. 4
HP V70
2B
117 590
0. 8
65 96
2. 4
75 87
2. 3
33 48
2. 1
58 19
1. 5
29 94
1. 7
74 80
1. 1
100 495
0. 6
67 85
2. 3
68 84
2. 8
30 26
1. 8
34 10
2. 9
23 19
3. 1
59 18
1. 1
HP V81 HP V82
2B
132 350
0. 1
67 83
1. 2
82 53
1. 8
38 86
2
50 38
1. 5
33 16
1. 8
74 63
1. 7
HP V34 /64
2B
672 41
0. 1
53 77
0. 3
64 62
0. 3
25 92
0. 2
38 69
0. 2
20 90
0
56 82
0. 1
HP V42
127 999
0. 5
72 35
4. 3
83 88
4. 8
40 24
1. 6
59 66
3. 3
29 38
2. 4
71 62
1. 2
HP V44
103 820
0. 4
22 67
0. 1
33 99
0. 3
21 94
0. 3
39 97
1. 2
20 34
0. 9
55 00
0. 4
HP V55
860 33
0. 3
68 60
1. 2
61 84
2. 2
28 89
1. 8
32 10
1. 4
18 25
1. 4
50 74
1. 2
HP V61
100 536
0. 6
62 43
3. 5
65 61
3. 8
30 13
3. 5
43 99
2. 7
26 11
2. 9
63 22
2. 2
HP V71 HP V72 HP V83 HP V89 HP V90
889 89 944 06 111 587 705 78 249 01
0. 4 0. 3 0. 4 0. 4 0. 6
57 14 60 46 68 43 45 63 32 2
0. 7 0. 7 2. 1
1. 9
51 89 61 33 73 77 51 61 10 78
0. 4 0. 8 1. 9 3. 4 1. 9
24 21 26 40 30 89 24 00 28 7
35 24 31 98 40 92 30 92 47 9
0. 3 0. 5 2. 2 5. 2 0. 8
23 47 22 04 23 60 18 25 13 2
0. 4 0. 5 1. 4 3. 1 0. 8
58 05 57 45 56 96 52 42 23 0
0. 4 0. 6 1. 5 2. 3 0. 9
HP V32
568 02
0. 1
26 75
0. 3
24 15
0. 1
10 66
0. 3 0. 8 1. 8 2. 9 0. 7 < 0. 1
89 4
0. 1
89 5
0. 6
23 14
0. 1
HP V40
915 96
0. 2
73 28
0. 9
79 40
1. 6
36 85
0. 6
54 00
0. 8
26 22
1
63 83
0. 4
HP V43
897 87
0. 3
21 98
0. 5
34 98
0. 3
21 60
0. 1
21 82
0. 4
82 2
0. 2
40 44
0. 1
HP V57
641 70
< 0.
35 26
0. 1
44 48
< 0.
18 48
< 0.
13 31
< 0.
58 9
< 0.
38 54
0. 1
3
9 13 0. 76 2* 3 17 0. 92 2* 9 27 0. 80 2 2 90 0. 48 2 28 0. 10 2* 5 22 0. 23 1 3 22 0. 66 1 7 21 0. 16 1 2 79 0. 13 1 20 0. 87 1 4 83 0. 89 1 91 0. 73 1 95 0. 25 1 85 0. 65 1 18 0. 53 1 < 36 0. 40 1 11 < 22 0. 4 1 < 95 0. 35 1 67 < 64 0.
