Probabilistic sensitivity analysis incorporating the bootstrap: An examplecomparing treatments for the eradication of Helicobacter pylori

Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Variou s types of sensitivity analysis are used to evaluate the uncertainty inhere nt in the models. Although probabilistic sensitivity analysis is more diffi cult theoretically and computationally, the results can be much more powerf ul and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to per form a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiv eness of Helicobacter pylori eradication. The necessary steps are straightf orward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model be yond the traditional base-case and deterministic sensitivity analyses and s hould become the standard method for assessing sensitivity.