Comparing HPV vaccination modeled CIN3+
outcomes with real-world evidence
Abstract
BACKGROUND: Vaccines against human papillomavirus infections are introduced in the national immunization program in many countries. Nowadays, long-term efficacy data is available from clinical trials and real-world settings. Here, we compare existing model predictions with observed
long-term efficacy data and real-world data (RWD) on the outcomes of CIN3+ (cancer). METHODS: We performed a literature search for efficacy and effectiveness of the bivalent HPV vaccine. We review the data on reductions of CIN3+, from both RCT’s and RWD. In addition, model
predicted outcomes on CIN were collected.
RESULTS: The bivalent vaccine showed reductions in CIN3+ in clinical trials and real-world data up to around 80-90%. Opposite these findings, model predicted reductions in the cancer remain all well
below the 80-90%.
CONCLUSION: Current HPV models seem insufficient in providing insight in the actual clinical benefits of the bivalent HPV vaccine. Further work should be directed to better capture the vaccine efficacy on CIN3+ of the bivalent vaccine within HPV vaccination models. Future research to herd
immunity and cross-protection is important.
Author information
Name: Frieda de Boer Study: MSc BA-Health Student nr.: 2943832
E-mail: f.h.de.boer.1@student.rug.nl Supervisor: Prof. dr. M. J. Postma Co-assessor: dr. U.C.P. Schneider Word count: 7597
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Table of content
1. Introduction ... 3 1.1 Research question ... 6 2. Literature review ... 8 2.1 The vaccination ... 82.2.1 The bivalent HPV vaccine ... 8
2.1.2 CIN3+ ... 8
2.1.3 Cross-protection ... 9
2.1.4 Herd immunity ... 9
2.2 Data HPV vaccination ... 9
2.2.1 HPV simulation models ... 9
2.2.2 Real-world data and clinical trials ... 10
2.2.3 Clinical trials ... 10
2.2.4 ICER and QALYs ... 11
2.3 Conceptual model ... 11
3. Methodology ... 12
3.1 The search ... 12
3.2 Data extraction and analysis ... 14
4. Results ... 15
4.1 Cost-effectiveness search (model predicted outcomes) ... 15
4.2 Model results ... 18
4.3 Cost-effectiveness, herd immunity, and cross-protection ... 19
4.4 Long-term efficacy and effectiveness data ... 20
4.4 Results of long-term efficacy & effectiveness data ... 22
4.5 cross-protection model ... 23
5. Discussion ... 27
6. Conclusion ... 30
7. References ... 31
8. Appendixes ... 36
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1. Introduction
Cervical cancer is the fourth-most-frequent cancer in women in the world. In 2018, 311,000 women died from this type of cancer, and an estimated 570,000 new cases were diagnosed (Haroz, 2019). The high mortality rate could be reduced through cancer prevention, early diagnosis, and effective screening and treatment programs. Cervical cancer screening programs exist in most developed countries; however, their efficacy and coverage are variable (Catarino, Petignat, Dongui, & Vassilakos, 2015). Effective screening is costly, which limits its widespread introduction. Moreover, diagnosis and treatment of pre-cancerous lesions are expensive (Skinner, Apter, De Carvalho, Harper, Konno, Paavonen, & Struyf, 2016). Cancer prevention offers the most cost-effective, long-term strategy for the control of cancer (WHO, 2018).
Human papillomavirus (HPV) is a sexually transmitted virus that is considered a necessary factor in the development of cervical cancer. While most HPV infections resolve spontaneously, persistent infections can lead to precancerous lesions (CIN) and cancer of the cervix, vagina, vulva, anus, penis, and head and neck (Bergman, Buckley, Villanueva, Petkovic, Garritty, Lutje, & Henschke, 2019). Many types of HPV are classified as a high-risk (cancer-causing) or low-risk (warts-(cancer-causing) virus. The high-risk types (16, 18, 45, 31, 33, 39, 52, 58, and 35) have been recognized as a necessary etiological agent for the development of cervical cancer and premalignant cervical lesions (Munoz, 2000), and the low-risk types (6, 11, 34, 40,42, and 44) have been associated with genital warts and low-grade cervical lesions (Munoz, 2000). The HPV types 16 and 18, which are high-risk and cancer-causing, are associated with approximately 71% of all cervical cancer cases (Woestenberg, King, van Benthem, Donken, Leussink, van der Klis, & Bogaards, 2017).
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that large numbers of CIN2 cases spontaneously regress (Lehtinen, Paavonen, Wheeler,
Jaisamrarn, Garland, Castellsagué, & Chow, 2012). It is preferable to conduct research on CIN3, as these studies will lead to results of a higher quality than CIN2. CIN3 is a more specific marker of the risk of cervical cancer than CIN2, because CIN2 diagnoses are likely to vary greatly later on (Carreon, Sherman, Guillén, Solomon, Herrero, Jerónimo, & Burk, 2007). CIN3 is the immediate precursor of cervical cancer and is considered a more predictive endpoint than CIN2 (Lehtinen et al., 2012). However, few studies have been conducted on CIN3+. The number of years post-vaccination make it insufficient to examine the impact of HPV vaccination on cervical intraepithelial neoplasia grade 3+ (CIN3+) (Lehtinen et al., 2017).
Vaccines designed to help prevent cervical cancer protect against common cancer-causing types of the human papilloma virus and reduce the risk of cervical cancer (Haroz, 2019).
