Fig 1.
Flow diagram of study selection in logistic and meta-regression models.
Table 1.
Descriptive statistics on sample of incremental cost-effectiveness ratios (ICERS) and articles reported in Tufts registries on human papillomavirus vaccines.
Fig 2.
Model fit for three independent variables that explain true variation across ICERs: (A) vaccine cost, (B) cervical cancer burden, and (C) GDP per capita. Results for vaccine cost (A) are reported by GDP per capita quartile, and results for burden of cervical cancer (B) and GDP per capita (C) are reported by vaccine cost quartile, after controlling for all other method and intervention-level characteristic model covariates. The X- and Y-axes are in log-space. The grey band indicates the total uncertainty (fixed and random effects) for the mean/median burden value for GDP per capita in (A) and of vaccine cost in (B) and (C). ICER = incremental cost-effectiveness ratio; DALY = disability-adjusted-life-year; GDP = gross domestic product per capita in 2017 US$.
Table 2.
Predicted cost-effectiveness ratios by country adjusted for cost-saving probabilities.
Fig 3.
(A) Predicted ICERs from the meta-regression analysis by country in 2017 US$ per DALY averted, and (B) predicted ICERs relative to four categories of GDP per capita: <0.5, 0.5 to 0.9, 1.0 to 3.0, and >3.0 times GDP per capita. Results for (B) incorporate the ICER uncertainty intervals such that the upper bound of the uncertainty interval (97.5th percentile) must be within the categories. UI = uncertainty interval; ICER = incremental cost-effectiveness ratio; DALY = disability-adjusted-life-year; GDP = gross domestic product per capita in 2017 US$.
Table 3.
Predicted incremental cost-effectiveness ratios aggregated to super-region level and compared to range of input data from Tufts registry dataset and additional extractions.