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. 2022 Apr 19;95(1135):20211274. doi: 10.1259/bjr.20211274

Table 3.

Performance metrics of all models of non-contrast chest CT scans

Model AUC Accuracy (%) Sensitivity (%) Specificity (%) p-value
Training cohort
Radiomics model 0.85 [0.80–0.90] 78% (155/200) [71–83] 81% (81/100) [72–88] 74% (74/100) [64–82] N/A
CT attenuation model 0.63 [0.55–0.71] 61% (122/200) [54–68] 54% (54/100) [44–64] 68% (68/100) [58–77] <0.001
Nested model (EAT-score+CT attenuation) 0.86 [0.81–0.91] 80% (159/200) [73–85] 77% (77/100) [67–85] 82% (82/100) [73–89] 0.41
Test cohort
Radiomics model 0.85 [0.77–0.92] 77% (77/100) [68–85] 70% (35/50) [55–82] 84% (42/50) [70–92] N/A
CT attenuation model 0.63 [0.52–0.74] 51% (51/100) [41–61] 88% (44/50) [75–95] 14% (7/50) 6–27 <0.001
Nested model (EAT-score+CT attenuation) 0.83 [0.74–0.91] 76% (76/100) [66–84] 68% (34/50) [53–80] 84% (42/50) [70–92] 0.10

AUC, area under the receiver operating characteristic curve; EAT, epicardial adipose tissue.

Data in the brackets are 95% confidence interval and data in the parentheses are the numerator and denominator for percentages. The p-value represents significance of AUC between the radiomics model and each of other models.