Vaccination is one of the most cost-effective interventions in public health (Westra, 2013). Three vaccines have been licensed for the prevention of HPV infections, providing protection against 2, 4, or 9 HPV types. In 2006, the quadrivalent HPV vaccine Gardasil was licensed in Europe; this vaccine protects against infections of HPV types 16, 18, 6, and 11. It was followed by the
bivalent HPV vaccine Cervarix in 2007; this vaccine protects against infections of HPV types 16 and 18 (Paavonen, Naud, Salmerón, Wheeler, Chow, Apter, & Hedrick, 2009).Both vaccines provide a high level of protection against HPV types 16- and 18-attributable lesions. Later, in 2015, the nonavalent HPV vaccine Gardasil9 was licensed in Europe. This vaccine protects against five high-risk HPV types that were not included in the first-generation HPV vaccines— HPV types 31, 33, 45, 52, and 58—in addition to HPV types 6, 11, 16, and 18 (Hartwig et al., 2017).
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two-dose schedule (Righolt et al., 2019). Some countries began with the introduction of the bivalent vaccine but later changed to the quadrivalent vaccine. For example, in the England and Scotland, the immunization program changed to use the quadrivalent vaccine in 2012
(
Mesher, Panwar, Thomas, Edmundson, Choi, Beddows, & Soldan, 2018). In the Netherlands, the bivalent vaccine Cervarix is recommend by the national immunization program, which began vaccinating girls in 2009 (Paavonen et al., 2009).More than 10 years have passed since the introduction of the vaccination in the
Netherlands’ national immunization program, which allows analysis of changes in the efficacy of the HPV vaccine since its introduction. Moreover, global statistics concerning the direct
effectiveness of the bivalent vaccine have become available from observational studies (Mollers, King, Knol, Scherpenisse, Meijer, van der Klis, & de Melker, 2015). It is important to verify the promising results from clinical trials and model predictions. At the time of the introduction of the vaccine, only short-term data was available, but long-term efficacy data is available now from clinical trials and real-world data. This is an important reason for conducting this research (Skinner, Apter, De Carvalho, Harper, Konno, Paavonen, & Struyf, 2016). In this study, we compared the predicted long-term effectiveness of vaccines with real-world, long-term data and whether they coincide at population level. Furthermore, we reviewed the long-term efficacy and effectiveness data for the bivalent vaccine and compared model predictions with long-term efficacy data from randomized clinical trials (RCTs) and real-world data (RWD).
In our study, the focus is on the bivalent HPV vaccine, because it is unclear how the predicted long-term effectiveness of the vaccine compares with real-world, long-term data and whether it coincide at population level. An overall reduction of CIN3+ in clinical trials has been demonstrated in studies examining the quadrivalent vaccine; this also is aligned with the
reduction of CIN3+ in real-world settings. The modeled findings for CIN3+ with the quadrivalent vaccine are significantly in line with the reductions seen in the real-world settings (Munoz, Kjaer, Sigurdsson, Iversen, Hernandez-Avila, Wheeler, & Garcia, 2010). According to Munoz et al. (2010), the vaccine correlates to a 43% reduction in CIN3+ in clinical trials and real-world settings. Current model predictions for the quadrivalent vaccine are estimated at 40-50%
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yet available for the nonavalent vaccine (Guevara, Cabello, Woelber, Moreira, Joura, Reich, & Luxembourg, 2017). A study concerning the model predicted outcomes on CIN3+ from the bivalent vaccine compared with the RWD and RCTs, is not considered before. The reduction in CIN3+ differed by vaccine type. Overall, the bivalent HPV vaccine showed high efficacy for protection against CIN3+. However, long-term data is needed to confirm this outcome (Arbyn, Xu, Simoens, & Martin‐Hirsch, 2018). Therefore, our focus is on the bivalent vaccine.
As mentioned earlier, this study compares model-predicted outcomes for the bivalent HPV vaccine with observed outcomes in the real world. In particular, we investigate whether the predicted CIN3+ reductions from the models are in line with real-world data. This is done by means of a systematic literature review. The aim in this study is to explore differences between the interpretations of the efficacy of the bivalent vaccine. The intention is to reveal differences between the outcomes from models and real-world evidence as well as identify a reason for the differences. With this clarification, we try to find a solution for adjusting the current models. This study aims to provide better insight into various outcomes of the efficacy and effectiveness of the bivalent HPV vaccine, with a goal of adjusting the health-economic models to better capture the current effectiveness of the bivalent vaccine.
Taking everything into account, this generates the following research question with three sub-questions:
1.1 Research question
“What are the similarities between model-predicted outcomes of CIN3+ and long-term, real-world results of the bivalent HPV vaccination?”
Sub-questions:
1. What do HPV vaccine models predict for reductions in CIN3+, and how are they described in the literature?
2. What does long-term efficacy data reveal about the reduction of CIN3+ through use of the bivalent HPV vaccine in RCTs and RWD?
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2. Literature review
Several concepts important to this study, some flow from the main research question and sub-questions, are addressed in this chapter. First, a short definition of each concept is given,
followed by information about what previous researchers have discovered. Since this study examines a relatively new area, we provide information about the majority of concepts that led to the current research. This section ends by linking the different parts of the literature review into a conceptual model.
2.1 The vaccination
2.2.1 The bivalent HPV vaccine
More than 10 years have passed since the implementation of the human papillomavirus vaccination in the Netherlands’ national immunization program (Drolet et al., 2019). As mentioned in the introduction, three types of vaccines are available throughout the world: the bivalent vaccine, the quadrivalent vaccine, and the nonavalent vaccine. These three vaccines are created through genetic technologies and are non-infectious, because they do not contain viral DNA (Bergman et al., 2019). The vaccines are known by the number of different HPV types they contain, with the bivalent vaccine Cervarix (GlaxoSmithKlineBiologicals, Belgium) targeting the HPV types 16 and 18(Paavonen et al., 2009).Previous research reveals that the protection against HPV types 16 and 18 lasts at least 10 years (Harper & DeMars, 2017). In the Netherlands, the bivalent vaccine was licensed in 2007. In 2009, the Dutch HPV vaccination program started with a catch-up program for girls ages 12-16 years (born in 1993-1996). Since 2010, girls have been offered the vaccination in the year they turn 13 (Woestenberg et al., 2017).