1 HP V74
1
1
1
1
606 97
0. 5
47 62
0. 2
37 20
0. 6
12 88
0. 8
13 02
0. 5
68 5
0. 7
35 40
0. 1
48 82
301 97
0. 2
16 95
0. 4
10 36
0. 4
56 1
0. 5
11 34
0. 2
10 18
0. 3
10 53
0. 2
25 49
HP V86
152 99
0. 1
25 4
0. 4
56 2
0. 4
22 0
< 0. 1
47 9
< 0. 1
13 2
18 4
< 0. 1
18 01
HP V87
598 7
0. 1
18 9
0. 5
10 32
0. 2
26 0
0. 4
47 8
0. 4
12 9
22 2
0. 5
96 3
HP V91
540 3
0. 2
88 2
3. 6
10 69
4. 2
35 5
3. 1
60 3
2. 5
27 2
28 1
2. 5
11 70 6
HP V85
Tota l
2B
13 18 18 18 6. 9. 5. 3. 6 1 0 4 * = higher prevalence in ICC than in normal cytology 28 .3
< 0. 1 < 0. 1 2. 6 21 0. 2
18 2. 9
1 < 0. 1 < 0. 1 < 0. 1 < 0. 1 < 0. 1 11 3. 6
Table 2. 1st Screening Round Population Attributable Proportion (PAR) (% with (95% confidence interval of the proportion) for different oncogenic HPV types. Follow-up up to 14 years of the Swedish nationwide randomized HPV screening trial of 12527 women. Adapted from33, 34.
HR HPV negative HPV 16 HPV 18 HPV 31 HPV 33 HPV 35 HPV 39 HPV 45 HPV 51 HPV 52 HPV 56
CIN2+
CIN3+
-46.9 (35.6-56.2) 7.1 (1.6-12.4) 8.8 (2.6-14.5) 3.2 (0.0-7.2) 1.8 (0.0-4.5) 0.8 (0.0-2.7) 8.9 (2.5-14.9) 2.7 (0.0-6.3) 8.8 (2.6-14.6) 1.3
-35.9 (27.8-43.1) 6.6 (2.6-10.5) 10.9 (5.8-15.8) 5.5 (1.6-9.2) 0.9 (0.0-2.4) 2.1 (0.0-4.4) 7.2 (2.7-11.4) 2.3 (0.0-4.9) 9.3 (4.5-13.8) 2.2
ASCUS
LSIL
CIN1
-15.5 (9.721.0) 4.2 (1.17.2) 8.5 (4.312.6) 3.1 (0.35.8) 1.8 (0.03.7) 1.7 (0.03.7) 5.9 (2.39.5) 3.8 (0.86.7) 6.3 (2.510.0) 0.8 (0.0-
-14.7 (8.020.9) 6.7 (2.311.0) 11.5 (6.016.8) 3.4 (0.16.5) 1.8 (0.04.1) 2.5 (0.05.1) 4.4 (0.58.1) 3.0 (0.06.1) 4.0 (0.37.6) 4.2 (0.7-
-13.4 (3.222.5) 7.3 (0.014.0) 17.3 (6.826.6) 3.9 (0.09.2) 3.0 (0.07.5) 1.3 (0.04.4) 6.8 (0.013.5) 5.2 (0.011.3) 8.6 (0.716.0) 4.4 (0.0-
HPV 58
(0.0-3.9) 5.3 (0.05-9.9)
HPV 59
--
HPV 66
--
HPV 68
--
(0.0-4.7) 5.2 (1.7-8.7) 0.1 (0.0-0.5) 0.3 (0.0-1.4) 0.3 (0.0-1.2)
2.3) 2.0 (0.04.2) -0.7 (0.02.2)
-19.9 54.0 42.9 (13.3HPV 16/18 (42.5-63.2) (34.4-50.3) 25.7) 32.6 66.1 59.6 (24.9HPV 16/18/31/33 (54.7-74.7) (50.8-66.8) 39.5) 33.9 88.2 80.8 (20.9HPV16/18/31/33/45/52/58* (79.3-93.3) (73.3-86.2) 44.8) 52.4 94.5 89.9 (43.1Any HR type (87.1-97.7) (83.7-93.8) 60.2) *For the low-grade lesions (ASCUS, LSIL and CIN1), the estimates for HPV16/18/31/33/45/52/58 also include HPV6/11.
