Abstract
Cost-effectiveness analysis (CEA) is a well-known, but resource intensive, method for comparing the costs and health outcomes of health interventions. To build on available evidence, researchers are developing methods to transfer CEA across settings; previous methods do not use all available results nor quantify differences across settings. We conducted a meta-regression analysis of published CEAs of human papillomavirus (HPV) vaccination to quantify the effects of factors at the country, intervention, and method-level, and predict incremental cost-effectiveness ratios (ICERs) for HPV vaccination in 195 countries. We used 613 ICERs reported in 75 studies from the Tufts University's Cost-Effectiveness Analysis (CEA) Registry and the Global Health CEA Registry, and extracted an additional 1,215 one-way sensitivity analyses. A five-stage, mixed-effects meta-regression framework was used to predict country-specific ICERs. The probability that HPV vaccination is cost-saving in each country was predicted using a logistic regression model. Covariates for both models included methods and intervention characteristics, and each country's cervical cancer burden and gross domestic product per capita. ICERs are positively related to vaccine cost, and negatively related to cervical cancer burden. The mean predicted ICER for HPV vaccination is 2017 US$4,217 per DALY averted (95% uncertainty interval (UI): US$773-13,448) globally, and below US$800 per DALY averted in 64 countries. Predicted ICERs are lowest in Sub-Saharan Africa and South Asia, with a population-weighted mean ICER across 46 countries of US$706 per DALY averted (95% UI: $130-2,245), and across five countries of US$489 per DALY averted (95% UI: $90-1,557), respectively. Meta-regression analyses can be conducted on CEA, where one-way sensitivity analyses are used to quantify the effects of factors at the intervention and method-level. Building on all published results, our predictions support introducing and expanding HPV vaccination, especially in countries that are eligible for subsidized vaccines from GAVI, the Vaccine Alliance, and Pan American Health Organization.
Highlights
Cost-effectiveness analysis (CEA) is a well-known method for comparing the costs and health outcomes of individual products or services to a standard of care, often in the context of a clinical trial
Beginning with the meta-regression results, we focus on three independent variables that explain true variation across incremental cost-effectiveness ratios (ICERs): vaccine cost, burden of cervical cancer, and gross domestic product (GDP) per capita (Fig 2)
Our findings show that the adjusted mean ICER for Human papillomavirus (HPV) vaccination is 2017 United States dollars (US$)4,217 per disability-adjusted life years (DALYs) averted (95% uncertainty interval (UI): US$773–13,448) globally, and below US$800 per DALY averted for 64 countries
Summary
Cost-effectiveness analysis (CEA) is a well-known method for comparing the costs and health outcomes of individual products or services to a standard of care, often in the context of a clinical trial. Goeree et al summarized the factors that researchers have proposed to assess whether or not the results of a specific CEA or other economic evaluation could be transferred [1]. Among the examples they surveyed in high-income countries, most CEA results could not be transferred. The results from one of seven economic evaluations could be transferred These approaches can guide the decision to accept or reject the results of a specific CEA, they do not use all available information nor quantify differences across settings by methods, intervention characteristics, and country setting
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