Cost-effectiveness of strategies in different scenarios.

1Input data regarding effectiveness within scenarios taken from Table 1.2Calculated to highest ranked strategy. Negative values indicate additional costs per effectiveness loss; positive values indicate additional costs per effectiveness gain. Strategies were either dominated (d) or undominated (u) by the first-ranked strategy.3Base-case: 20-year-old-patient with 58.25 years to live [19]; replacement of 80% of removed teeth assumed [26]; 3% discounting rate [18], triangular distribution of probabilities between 95% CI assumed.4Best-case: Highest evidence-based effectiveness of micro-invasive treatment assumed.5Worst-case: Lowest evidence-based effectiveness of micro-invasive treatment assumed.6Years to live: 63.5 [19].7Years to live: 39.0 [19].Mean costs (c, €) and effectiveness (e, % of unrestored lesions), ranking of strategies as well as incremental cost-effectiveness ratios (ICERs) were calculated. Ranking was performed according to costs (strategies with higher costs were ranked lower). Cost-effectiveness analyses were performed separately for lesions of different stages (E2 or D1). Besides the base-case analysis, we performed best- and worst-case sensitivity analyses to explore effects of uncertainty resulting from current evidence. Within these analyses, we varied the transition probabilities of micro-invasively treated lesions based on the 95% CI of calculated Risk Ratios of our meta-analysis. We additionally explored the effects of the patient’s age as well as used discount rates and applied distribution of probabilities for random sampling on the cost-effectiveness estimates.