7.7) 5.1 (1.38.8) 0.6 (0.02.1) -1.1 (0.83.0) 21.5 (13.828.6) 36.2 (26.944.3) 43.4 (28.855.0) 62.5 (52.170.7)
9.7) 2.1 (0.06.3) 1.1 (0.04.1) 0.6 (0.03.2) -21.2 (8.931.9) 43.7 (28.455.7) 43.9 (20.060.7) 69.1 (53.279.6)
Table 3. The cumulative incidence proportions to develop cervical lesions on an on average 11 years followup after testing HPV-positive for different HR-HPV types. % with (95% confidence interval). Follow-up up to 14 years of the Swedish nationwide randomized HPV screening trial of 12527 women. Adapted from33, 34. HPV type
HR HPV negative
HPV 16
HPV 18
HPV 31
HPV 33
HPV 35
HPV 39
HPV 45
HPV 51
CIN2+
1.9 (1.5-2.5)
42.8 (36.4-49.8)
39.4 (28.4-52.8)
41.9 (31.1-54.6)
54.2 (37.6-72.5)
15.6 (6.1-36.9)
17.6 (8.3-35.1)
24.1 (17.2-33.1)
10.5 (5.6-19.2)
HPV 52
27.7 (20.3-37.0)
HPV 56
13.8 (7.4-25.0)
HPV 58
HPV 59
HPV 66 HPV 68
32.1 (20.4-48.2)
8.1 (2.7-23.2)
16.0 (8.1-30.3) 12.1 (3.1-41.5)
CIN3+ ASCUS 0.9 (0.61.3) 34.5 (28.441.5) 29.7 (19.643.4) 28.4 (18.242.7) 34.1 (19.255.6) 15.6 (6.136.9) 9.1 (3.025.8) 16.0 (10.424.2) 7.0 (3.214.9) 14.0 (8.821.8) 4.6 (1.513.6) 18.3 (9.633.3) 5.6 (1.420.5) 5.9 (1.917.2) 7.1
LSIL
CIN1
7.9 (7.0–9.0)
2.8 (2.3–3.4)
2.0 (1.5–2.6)
19.2 (14.7– 24.7)
17.0 (12.8– 22.3)
7.1 (4.3–11.6)
16.8 (9.9– 27.6)
23.2 (14.4– 36.2)
7.1 (3.0–16.2)
27.3 (20.0– 36.6)
25.1 (15.5– 39.2)
14.6(9.3– 22.4)
21.4 (11.7– 37.3)
32.6 (19.3– 51.5)
14.2 (5.3– 27.3)
17.4 (7.6– 36.9)
13.8 (5.4–32.7)
6.9 (1.8–24.9)
11.4 (4.5– 27.6)
11.5 (4.5–27.9)
2.9 (0.4–18.6)
19.2 (12.7– 28.6)
11.8 (7.0–19.5)
6.2 (3.0–12.6)
14.2 (7.9– 25.0)
9.5 (4.8–18.0)
4.7 (1.8–12.1)
24.7 (17.3– 34.6)
14.9 (9.4–23.3)
13.6 (7.9– 22.8)
9.9 (4.5–20.9)
11.6 (6.0–21.9)
5.8 (2.2–14.7)
21.0 (11.5– 36.5)
20.3 (11.1– 35.3)
4.6 (1.2–17.0)
2.8 (0.4–18.1)
10.5 (4.1–25.6)
2.6 (0.4–16.8)
18.2 (10.2– 31.3)
11.8 (5.4–24.7)
5.9 (1.9–17.7)
10.1 (2.6–
17.1 (5.6–45.5)
–
HPV 16/18
HPV 16/18/31/33
Any HR type
(1.040.9) 32.7 (27.441.5 (36.0-47.6) 38.8) 31.7 (26.542.2 (36.8-48.0) 37.7) 20.7 (17.629.9 (26.5-33.5) 24.2)
34.7) 18.7 (14.8– 23.6)
17.7 (13.9– 22.5)
7.2 (4.7–11.1)
21.0 (17.5– 25.1)
20.6 (16.2– 25.9)
9.1 (6.7–12.3)
18.0 (15.6– 20.7)
15.6 (12.9– 18.7)
7.2 (5.6–9.2)
Table 4. The adjusted incidence rate ratio (IRR) to develop cervical lesions on an on average 11 years followup after testing HPV-positive for different HR-HPV types. % with (95% confidence interval). Follow-up up to 14 years of the Swedish nationwide randomized HPV screening trial of 12527 women. Adjusted for follow-up time (1-year intervals), age at entry, study arm, and individual HPV type data. Adapted from33, 34.