2.1.2 CIN3+
Cervical intraepithelial neoplasia (CIN) is the precancerous stage of cervical carcinoma. According to Westra (2013) is CIN classified in three different stages: mild (CIN1), moderate (CIN2), and severe (CIN3). A typical progression from HPV infection to CIN3 takes
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reasonable to expect that a reduction in CIN3 will lead to a reduction in cervical cancer in the future (Palmer et al., 2019). Approximately 80% of CIN3 lesions are caused by HPV type 16 and/or 18 (Lethinen et al., 2012). Research has revealed that the bivalent vaccine provides better protection against CIN3+ in comparison to the quadrivalent vaccine (Harper & DeMars, 2017).
2.1.3 Cross-protection
The concept of cross-protection is important in understanding the overall vaccine effectiveness and potential clinical impact of the bivalent HPV vaccination program
(Woestenberg et al., 2017). The most prevalent HPV type in cervical cancer is HPV type 16, followed by HPV type 18. These types are linked with approximately 71% of all cervical cancers, with an additional 14% linked to HPV types 31, 33, and 45 (Skinner et al., 2016). The bivalent vaccine provides significant efficacy in the cross-protection against these latter three HPV types (Malagón, Drolet, Boily, Franco, Jit, & Brisson, 2012). Furthermore, recent evidence
demonstrates that the bivalent vaccine has a higher efficacy against HPV types 31, 33, and 45 as compared to the quadrivalent vaccine (Drolet et al., 2015). Cross-protection from the bivalent HPV vaccine thereby enhances its overall effectiveness (Harari, Chen, Rodríguez, Hildesheim, Porras, Herrero, & Schiffman, 2015).
2.1.4 Herd immunity
The durability of natural immunity is a strength of herd immunity generated by the vaccine. Through vaccination, more people are immune to the HPV infection, and a result is resistance to the spread of the disease (Woestenberg et al., 2017). Recent studies have reveal evidence for potential development of herd immunity in the non-vaccinated population in Australia. Herd immunity is observed in the population, this will have positive effects the
decreasing of the HPV virus. Nonetheless, few studies have been published concerning the effect of herd immunity in the population, particular studies in which vaccination is linked to viral outcomes (Tabrizi, Brotherton, Kaldor, Skinner, Liu, Bateson, & Malloy, 2014).
2.2 Data HPV vaccination
2.2.1 HPV simulation models
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Sasieni, 2018). Models are a form of a methodological approach, which has strengths and limitations. A strength is that models are explicit, systematic, and quantitative (Landy et al., 2018). Two different model types are often used for interventions against infectious diseases: a static model (most often the Markov model) or a dynamic model. A Markov model is a
mathematical system that simulates transitions from one health state to another during specified time periods (Westra, 2013). Most commonly, the Markov model is used for infectious diseases. However, herd immunity is not considered in static models (Kim & Goldie, 2008). When indirect effects of the vaccination are to be expected, dynamic models should preferably be used. For example, these models will provide more reliable predictions under moderate vaccination coverage (Jit, Choi, & Edmunds, 2008).
2.2.2 Real-world data and clinical trials
In lieu of clinical trials, mathematical models are made and used to predict the long-term, population-level effectiveness of vaccination programs. Modeling studies have predicted that HPV-related diseases will decrease over the coming decades through vaccination (Kim et al., 2008). However, uncertainty remains concerning the potential population-level effects. The number of years post-vaccination are insufficient to examine the impact of the HPV vaccination (Drolet et al., 2015). High efficacy against multiple endpoints was consistently observed in clinical trials, however, it is important to document how trial results translate to real-world settings (Garland, Kjaer, Muñoz, Block, Brown, DiNubile, & Saah, 2016). When real-world data is used instead of a selected cohort, the data is more reliable. The real-world data can be defined as patients’ health and lifestyle data that is obtained through real-world settings. More complete information can be obtained (Garland et al., 2016). The impact in real-world settings has become increasingly evident in recent years, especially among girls who are vaccinated before their sexual debut (Palmer, Wallace, Pollock, Cuschieri, Robertson, Kavanagh, & Cruickshank, 2019).
2.2.3 Clinical trials
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than 90% (Woestenberg et al., 2017). The most important RCT concerning bivalent HPV vaccination is the PATRICIA trial, which is included in our literature review (Lehtinen et al., 2012).
2.2.4 ICER and QALYs
Decisions for policy-makers are supported by studies which evaluate the costs of vaccination in relation to the expected health gain of the HPV vaccination interventions. The most economic evaluations of the bivalent HPV vaccine, demonstrate favorable
cost-effectiveness ratios (Seto, Marra, Raymakers & Marra, 2012). The threshold in the Netherlands for the ICER is €20,000 per QALY and the costs per QALY were €18,472 (Westra, 2013). According to Westra (2013), the bivalent HPV vaccine provides the highest reduction in the incidence of cervical cancer. Consequently, the highest number of life-years gained was obtained by implementing the bivalent vaccine, resulting in a more favorable incremental
cost-effectiveness ratio (ICER). Studies have also demonstrated that the bivalent HPV vaccine
remains the most cost-effective vaccine (Harper & DeMars, 2017). Finally, the cost-effectiveness of the HPV vaccination was found to be more favorable in a setting with a moderate or poor screening program (Seto et al., 2012).
