Potential overestimation of HPV vaccine impact due to unmasking of non-vaccine types: Quantification using a multi-type mathematical model

Yoon Hong Choi; Ruth Chapman; Nigel Gay; Mark Jit

doi:10.1016/j.vaccine.2012.03.065

Potential overestimation of HPV vaccine impact due to unmasking of non-vaccine types: Quantification using a multi-type mathematical model

Yoon Hong Choi^*, Ruth Chapman, Nigel Gay, Mark Jit

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

19 Citations (Scopus)

Abstract

Introduction: Estimates of human papillomavirus (HPV) vaccine impact in clinical trials and modelling studies rely on DNA tests of cytology or biopsy specimens to determine the HPV type responsible for a cervical lesion. DNA of several oncogenic HPV types may be detectable in a specimen. However, only one type may be responsible for a particular cervical lesion. Misattribution of the causal HPV type for a particular abnormality may give rise to an apparent increase in disease due to non-vaccine HPV types following vaccination (" unmasking" ). Methods: To investigate the existence and magnitude of unmasking, we analysed data from residual cytology and biopsy specimens in English women aged 20-64 years old using a stochastic type-specific individual-based model of HPV infection, progression and disease. The model parameters were calibrated to data on the prevalence of HPV DNA and cytological lesion of different grades, and used to assign causal HPV types to cervical lesions. The difference between the prevalence of all disease due to non-vaccine HPV types, and disease due to non-vaccine HPV types in the absence of vaccine HPV types, was then estimated. Results: There could be an apparent maximum increase of 3-10% in long-term cervical cancer incidence due to non-vaccine HPV types following vaccination. Conclusion: Unmasking may be an important phenomenon in HPV post-vaccination epidemiology, in the same way that has been observed following pneumococcal conjugate vaccination.

Original language	English
Pages (from-to)	3383-3388
Number of pages	6
Journal	Vaccine
Volume	30
Issue number	23
DOIs	https://doi.org/10.1016/j.vaccine.2012.03.065
Publication status	Published - 14 May 2012

Bibliographical note

Funding Information:
RC was funded by a grant from the Department of Health, England (grant reference number DOH 039/0031 ). The authors’ work was independent of the funders, who had no role in the study design, analysis of data, writing of the manuscript or decision to submit for publication.

Funding Information:
We thank Henry Kitchener and the English HPV Typing Study Group for data from the English HPV typing study (funded by the NHS Cervical Screening Programme), Andrew Cox and Stefan Flasche for their assistance in generating the figures in this paper; and Simon Beddows for helpful discussions around HPV typing.

Keywords

Human papillomavirus
Individual based model
Mathematical model
Unmasking
Vaccine

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.vaccine.2012.03.065

Cite this

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title = "Potential overestimation of HPV vaccine impact due to unmasking of non-vaccine types: Quantification using a multi-type mathematical model",

abstract = "Introduction: Estimates of human papillomavirus (HPV) vaccine impact in clinical trials and modelling studies rely on DNA tests of cytology or biopsy specimens to determine the HPV type responsible for a cervical lesion. DNA of several oncogenic HPV types may be detectable in a specimen. However, only one type may be responsible for a particular cervical lesion. Misattribution of the causal HPV type for a particular abnormality may give rise to an apparent increase in disease due to non-vaccine HPV types following vaccination ({"} unmasking{"} ). Methods: To investigate the existence and magnitude of unmasking, we analysed data from residual cytology and biopsy specimens in English women aged 20-64 years old using a stochastic type-specific individual-based model of HPV infection, progression and disease. The model parameters were calibrated to data on the prevalence of HPV DNA and cytological lesion of different grades, and used to assign causal HPV types to cervical lesions. The difference between the prevalence of all disease due to non-vaccine HPV types, and disease due to non-vaccine HPV types in the absence of vaccine HPV types, was then estimated. Results: There could be an apparent maximum increase of 3-10% in long-term cervical cancer incidence due to non-vaccine HPV types following vaccination. Conclusion: Unmasking may be an important phenomenon in HPV post-vaccination epidemiology, in the same way that has been observed following pneumococcal conjugate vaccination.",

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author = "Choi, {Yoon Hong} and Ruth Chapman and Nigel Gay and Mark Jit",

note = "Funding Information: RC was funded by a grant from the Department of Health, England (grant reference number DOH 039/0031 ). The authors{\textquoteright} work was independent of the funders, who had no role in the study design, analysis of data, writing of the manuscript or decision to submit for publication. Funding Information: We thank Henry Kitchener and the English HPV Typing Study Group for data from the English HPV typing study (funded by the NHS Cervical Screening Programme), Andrew Cox and Stefan Flasche for their assistance in generating the figures in this paper; and Simon Beddows for helpful discussions around HPV typing. ",

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AU - Jit, Mark

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Potential overestimation of HPV vaccine impact due to unmasking of non-vaccine types: Quantification using a multi-type mathematical model

Abstract

Bibliographical note

Keywords

UN SDGs

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