HPV type HR HPV negative
CIN2+ Reference
HPV 16
13.1 (10.3-16.7)
HPV 18
7.4 (4.8-11.4)**
HPV 31
11.0 (7.9-15.3)
HPV 33
4.5 (2.7-7.4)**
HPV 35
3.2 (1.2-8.9)**
HPV 39
7.2 (3.2-16.3)
HPV 45
4.6 (3.0-7.0)**
HPV 51
1.8 (0.9-3.6)**
HPV 52
6.4 (4.4-9.4)**
HPV 56
3.4 (1.7-6.5)**
HPV 58
7.0 (4.0-12.2)
HPV 59
1.7 (0.5-5.3)**
HPV 66
1.0 (0.5-2.1)**
HPV 68
1.7 (0.4-6.9)**
HPV 16/18
15.5 (12.3-19.4)
HPV 16/18/31/33
23.1 (18.8-28.5)
Any HR type **
30.7 (24.6-38.1)
CIN3+ Reference 19.5 (14.625.9) 9.4 (5.715.5)** 9.6 (6.314.8)** 2.4 (1.24.7)** 6.8 (2.518.7)** 6.2 (2.019.6) 4.6 (2.77.8)** 2.0 (0.84.6)** 4.9 (2.98.2)** 1.7 (0.65.4)** 4.2 (1.99.0)** 1.8 (0.57.4)** 0.6 (0.22.0)** 1.3 (0.29.5)** 22.9 (17.430.3) 32.3 (24.742.4) 42.0 (30.957.1)
ASCUS Reference
LSIL Reference
CIN1 Reference
3.2 (2.3–4.2) 4.6 (3.3–6.4) 2.9 (1.7–4.8) 2.6 (1.4–4.6) 5.4 (3.1–9.3) 3.2 (1.2–8.2) 4.8 (3.3–6.9) 2.6 (1.3–5.2)
7.3 (4.8– 11.3) 6.4 (3.4– 11.9)
2.7 (1.1–6.6) 3.4 (1.2–9.5) 2.1 (0.8–5.7)
4.9 (1.8– 13.2)
9.0 (5.4– 15.0)** 4.7 (1.9– 12.0) 3.2 (0.7– 13.5) 1.5 (0.2– 10.6)
3.1 (2.0–4.9) 2.9 (1.6–5.0) 2.9 (1.3–6.3) 2.3 (1.3–4.3) 2.4 (1.1–4.9) 1.9 (0.6–5.5) 3.6 (2.4–5.4) 3.5 (2.1–5.8)
5.8 (3.2– 10.4)
1.4 (0.6–3.0) 3.5 (1.7–7.2) 3.1 (1.2–8.5) 3.8 (1.9–7.3) 0.3 (0.0– 2.4)** 1.8 (0.9–3.4) 1.1 (0.3–4.4)
7.3 (3.7– 14.4)
1.9 (0.4–7.9)
2.1 (0.7–5.7) 1.1 (0.2–8.0) 1.3 (0.5– 3.0)** 3.4 (1.1– 11.0)
1.2 (0.4–4.0)
3.2 (2.5–4.2) 5.5 (4.1–7.4) 3.2 (2.0–5.2) 4.3 (3.5–5.4) 7.7 (6.0–9.9) 5.8 (4.0–8.2) 4.3 (3.6–5.2)
8.5 (6.8– 10.6)
Type-specific IRR that was significantly different from HPV 16 IRR, p < 0.05
6.1 (4.5–8.3)