• J Cardiovasc Comput Tomogr · Jul 2017

    Comparative Study Observational Study

    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.

    • Jia Zhou, Yujie Liu, Lingyu Huang, Yahang Tan, Xingchen Li, Hong Zhang, Yanhe Ma, and Ying Zhang.
    • Department of Cardiology, Tianjin Chest Hospital, Tianjin, China.
    • J Cardiovasc Comput Tomogr. 2017 Jul 1; 11 (4): 317-323.

    ObjectiveWe 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).BackgroundThe 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.MethodsWe 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 χ2) were assessed to validate and compare these models.ResultsOverall, 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 χ2 = 137.82), DCS (H-L χ2 = 156.70), GCM (H-L χ2 = 51.17) and GEM (H-L χ2 = 29.67), respectively.ConclusionAlthough 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.Copyright © 2017 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

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