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Copyright ©The Author(s) 2021.
World J Gastroenterol. Sep 7, 2021; 27(33): 5536-5554
Published online Sep 7, 2021. doi: 10.3748/wjg.v27.i33.5536
Table 5 Algorithmic approaches using the combination of serologic and clinical parameters for hepatocellular carcinoma risk prediction
Risk scores
Cohort: Patients/ratio of cirrhosis
Study population
Variables
External validation
GALAD score (Johnson et al[72], 2014)HCC case: 670/90%; CLD control: 339/97%Caucasian (England)AFP; AFP-L3; DCPAsian, Caucasian
Doylestown algorithm (Wang et al[76], 2016)Training HCC case: 165/100%; CLD control: 195/100%; Validation 1 HCC case: 432/100%; CLD control: 438/100%; Validation 2 HCC case: 113/100%; CLD control: 586/100%; Validation 3 HCC case: 425/100%; CLD control: 804/100%North America (United States)Age; Gender; ALT; ALP; AFP; Fucosylated kininogenNorth America (United States)
GALADUS score (Yang et al[75], 2019)Training HCC case: 111/98%; CLD control: 180/85%; Validation HCC case: 233/100%; CLD control: 412/100%North America (United States)AFP; AFP-L3; DCP; UltrasonographyNorth America (United States)
HES algorithm (Tayob et al[78,79], 2019)HCC case: 4804/100%; CLD control: 33627/100%North American (United States Veterans Administration)Age; Rate of AFP change; ALT; Platelet count; Etiology of cirrhosis-