2.3 Conceptual model
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3. Methodology
3.1 The search
To answer the main research question, “What are the similarities between model-predicted outcomes of CIN3+ and long-term, real-world results of the bivalent HPV vaccination?,” a systematic literature review was performed. The literature that is available describing model-assessing reductions in CIN3+ and the literature considering the reduction in CIN3+ in clinical trials and real-world data will be studied. We will report the data according to the Preferred Reporting Items for Systemic Reviews and Meta-Analysis (PRISMA). The PRISMA statement consists of a checklist and a flow diagram. The flow diagram maps out the number of records identified, included, and excluded, and the reasons for exclusions (Moher, Liberati, Tetzlaff, & Altman, 2009).
Studies were eligible for inclusion if they fulfill the following criteria:
When the outcome data is specific regarding the bivalent HPV vaccine; and When reductions of CIN3+ are given as a result.
Articles were excluded when they meet the following exclusion criteria: When they are non-English;
When only the abstract is available;
When nothing is said regarding cervical cancer; and
13 3.2 Search strategy and selection criteria
Our search strategy had different stages. First, we searched in the PubMed database for model predictions with a combination of the following medical subject heading (MeSH) terms, title, or abstract (tiab) words:
(“Papillomavirus Infections” [MeSH] OR “DNA Virus Infections” [MeSH] OR
“Papillomaviridae” [MeSH] OR “Alphapapillomavirus” [MeSH] OR “Human Papillomavirus 16/18” [MeSH] OR “Cervical Intraepithelial Neoplasia” [MeSH] OR HPV [tiab] OR human papillomavirus [tiab] OR cervical cancer [tiab] OR oropharyngeal cancers [tiab] OR HPV-16/18 [tiab] OR Human Papillomavirus [tiab]) AND (“Papillomavirus Vaccines” [MeSH] OR vaccine [tiab]) AND (bivalent [tiab] OR Cervarix[tiab]) AND (“Models” [MeSH] OR “Economics” [MeSH] OR “Models, Economic” [MeSH] OR “Cost-Benefit Analysis” [MeSH] OR “Markov Chains” [MeSH] OR “Monte Carlo Method” [MeSH] OR model [tiab] OR economic evaluation [tiab] OR cost-effectiveness [tiab] OR cea [tiab] OR markov [tiab]) AND (“Carcinoma in Situ” [MeSH] OR Cervical Intraepithelial Neoplasms [tiab] OR Cervical Intraepithelial Neoplasia, Grade III [tiab] OR CIN3+ [tiab] OR cross protection [tiab]).
Secondarily, we searched in the same database for long-term efficacy data with the following MeSH and tiab terms: (“Papillomavirus Infections” [MeSH] OR “DNA Virus Infections” [MeSH] OR “Papillomaviridae” [MeSH] OR “Alphapapillomavirus” [MeSH] OR “Human Papillomavirus 16/18” [MeSH] OR “Cervical Intraepithelial Neoplasia” [MeSH] OR HPV [tiab] OR human papillomavirus [tiab] OR cervical cancer [tiab] OR oropharyngeal cancers [tiab] OR HPV-16/18 [tiab]) AND (“Papillomavirus Vaccines” [MeSH] OR Cervarix [tiab] OR vaccine [tiab] OR bivalent [tiab] OR AS04 [tiab] OR Bivalent Human Papillomavirus Vaccine [tiab]) AND (Real world data [tiab] OR RWD [tiab] OR real world evidence [tiab] OR real world study [tiab] OR population based data [tiab] OR population study [tiab] OR population based [tiab] OR crossectional study [tiab] OR total effectiveness [tiab] OR global estimates [tiab] OR
14 3.2 Data extraction and analysis
Our primary outcomes were on the reductions in CIN3+ after dispensing the bivalent vaccine, comparing the model-predicted outcomes and the long-term efficacy data outcomes. All of the established articles were collected in Abstractr, a web application that eases the
abstract-screening process of systematic reviews. In this program, we excluded articles, included articles, and designated some articles with the value “maybe”. Articles in the “maybe” category were evaluated full text, in this way is decided whether to include or exclude these articles.
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4. Results
In this chapter, included articles are represented in two overviews. First, the
cost-effectiveness search is demonstrated. Important highlights are mentioned and, more important, the reduction in CIN3+ is indicated. Afterwards, this is done for the long-term efficacy and effectiveness data.
4.1 Cost-effectiveness search (model predicted outcomes)
In the first database search considering the model-predicted outcomes, 113 articles were identified, and 3 additional articles, which were found during the second literature research, were added. This makes a total of 116 records. We started with the exclusion of the articles that did not discuss the bivalent vaccine or use a cost-effectiveness analysis. Thereafter, full-text articles were screened, and all reviews were excluded. Furthermore, all articles without outcomes with CIN, that were not written in English, and that included real-world data were excluded. Thirteen articles met the inclusion criteria. The literature search is outlined in the PRISMA flow diagram below. In Model 1, an overview of the cost-effectiveness analysis, all inputs included in this systematic review are included. The model is presented on the following page.
