Noninvasive scores use LSM to detect cirrhosis, advance fibrosis in NAFLD

Using liver stiffness measurements (LSM) combined with routine clinical parameters, Agile 3+, and Agile 4, both noninvasive scoring methods, can accurately identify advanced fibrosis (AF) and cirrhosis, respectively, in patients with nonalcoholic fatty liver disease (NAFLD), reports a new study.

The study included seven different international cohorts of adult NAFLD patients who underwent liver biopsy. Participants were randomly divided into the training and internal validation sets, data from which were used to build and assess models, respectively. External validation of Agile 3+ and Agile 4 was also conducted using two large cohorts.

During internal validation, Agile 4 demonstrated strong predictive performance for cirrhosis, as shown by an area under the receiver operating curve (AUROC) of 0.89 (95 percent confidence interval [CI], 0.87–0.92). Such predictive capacity was statistically better than using only LSM (p<0.0001) or the fibrosis-4 score (p<0.0001).

The same was true for Agile 3+, which produced an AUROC of 0.90 (95 percent CI, 0.89–0.92) for the prediction of AF.

Both Agile 3+ and Agile 4 led to excellent discriminative performances for AF and cirrhosis, respectively, when using the external validation cohorts. AUROCs ranged from 0.86 to 0.93 across all analyses.

“By combining simple clinical parameters together with routine laboratory biomarkers and LSM, it is possible to improve the positive predictive value and reduce the number of cases with indeterminate results for the identification of cirrhosis and AF in patients with NAFLD in secondary/tertiary care liver clinics,” the researchers said.