American Journal of Epidemiology Advance Access originally published online on February 1, 2007
American Journal of Epidemiology 2007 165(7):762-775; doi:10.1093/aje/kwk059
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ORIGINAL CONTRIBUTIONS |
Modeling Human Papillomavirus Vaccine Effectiveness: Quantifying the Impact of Parameter Uncertainty
1 Department of Social and Preventive Medicine, Laval University, Quebec, Canada
2 Health Economics and Outcomes Research, Merck Frosst Canada Ltd., Montreal, Canada
3 Department of Infectious Disease Epidemiology, Imperial College, London, United Kingdom
Reprint requests to Dr. Marc Brisson, Unité de recherche en santé des populations, Centre hospitalier affilié universitaire de Québec, Hôpital Saint-Sacrement, 1050 Chemin Sainte-Foy, Québec, Québec, Canada G1S 4L8 (e-mail: marc.brisson{at}uresp.ulaval.ca).
Received for publication June 7, 2006. Accepted for publication September 15, 2006.
The development of models is based on assumptions, which inevitably embed a level of uncertainty. Quantifying such uncertainty is particularly important when modeling human papillomavirus (HPV) vaccine effectiveness; the natural history of infection and disease is complex, and age- and type-specific data remain scarce and incomplete. The aim of this study was to predict the impact of HPV-6/11/16/18 vaccination, using a cohort model and measuring parameter uncertainty. An extensive fitting procedure was conducted, which identified 164 posterior parameter combinations (out of 200,000 prior parameter sets) that fit simultaneously HPV type-specific incidence and prevalence data for infection, cervical intraepithelial neoplasia (CIN), and squamous cell carcinoma (SCC). Results based on these posterior parameter sets suggest that vaccinating girls aged 12 years (vaccine efficacy = 95%, no waning) would reduce their lifetime risk of HPV infection, CIN1, CIN2/3, and SCC by 21% (80% credibility interval: 17, 29), 24% (80% credibility interval: 17, 31), 49% (80% credibility interval: 36, 60), and 61% (80% credibility interval: 47, 73), respectively. If vaccine efficacy is reduced or vaccine protection is assumed to wane, uncertainty surrounding predictions widens considerably. Important priorities for future research are to understand the role of natural immunity and to measure the duration of vaccine protection because results were most sensitive to these parameters.
cancer vaccines; computer simulation; models, theoretical; papillomavirus infections; papillomavirus vaccines; uncertainty; uterine cervical neoplasms; vaccination
Abbreviations: CIN, cervical intraepithelial neoplasia; HPV, human papillomavirus; HR, other high oncogenic risk types; SCC, squamous cell carcinoma
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