16 Model Group Definition
vaccine Country Vaccine coverage in base case Duration of protection Cross-protection HPV types Vaccine efficacy against HPV type 16/18
CIN outcomes bivalent vaccine
Van de Velde et al., 2012 Individual-based, transmissio n-dynamic model Women in a cervical cancer screening in Canada
Bivalent Canada 70% Lifetime Yes, HPV
types 31/33/45/52, and 58 98-100% 51.0% reduction of CIN2/3 Bardach et al., 2017 Markov model
Cohort of girls aged 11 years in Venezuela
Bivalent Venezuela 95% for a three-dose scheme
Lifetime Yes, for HPV types 31/33/35/39/ 45/51/52/56/ 58, and 59 98% 68.4% reduction in CIN2+ Horn et al., 2013 Dynamic mathematic al model
The sexually active population in Germany
Bivalent Germany 50% 10 years Yes, HPV types 31/33/35/39/ 45/51/52/56/ 58/59
98% 37.8% reduction CIN2+ without cross-protection, 47.9% with cross protection
Tully et al., 2012
Dynamic model
Males and females were recruited (i.e., entered the model population) at age 15 in Canada
Bivalent Canada 80% Lifetime Yes, no
types mentioned
High efficacy (> 90%)
37% reduction CIN2+ after adjusting for co-infections
Zhang et al., 2016
Markov model
12-year-old girls who are vaccinated in addition to current screening in China
Bivalent China 70% Lifetime No 93.2% 64.9% reduction in CIN2/3
Lee et al., 2011
Markov model
Cohort of women in Singapore who turned 12 years old in 2008
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Demarteau et al., 2012
Markov model
The model included an age cohort of girls aged 12 years in Taiwan
Bivalent and quadrivalent
Taiwan 100% Lifetime Yes, HPV
types 31/33/35/39/ 45/51/52/56/ 58, and 59 98% 66.6% reduction in CIN2/3 Germar et al., 2017 Markov model Cohort of 13-year-old girls for the year 2013 was considered in the model
Bivalent Philippines 100% Lifetime Yes, HPV types 31/33/35/39/ 45/51/52/56/ 58, and 59 98% 75.9% reduction in CIN2/3 Liu et al., 2016 Markov model Hypothetical cohort of 12-year-old girls to 55-year-old women
Bivalent China 70% Lifetime No 93.2% 50.3 % reduction in CIN2+
Aljunid et al., 2010
Prevalence-based model
12-year-old females Bivalent Malaysia 100% Lifetime Yes, HPV types 31/33/35/39/ 45/51/52/56/ 58, and 59 98% 40.3% reduction in CIN2/3 Capri et al., 2011 Prevalence-based model
The Italian female population
Bivalent Italy 100% Lifetime Yes, HPV
types 31/33/35/39/ 45/51/52/56/ 58, and 59 98% 68.4% reduction in CIN2/3 Bogaards et al., 2011 Individual-based simulation model Women aged 17–25 years in 2010 from the Netherlands Bivalent The Netherlands 50% Lifetime Yes, HPV types 31/33/45/58 100% 43.2% reduction in CIN 2/3 Gomez et al., 2014 Markov model
Women aged 11 years Bivalent and quadrivalent
Chile 95% Lifetime Yes, HPV
types 31/33/35/39/ 45/51/52/56/ 58, and 59
18 4.2 Model results
We observed the overview and discussed the results. Several factors are noteworthy: All of the cost-effectiveness studies adopt a high-vaccine efficacy, with a range between 93% and 100%. In 9 out of 13 studies, cross-protection of the bivalent vaccine is considered. The studies announced that the 10 most commonly seen HPV types that are not targeted by the bivalent vaccine are HPV types 31/33/35/39/45/51/52/56/58, and 59. The most important ones are HPV types 31, 33, and 45, which can be addressed through cross-protection. The models simulate the progression from HPV infection through CIN to cancer; we would expect similar reductions in persistent infections in CIN/cancer predictions. Noticeably, most of the models applied are static models, of which Markov models are an example.
A primary outcome we observed, defined beforehand, is the CIN2/3 outcome and the reduction in CIN. Observing all the CIN reductions together, there is a rage of 37-76%. The mean of all the CIN reductions is 56%
((51.0+ 68.4+37.8+37+64.9+65+66.6+75.9+50.3+40.3+68.4+43.2+60.6)/13=56).
Observing the population, only 2 out of 13 studies mentioned the HPV vaccination in males. All of the other studies examined only women.
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4.3 Cost-effectiveness, herd immunity, and cross-protection
During the review, we examined all articles concerning the ICER and quality-adjusted life year QALYs, in combination with herd immunity and protection. In Model 1, all cross-protection is mentioned. Herd immunity is exclusively mentioned in two articles: the one of Tully et al. (2012) and the one of Boogaards et al. (2011). Following is a brief summary of what is mentioned in both articles.
The model of Tully et al. (2012) included herd immunity effects, cross-protection, and the most recent information on reduced costs for the bivalent vaccine. All of this had significant impact on the predicted costs per QALY gained. In the article, the ICER was €18,633 per QALY gained. In this study, a dynamic model is used to capture herd immunity and cross-protection. Expected significant benefits of herd immunity can be demonstrated at 40% vaccination coverage.
According to Boogaards et al. (2011) , the combined ICER of vaccinating 17- to 25-year-old females is €48,433 per QALY. HPV vaccination will become more attractive when the vaccine price is reduced. The ICER is €22,526 per QALY at a price of €65 per dose, but only €9,572 per QALY at a price of €35 per dose. In the base case, the ICER was €22,526 per QALY gained. This can be considered as marginally cost-effective in the Netherlands. Nonetheless, when cross-protection is included, the ICER becomes €14,734 per QALY. Cross-protection has a positive effect on the cost-effectiveness of the bivalent HPV vaccine. The difference in both ICERs can expressed as:
20 4.4 Long-term efficacy and effectiveness data
In the second search considering the long-term efficacy and effectiveness data, 197 articles were found and 5 more articles were added. These articles were discovered during the first search to model predicted data. As with the cost-effectiveness analysis, this literature search is outlined in a PRISMA flow diagram, presented below in Figure 2. After exclusion of reviews, articles with no CIN outcomes, articles where no bivalent vaccine was used, and exclusion of the articles used in the cost-effectiveness analysis, five studies met the inclusion criteria. In Model 2, an overview of the long-term efficacy and effectiveness data is given with all inputs included in this systematic review are included. The model is presented on the following page.
