Estimating Progression Rates for Human Papillomavirus Infection From Epidemiological Data

Mark Jit, Nigel Gay, Kate Soldan, Yoon Hong Choi and William John Edmunds
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Mark Jit: Modelling and Economics Unit, Health Protection Agency Centre for Infections, London, United Kingdom, mark.jit@hpa.org.uk, Immunisation Department, Health Protection Agency Centre for Infections, London, United Kingdom
Nigel Gay: Modelling and Economics Unit, Health Protection Agency Centre for Infections, London, United Kingdom
Kate Soldan: the HIV/STI Department Health Protection Agency Centre for Infections, London, United Kingdom
Yoon Hong Choi: Modelling and Economics Unit, Health Protection Agency Centre for Infections, London, United Kingdom, Immunisation Department, Health Protection Agency Centre for Infections, London, United Kingdom
William John Edmunds: Modelling and Economics Unit, Health Protection Agency Centre for Infections, London, United Kingdom

Medical Decision Making, 2010, vol. 30, issue 1, 84-98

Abstract: A Markov model was constructed in order to estimate typespecific rates of cervical lesion progression and regression in women with high-risk human papillomavirus (HPV). The model was fitted to age- and type-specific data regarding the HPV DNA and cytological status of women undergoing cervical screening in a recent screening trial, as well as cervical cancer incidence. It incorporates different assumptions about the way lesions regress, the accuracy of cytological screening, the specificity of HPV DNA testing, and the age-specific prevalence of HPV infection. Combinations of assumptions generate 162 scenarios for squamous cell carcinomas and 54 scenarios for adenocarcinomas. Simulating an unscreened cohort of women infected with high-risk HPV indicates that the probability of an infection continuing to persist and to develop into invasive cancer depends on the length of time it has already persisted. The scenarios and parameter sets that produce the best fit to available epidemiological data provide a basis for modeling the natural history of HPV infection and disease.

Keywords: cervical intraepithelial neoplasms; mathematical model; Markov process; papillomavirus infections; uncertainty. (Med Decis Making 2010; 30:84—98) (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:30:y:2010:i:1:p:84-98

DOI: 10.1177/0272989X09336140

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