Coronary artery disease (CAD), as the leading cause of death, poses a huge economic burden on health-care systems. We used a multi-marker approach to explore discriminative abilities of several lipid, inflammatory, and oxidative stress/antioxidative defense markers as CAD predictors. We assessed their cost-effectiveness compared with the Framingham risk score (FRS).
Using a decision model, we evaluated the costs, accuracy, and cost-effectiveness of each model. The FRS was used as the baseline model. Other models were formed with the consecutive addition of selected markers: apolipoprotein A-I (apoA-I), apolipoprotein B (apoB), apolipoprotein (a) [apo(a)] isoform, lipoprotein (a), high-sensitivity C-reactive protein, malondialdehyde, superoxide dismutase (SOD), sulfhydryl, and superoxide anion (O ). A best-case model was formed from a combination of diagnostic markers to yield the best patient stratification algorithm. All models were assessed by their predictive probabilities using receiver operating characteristic curves. To accomplish our goals, we recruited 188 CAD patients (verified by coronary angiography) and 197 asymptomatic CAD-free subjects for comparison. The analysis was performed from a third-party payer perspective.
Only two strategies had outstanding discriminative abilities: the best-case model (FRS, SOD, and O ) and FRS plus SOD with area under the curve (AUC) values of 0.924 and 0.906, respectively. The cost-effectiveness ratio varied between €593 per AUC for the baseline model to €2425 per AUC for FRS plus apo(a) isoform. Strategies involving oxidative stress/antioxidative defense markers were more cost-effective than strategies involving lipid or inflammatory markers. All results were robust.
Our results support the feasibility of a multimarker approach for CAD screening. The introduction of oxidative stress/antioxidative defense markers in the clinical laboratory would be convenient and cost-effective.