21 Model 2: Long-term efficacy & effectiveness data
Article Type of study Number of partici-pants Population Case/ exposed Control/non -exposed Follow-up time Confounders adjusted Correctio n confoundi ng Vaccine efficacy Cross-protection Outcome CIN3+ Lehtinen et al., 2012 Randomized Clinical Trial, the Patricia-trial 18,729 Healthy women aged 15–25 years, from 14 countries, and with no more than six lifetime sexual partners Women who received HPV vaccine Women who received hepatitis vaccine
5 years Total sexual lifetime partners No Higher than 90% Yes, HPV types 31/33/45 93.2% reduction in CIN3+ Ryser et al., 2019 Case counts from randomized clinical trials 8,694 in vaccine group and 8,598 in control group Women Vaccinat ed women (at least one dose) Unvaccinate d women 7-8 years High frequency of co-infection Not in bivalent. 90-100% Yes, HPV types 31/33/45 90% reduction in CIN3+ Palmer et al., 2019 Retrospective cohort 138,692 Women screened in Scotland Routinel y vaccinate d women Vaccinated during catch-up program and un- vaccinated women 10 years Subgroups: unvaccinated, vaccinated during catch-up program and routinely vaccinated No Not mentione d No 89% reduction in CIN3+ Egli-Gany et al., 2019 Retrospective and prospective cross-sectional study 768 Women with biopsies in Switzerland
- - 6 years? Women who
has taken biopsies No Not mentione d No 62% reduction in CIN3+ Pollock et al., 2014 Retrospective cohort, preliminary population analysis 106,042 Women born between 1988 and 1992 Vaccinat ed women Unvaccinate d women 3 years Confounded with leaving school Yes, leaving school Not mentione d No 55% reduction in
22 4.4 Results of long-term efficacy & effectiveness data
In this overview, the first two considerations are RCTs and the following three are RWD. There is a difference: The RCTs provide the ideal study design for demonstrating causality between the use of a specific medicine and the effects under optimum circumstances (Makady, de Boer, Hillege, Klungel, & Goettsch, 2017). RWD refers to data that is collected from diversified areas of daily life, which are outside the scope of highly controlled RCTs (Makady et al., 2017). An example of real-world data is an electronic medical record used in hospitals, which includes a wide range of data has already been collected. These real, practical data cannot be obtained through contemporary or traditional clinical trials (Kim et al., 2018).
Observing the model, only two studies—those that use RCTs—make use of
cross-protection. The study of Lehtinen et al. (2012) mentioned that the overall impact of the vaccine in reducing CIN3+ is derived from protection associated with HPV types 16/18 (the vaccine types) and protection against non-vaccine types. This is an example of cross-protection to increase the vaccine efficacy.
All of the RWD studies make use of a retrospective cohort design. These studies were conceived after some people have already developed the outcomes of interest. When observing the
population, it must be noted that all of the studies use only women.
The range in reduction of CIN3+ is between 55% and 93.2%. A closer look reveals the range in RCTs is 90–93.2% and the range in RWD is 55–86%.
The RCT studies are:
1. Lehtinen et al. (2012), a PATRICIA randomized clinical trial 93% reduction in CIN3+
2. Ryser et al. (2019), trail counts
23 The RWD studies are:
1. Palmer et al. (2019) Retrospective cohort study Routinely vaccinated women: 86% reduction in CIN3+
Lower for women first vaccinated at age 17 (catch-up cohort): 46% reduction in CIN 3+ 2. Egli-Gany et al. (2019) Retrospective and prospective cross-sectional study
Quadrivalent and bivalent vaccines cover approximately 62% of CIN3+ lesions. 3. Pollock et al. (2014) Retrospective catch-up cohort study, preliminary population
analysis
Reduction of 55% in relative risk of CIN3+
The reduction in CIN3+ has important significance for the costs and effects of HPV vaccination, which is discussed further in the next paragraph. None of the articles mentioned above address cost-effectiveness or a reduction in costs.
4.5 cross-protection model
To reveal the impact of cross-protection, we construct a model to demonstrate the reduction in CIN3+. In this model, we made the separation between people who receive a bivalent
vaccination and people who receive nothing (no vaccination). The model is illustrated below in model 3.
24 For an example, we establish the following things:
Population: 100.000 people who receive a bivalent HPV vaccination and 100.000 who not receive a vaccination.
10% of the population will get an infection with HPV type 16/18 APA (RIVM, 2019)
Chance for the population to get CIN3+ is 0,0081% (Arbyn, Xu, Simoens & Martin‐Hirsch,
2018).
Vaccination is for 90-100% effective against HPV 16/18 (own study)
Vaccination is for 81-89% effective against HPV type 31-59 (RIVM, 2019)
In the total amount of CIN3+ cases, HPV type 16,18 is responsible for 80% of the CIN3 cases and HPV type 31-59 is for 20% responsible for the CIN3+ cases. This can be due to the incidence of people who receive the virus or due to a lower incidence of people with the virus who receive CIN3+ (Schurink & de Melker, 2017).
For HPV type 31-59 we made the assumption that the incidence to get is the virus is 50% lower and the incidence to get CIN3+ is also 50% lower when people have the virus
(=25%(=50%*50%)) in comparison with HPV type 16 and 18 (20%/80%=25%).
We made some formulas in assistance for calculating the vaccine effectiveness on CIN3+. Calculations:
For people who receive the vaccine, the calculations were a bit difficult because of the range in vaccine efficacy of HPV type 16 and 18. This range was between the 90-100%.
Furthermore, the vaccine efficacy against HPV type 31-59 (31,33,35,39,45,51,52,56,58, and 59) has a range between the 81-89%. The results are illustrated in table 1on the next page.
