COMPARISON OF COST-EFFECTIVENESS AND UTILITY OF EXERCISE ECG, SINGLE-PHOTON EMISSION COMPUTED-TOMOGRAPHY, POSITRON EMISSION TOMOGRAPHY, ANDCORONARY ANGIOGRAPHY FOR DIAGNOSIS OF CORONARY-ARTERY DISEASE

Background To compare cost-effectiveness and utility of four clinical algorithms to diagnose obstructive coronary atherosclerotic heart dise ase (CAD), we compared exercise ECG (ExECG), stress single photon emis sion computed tomography (SPECT), positron emission tomography (PET), and coronary angiography. Methods and Results Published data and a str aightforward mathematical model based on Bayes' theorem were used to c ompare strategies. Effectiveness was defined as the number of patients with diagnosed CAD, and utility was defined as the clinical outcome, ie, the number of quality-adjusted life years (QALY) extended by thera py after the diagnosis of CAD. Our model used published values for cos ts, accuracy, and complication rates of tests. Analysis of the model i ndicates the following results. (1) The direct cost (fee) for each tes t differs considerably from total cost per Delta QALY. (2) As pretest likelihood of CAD (pCAD) in the population increases, there is a linea r increase in cost per patient tested but a hyperbolic decrease in cos t per effect and cost per utility unit, ie, increased cost-effectivene ss and decreased cost per utility unit. (3) At pCAD<0.70, analysis of the model indicates that stress PET is the most cost-effective test, w ith the lowest cost per utility, followed by SPECT, ExECG, and angiogr aphy, in that order. (4) Above a threshold value of pCAD of 0.70 (for example, middle-aged men with typical angi na), proceeding directly to angiography as the first test showed the lowest cost per effect or ut ility. This quantitative model has the advantage of estimating a thres hold value of pCAD (0.70) at which the rank order of cost-effectivenes s and cost per utility unit change. The model also allows substitution of different values for any variable as a way to account for the unce rtainties of clinical data, ie, changing costs, test accuracy and risk , etc. This procedure, called sensitivity analysis, showed that the ra nk order of cost-effectiveness did not change despite changes in sever al variables. Conclusions (1) Estimation of total costs of diagnostic tests for CAD requires consideration not only of the direct cost of th e test per se (eg, test fees) but also of the indirect and induced cos ts of management algorithms based on the test leg, cost/Delta QALY). ( 2) It is essential to consider the clinical history (pCAD) when select ing the clinical algorithm to make a diagnosis with the lowest cost pe r effect or cost per utility unit. (3) Stress PET shows the lowest cos t per effect or cost per utility unit in patients with pCAD<0.70. (4) Angiography shows the lowest cost per effect or cost per utility unit in patients with pCAD>0.70.