CORE model outperforms FIB-4 in predicting liver-related outcomes

A novel risk score, named Cirrhosis Outcome Risk Estimator (CORE), performs better than FIB-4 in predicting liver-related outcomes in the general population, a study has shown. This model is based on a flexible modelling approach and utilizes biomarkers that are easily accessible in primary care.

“The CORE model outperformed the currently recommended first line test FIB-4 when predicting future major adverse liver outcomes (MALO), both in the training data and in external validation,” the researchers said.

MALO refers to the composite outcome of compensated and decompensated cirrhosis, hepatocellular carcinoma, liver transplant, and liver-related mortality.

This population-based cohort study was conducted in Sweden and validated in Finland and the UK. A total of 480,651 individuals with no known history of liver disease and blood tests taken in primary care or at occupational healthcare screening were included in the model development phase. Validation involved two cohorts with 24,191 and 449,806 individuals with no liver disease history, respectively.

Flexible parametric survival models and easily available laboratory-based biomarkers were used to develop the new risk score. The CORE model included age, sex, aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl transferase.

The researchers assessed the new model’s performance through discrimination, calibration, and clinical utility. They also conducted external validation using data from the UK Biobank and the FINRISK and Health 2000 cohorts and compared CORE with the FIB-4 score.

A total of 7,168 MALO events occurred during a median follow-up of 28 years. The 10-year incidence risk of MALO was 0.27 percent. The CORE model achieved a significantly higher 10-year area under the curve than FIB-4 (88 percent, 95 percent confidence interval [CI], 87‒89 vs 79 percent, 95 percent CI, 78‒80). [BMJ 2025;390:e083182]

“The calibration of CORE was good in all three cohorts, and according to the decision curve analysis CORE provides a higher net benefit than FIB-4 for all risk thresholds,” the researchers said.

Risk scores

Other risk scores (ie, LiverRisk, SAFE, and MAF-5 scores) were developed to detect the different stages of fibrosis in a general population or primary care setting, but these may be used for prediction purposes as well. [Lancet 2023;402:988-996; Hepatology 2023;77:256-267; Gastroenterology 2024;167:357-367.e9]

“We could not compare CORE directly with these scores owing to data availability (globulin for SAFE and waist circumference for MAF-5 not being available in AMORIS) and the formula for LiverRisk not being publicly available,” the researchers said.

“However, CORE may have benefits over these models as the included parameters are few and inexpensive, are readily available, and do not require other time-consuming tasks such as measuring waist circumference,” they added.

Further studies are warranted to compare the predictive performance of CORE with the other risk scores available, according to the researchers.

Of note, an earlier study used the AMORIS cohort to assess the discrimination of several scores (FIB-5, NFS, APRI, BARD, Forns) in predicting incident MALO. The results showed FIB-4 to be the most effective in predicting MALO. [Gastroenterology 2020;158:200-214]