Calculations:
We start with calculating the amount of people who are possess CIN3+. Population who receive a vaccine:
(1) (100,000 * (0,1*(1-VE))) * 0,0081 = 0-8.1 people VE= vaccine efficacy HPV type 16,18 = 90-100%
25 Population who not receive a vaccine:
(1) (100,000 * 0,1) * 0,0081 = 81
(2) (100,000 * (0,1*50%=0,05)) * (0,0081*50%=0,0046) = 20,25 people
(3) Population who not receive a vaccine: (81+20,25) /100,000= 0,1013%
(3) Population who receive a vaccine is illustrated in the tabel below, in the colom: %vaccination-population with CIN3+.
(4) The outcomes of the effectiveness of the bivalent HPV vaccine, are demonstrated in the last colum of the model below (4).
Vaccine efficacy against HPV 16/18 (90-100%) Vaccine efficacy against HPV31-59 (81-89%) (3) % vaccination-population with CIN3+ (population wo receive vaccine) (4)Effectiveness vaccination total 90% 81% 0,0119% 88,2% 90% 89% 0,0103% 89,8% 100% 81% 0,0038% 96,2% 100% 89% 0,0022% 97,8% 95% 85% 0,0071% 93,0% 94% 89% 0,0071% 93,0% 96% 81% 0,0071% 93,0% 93% 81% 0,0095% 90,6%
26
27
5. Discussion
This paper sought to investigate whether the model-predicted reductions in CIN3+ are in line with long-term efficacy data. However, taken together, the results in reduction of CIN3+ exhibit a wide range. Current models do not fully capture the broad protection provided by the bivalent HPV vaccine as observed in real-world settings and/or clinical trials. The bivalent vaccine revealed up to 90% reductions in CIN3+ in clinical trial and real-world settings. In contrast to these findings, model-predicted reductions in CIN3+ for the bivalent HPV vaccine remain well below 90%, despite incorporation of cross-protection in the models. The range for model-predicted reductions was between 37% and 76%, representing a significant contrast in the efficacy of the bivalent HPV vaccine in the reduction of CIN3+. In comparison to previous research, which revealed that high efficacy (over 90%) against HPV types 16 and 18 was exhibited in bivalent vaccine trials (Skinner et al., 2018).
Regarding the other HPV vaccines, the inequalities between the model-predicted outcomes and the long-term efficacy and effectiveness data appeared only with the bivalent vaccine. The quadrivalent vaccine demonstrated vast overall reductions of CIN3+ in clinical trials, aligned with reductions seen in real-world settings, as, for example, recently in Australia. Modeled findings on CIN3+ for the quadrivalent vaccine were significantly in line with these reductions (Crowe, Pandeya, Brotherton, Dobson, Kisely, Lambert, & Whiteman, 2014). The efficacy of the nonavalent vaccine against HPV infection was recently found to be over 40% better than the quadrivalent vaccine, indicating further reductions in the disease burden. However, long-term trial and real-world data on CIN3+ are not yet available (Guevara et al., 2017).
The difference in the efficacy of the bivalent HPV vaccine can traced to the underestimation of its clinical and economic value through current HPV models. Furthermore, exclusion of herd immunity and cross-protection can cause these differences. In our result section, we illustrate our own model to calculate the overall vaccine effectiveness on CIN3+. In this model,
28
When observing the cost-effectiveness of the bivalent vaccine in the Netherlands, cross-protection and herd immunity cause differences in the approved QALYs. Since the introduction of the HPV vaccination in 2006–2009 in the Netherlands, various cost-effectiveness analyses were performed to demonstrate the effectiveness of the bivalent HPV vaccine. Relative to the willingness-to-pay ratio of €20,000 per QALY, the vaccine was, at that moment, marginally cost-effective. Some costs per QALY were below the willingness-to-pay ratio and some were above the ratio: €19,500 per QALY (Coupé, van Ginkel, de Melker, Snijders, Meijer, & Berkhof, 2009), €24,000 per QALY (Boot, Wallenburg, de Melker, Mangen, Gerritsen, van der Maas, &
Kimman, 2007), and €22,700 per QALY (Rogoza, Westra, Ferko, Tamminga, Drummond, & Daemen, 2009). However, the costs per QALY are different today, due to better understanding of the vaccine’s benefits.
In the first calculations concerning the costs per QALY, herd immunity and cross-protection were not taken into account. Furthermore, the price of the vaccines decreased significantly, from approximately €102 per dose in 2007 to approximately €30 per dose in 2017 (Qendri, Bogaards, & Berkhof, 2019). The inclusion of other HPV-related forms of cancer and cross-protection resulted in an ICER of €5,815 per QALY (Luttjeboer, Westra, Wilschut, Nijman, Daemen, & Postma, 2013). Recent research reveals an ICER of €4,214 when 12-year-old girls are vaccinated, with a vaccination rate of 60%. Herd immunity is taken into account here and, as a result, the cost-effectiveness ratio is favorable (Qendri, Bogaards, & Berkhof 2017). The ICER is
unfavorable only when the vaccination rate is 90%: €36,361 per QALY. The beneficial effect of herd immunity is reduced by a higher vaccination rate among girls (Qendri et al., 2017). In conclusion, herd immunity and cross-protection play important roles in the cost-effectiveness of the bivalent HPV vaccine. Inclusion of herd immunity and cross-protection lead to ICERs below the ceiling ratio of €20,000 per QALY (Westra, Rozenbaum, Rogoza, Nijman, Daemen, Postma, & Wilschut, 2011). We illustrate here what the effect of our study is on the cost-efficacy
Furthermore, in our results section, we spoke about an reduction of the ICER with 34,4% when include cross-protection. According to the study of Luttjeboer et al. (2013) the impact on cancer including cross-protection for non-vaccine types resulted in a 19% reduction of the ICER. These numbers are somewhat in line with each other, however more research is needed
29 Strengths and Limitations
An important strength of this study is the novelty of the literature review, with very few studies having examined the reduction in CIN3+ with long-term efficacy data. However, this study has some limitations, one of which is the scarcity of studies containing long-term efficacy data. This data appeared only in the last couple of years. In comparison with the model predicted studies, the number of studies of the RCTs and RWD were small. However, this study show the clear difference between model predicted outcomes and reductions of CIN3+ in RCTs and RWD. Another limitation is about the comparison with relevant literature concerning our results.
