CONFIDENCE-INTERVALS FOR COST-EFFECTIVENESS RATIOS - A COMPARISON OF 4 METHODS

We evaluated four methods for computing confidence intervals for cost- effectiveness ratios developed from randomized controlled trials: the box method, the Taylor series method, the nonparametric bootstrap meth od and the Fieller theorem method. We performed a Monte Carlo experime nt to compare these methods. We investigated the relative performance of each method and assessed whether or not it was affected by differin g distributions of costs (normal and log normal) and effects (10% abso lute difference in mortality resulting from mortality rates of 25% ver sus 15% in the two groups as well as from mortality rates of 55% versu s 45%) or by differing levels of correlation between the costs and eff ects (correlations of -0.50, -0.25, 0.0, 0.25 and 0.50). The principal criterion used to evaluate the performance of the methods was the pro bability of miscoverage. Symmetrical miscoverage of the intervals was used as a secondary criterion for evaluating the four methods. Overall probabilities of miscoverage for the nonparametric bootstrap method a nd the Fieller theorem method were more accurate than those for the ot her the methods. The Taylor series method had confidence intervals tha t asymmetrically underestimated the upper limit of the interval. Confi dence intervals for cost-effectiveness ratios resulting from the nonpa rametric bootstrap method and the Fieller theorem method were more dep endably accurate than those estimated using the Taylor series or box m ethods. Routine reporting of these intervals will allow individuals us ing cost-effectiveness ratios to make clinical and policy judgments to better identify when an intervention is a good value for its cost. (C ) 1997 by John Wiley & Sons, Ltd.