Comparison of the Diamond-Forrester method and Duke Clinical Score to predict obstructive coronary artery disease by computed tomographic angiography.

We sought to evaluate the ability of the Diamond and Forrester method (DFM) and the Duke Clinical Score (DCS) to predict obstructive coronary artery disease (CAD) on coronary computed tomographic angiography (CCTA) and the effect of these different risk scores on the appropriateness level using the 2010 Appropriate Use Criteria. Consecutive symptomatic patients who underwent CCTA for evaluation of CAD (n = 114) were classified as having a low, intermediate, or high pretest probability using the DFM and DCS. Using the Appropriate Use Criteria, the indications for CCTA were classified according to the pretest probability and previous testing. The CCTA results were classified as revealing obstructive (≥70% stenosis), nonobstructive (<70%), or no CAD. When the patients' risk was classified using the DFM, 18% were low, 65% intermediate, and 17% high risk. When using the DCS, 53% of patients had a reclassification of their risk, most of whom changed from intermediate to either low or high risk (50% low, 19% intermediate, 35% high risk). The net reclassification improvement for the prediction of obstructive CAD was 51% (p = 0.01). Of the 37 patients who were reclassified as low risk, 36 (97%) lacked obstructive CAD. Appropriateness for CCTA was reclassified for 13% of patients when using the DCS instead of the DFM, and the number of appropriate examinations was significantly fewer (68% vs 55%, p <0.001). In conclusion, reclassification of risk using the DCS instead of the DFM resulted in improved prediction of obstructive CAD on CCTA, especially in low-risk patients. More patients were categorized as having a high pretest probability of CAD, resulting in reclassification of their examination indications as uncertain or inappropriate. These results identify the need for improved pretest risk scores for noninvasive tests such as CCTA and suggest that the method of risk assessment could have important implications for patient selection and quality assurance programs.