Affiliation:
1. Department of Internal Medicine College of Medicine Kyung Hee University Hospital Kyung Hee University Seoul Republic of Korea
2. Department of Biostatistics Korea University Seoul Republic of Korea
3. Health Screening and Promotion Center Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea
4. Department of Gastroenterology Liver Center Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea
Abstract
AbstractBackground & AimsAlthough non‐alcoholic fatty liver disease (NAFLD) is becoming a leading cause of hepatocellular carcinoma (HCC), HCC risk in non‐cirrhotic NAFLD received little attention. We aimed to develop and validate an HCC risk prediction model for non‐cirrhotic NAFLD.MethodsA nationwide cohort of non‐cirrhotic NAFLD patients in Korea was recruited to develop a risk prediction model and validate it internally (n = 409 088). A model using a simplified point system was developed by Cox proportional hazard model. K‐fold cross‐validation assessed the accuracy, discrimination and calibration. The model was validated externally using a hospital cohort from Asan Medical Center (n = 8721).ResultsAn 11‐point HCC risk prediction model for non‐cirrhotic NAFLD was developed using six independent factors of age, sex, diabetes, obesity, serum alanine aminotransferase level and gamma‐glutamyl transferase level (c‐index 0.75). The average area under receiver operating curves (AUROCs) of the model was 0.72 at 5 years and 0.75 at 10 years. In the external validation cohort, the AUROCs were 0.79 [95% confidence interval [CI], 0.59–0.95] at 5 years and 0.84 (95% CI, 0.73–0.94) at 10 years. The calibration plots showed the expected risks corresponded well with the observed risks. Risk stratification categorized patients into the low (score 0–6), moderate (7, 8) and high (9–11; estimated incidence rate >0.2%/year) risk groups.ConclusionsA novel HCC risk prediction model for non‐cirrhotic NAFLD patients was developed and validated with fair performance. The model is expected to serve as a simple and reliable tool to assess HCC risk and assist precision screening of HCC.