Cost–Effectiveness of Angiotensin-converting Enzyme Inhibitors in Nondiabetic Advanced Renal Disease

Charles Christian Adarkwah; Afschin Gandjour


Expert Rev Pharmacoeconomics Outcomes Res. 2011;11(2):215-223. 

In This Article

Sensitivity Analysis

To address uncertainty around mean incremental costs and effectiveness, we conducted univariate sensitivity analyses, where we varied one variable at a time while keeping all other variables constant at their mean or base-case value. We ran analyses using the upper and lower limit of the 95% confidence intervals (CIs) of the mean. For transplantation costs, we did not have information on the 95% CI and thus varied costs by 20% (see Table 2 for uncertainty ranges).

In order to assess how a simultaneous change of several variables affects the incremental cost–effectiveness ratio, we performed a Monte Carlo simulation, a type of multivariate sensitivity analysis. This technique runs a large number of simulations (in this case 1000) by repeatedly drawing samples from probability distributions of input variables. Thus, it provides a probability distribution for the output variables (incremental costs, incremental effectiveness and incremental cost–effectiveness ratios). Probabilities were assumed to follow a β distribution β(α, β) because they are normally distributed but restricted to take on values between 0 and 1. The standard error of a probability or proportion was calculated according to the following formula:[32]

where p = probability and n = sample size. Cost data were assumed to follow a γ distribution γ(a, b), which reflects the long right tail and restriction to positive values. Relative risks and odds ratios were assumed to follow a lognormal distribution.

Based on the Monte Carlo simulation, we generated a cost–effectiveness acceptability curve. A cost–effectiveness acceptability curve allows a decision-maker to consider whether a prevention strategy is cost effective in relation to the maximum amount a decision-maker is willing to pay for a QALY. At each willingness-to-pay threshold, the cost–effectiveness acceptability curve shows the probability that treatment is cost effective.


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