Because of the newness of our study, no comparison can be made (is found) with other literature concerning the main subject of our review, the comparison of the HPV vaccination modeled CIN3+ outcomes with real-world evidence.
Furthermore, long term efficacy data is needed for the nonavalent vaccine for comparative results. The nonavalent vaccine is introducted in 2014, so long-term efficacy and effectiveness data is not yet available. Research can be done in a couple of years. Another idea for future research is concerning the male inclusion of the HPV vaccine. Following the advice of the Health Council, HPV vaccination will also become a part of the Dutch National Immunization Program for males in 2021. In Australia and Denmark, males are already are included in the Immunization Program and receive the vaccine (Dyda, Shah, Surian, Martin, Coiera, Dey, & Dunn, 2019) In our research, only one article from Tully et al. (2012) has taken male vaccination into account. For future research it is important to take more male vaccination into account. This will have an important effect on the effectiveness of the vaccine (Smith, Lew, Walker, Brotherton, Nickson, & Canfell, 2011).
Our study is primary focused on the bivalent HPV vaccine to make a comparison concerning the model predicted outcomes and long-term efficacy and effectiveness data. For future research, a comparison of another HPV-vaccine will possible lead to a better overview of the different outcomes and reductions in CIN3+. For this new research, also long-term efficacy data of the nonavalent vaccine is needed. In the cost-effectiveness model, the reduction of CIN2/3 can be found back and not only the reduction in CIN3+. For better outcomes next time, only the
30
reduction in CIN3+ were untraceable. Additionally, an valuable idea for an follow-up study will be attempting cross-protection and herd immunity implementation in models for the bivalent HPV vaccine. In our own model, only cross-protection is taken into account.
6. Conclusion
In conclusion we can state that the current models are insufficient in providing insight in the clinical benefits of the bivalent HPV vaccine. We want to give an answer on the research
question: “What are the similarities between model-predicted outcomes of CIN3+ and long-term, real-world results of the bivalent HPV vaccination?”. The results on long-term in de reduction of CIN3+ are higher is comparison to the the model predicted reductions. In conclusion can we stead that there are no similarities.
In this research, we better want to capture the >90% vaccine efficacy of the bivalent vaccine within health-economic models. To make well-informed decision with respect to HPV
vaccination improved HTA models are required which captures the broad protection induced by the bivalent HPV vaccine. To better capture the 90% efficacy against CIN3+, herd immunity and cross-protection should be taken into consideration. Most of the models nowadays are static models that not can capture the cross-protection. The purpose of this study is it to improve the predicted models so the outcomes better conform to real-world data. This is important because policy-makers use simulation models in inform health policy decisions concerning the HPV vaccination. Our research demonstrated a better efficacy and effectiveness in the reduction in CIN3+ then was predicted with models.
31
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36
8. Appendixes
8.1 Table: Countries that use the bivalent vaccine
Country Year Age Gender Using bivalent vaccine
yet? The Netherlands Since 2009 in the
public package
Children aged 12/13 years, receive a call in the year they become 13 [1].
In public package for girls, but from 2021 also for boys [1]
YES
Scotland Since September
2008
Routinely offered to all secondary school girls, from age 11 to 12 years [2]
Girls NO
In September 2012, the vaccine was changed from Cervarix to Gardasil (quadrivalent) [2].
England Since 2008 Vaccination routinely
to 12–13 year olds, and offer catch-up vaccination to girls up to 18 years old [3].
Girls NO
In 2012, the UK program changed to use the quadrivalent vaccine (Gardasil) [3].
Brazil In Brazil, the
quadrivalent HPV vaccine was approved in 2006 and the bivalent vaccine in 2008[4].
Girls and Adolescents 11-12 years old
Girls NO
From 2014, the Ministry of Health of Brazil decided to introduce the quadrivalent vaccine and is offered to girls and adolescents 11-12 years old[4]
Luxembourg Since 2008 Nowadays, girls 11-13 years old.
In 2008: targeting 12-17 year old girls offering the choice: bivalent/quadrivalent vaccine[5].
Girls YES
In 2015, the program was changed offering the bivalent vaccine only to 11–13 year old girls[5].
Belgium
(Only the French community)
Since September 2011
37 References of appendix:
1. RIVM (2019) HPV-vaccinatie voor meisjes bij 13 jaar
retrieved from : https://rijksvaccinatieprogramma.nl/vaccinaties/hpv 2. Health protection Scotland (2018) Human papillomavirus (HPV)
retrieved from: https://www.hps.scot.nhs.uk/a-to-z-of-topics/human-papillomavirus/
3. Mesher, D., Panwar, K., Thomas, S. L., Edmundson, C., Choi, Y. H., Beddows, S., & Soldan, K. (2018). The impact of the national HPV vaccination program in England using the bivalent HPV vaccine: surveillance of type-specific HPV in young females, 2010–2016. The Journal of infectious diseases, 218(6), 911-921.
4. Villa, L. (2014, October). HPV vaccines in Brazil and the world. In BMC proceedings (Vol. 8, No. 4, p. O7). BioMed Central.
5. Latsuzbaia, A., Arbyn, M., Weyers, S., & Mossong, J. (2018). Human papillomavirus vaccination coverage in Luxembourg–Implications of lowering and restricting target age groups. Vaccine, 36(18), 2411-2416.
