Analysing clinical decision analyses

We present a critical review of aspects of clinical decision analysis which uses an application to screening for familial intracranial aneurysms. The analysis is reported together with methods for assessing decision trees. These methods appear to be powerful checks on the usually rather intuitive way in which decision trees are built. The problem of assessing the uncertainty in the results of a decision analysis is discussed in detail. In practice, sensitivity analysis covers nearly every calculation apart from the standard evaluation of the decision tree. Different forms of sensitivity analysis are distinguished and given appropriate names: influence analysis, threshold analysis, full Bayesian analysis, Bayesian influence analysis, attribute analysis, generalization analysis and scenario analysis. The biostatistical community may well contribute to the much needed methodological improvement in decision analysis and its different forms of sensitivity analysis, especially if prepared to look beyond the standard statistical techniques.