Validation and comparison of four models to calculate pretest probability of obstructive coronary artery disease in a Chinese population: A coronary computed tomographic angiography study.

Objective: We sought to compare the performance of the updated Diamond-Forrester method (UDFM), Duke clinical score (DCS), Genders clinical model (GCM) and Genders extended model (GEM) in a Chinese population referred to coronary computed tomography angiography (coronary CTA).

Background: The reliability of existing models to calculate the pretest proability (PTP) of obstructive coronary artery disease (CAD) have not been fully investigated, especially in a Chinese population.

Methods: We identified 5743 consecutive patients with suspected stable CAD who underwent coronary calcium scoring (CCS) and coronary CCTA. Obstructive CAD was defined as with the presence of ≥50% diameter stenosis in coronary CTA or unassessable segments due to severe calcification. Area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), net reclassification improvement (NRI) and Hosmer-Lemeshow goodness-of-fit statistic (H-L χ) were assessed to validate and compare these models.

Results: Overall, 1872 (32%) patients had obstructive CAD and 2467 (43%) had a CCS of 0. GEM demonstrated improved discrimination over the other models through the largest AUC (0.816 for GEM, 0.774 for GCM, 0.772 for DCS and 0.765 for UDFM). UDFM (-0.3255, p < 0.0001), DCS (-0.3149, p < 0.0001) and GCM (-0.2264, p < 0.0001) showed negative IDI compared to GEM. The NRI was significantly higher for GEM than the other models (0.7152, p < 0.0001, 0.5595, p < 0.0001 and 0.3195, p < 0.0001, respectively). All of the four models overestimated the prevalence of obstructive CAD, with unsatisfactory (p < 0.01 for all) calibration for UDFM (H-L χ = 137.82), DCS (H-L χ = 156.70), GCM (H-L χ = 51.17) and GEM (H-L χ = 29.67), respectively.

Conclusion: Although GEM was superior for calculating PTP in a Chinese population referred for coronary CTA, developing new models allowing for more accurate and operational estimation are warranted.