New algorithm predicts HCC risk in compensated advanced chronic liver disease

A novel algorithm using post-treatment age, albumin, and liver stiffness measurement (LSM), among other parameters, can accurately stratify patients with compensated advanced chronic liver disease (cACLD) according to their de novo hepatocellular carcinoma (HCC) risk, a new study shows.

The algorithm was first developed in a derivation cohort including 527 patients who had pretreatment ACLD and had achieved sustained virologic response (SVR). Likelihood of de novo HCC development was assessed according to sociodemographic factors, alpha-foetoprotein (APF), and noninvasive surrogates of portal hypertension such as LSM. Subsequent validation of the algorithm was performed in a cohort of 1,500 cACLD patients.

In the derivation cohort, 90.1 percent (n=475) had cACLD while 9.9 percent (n=52) had decompensated ACLD. HCC developed in 4.6 percent and 23.1 percent of the respective subgroups. As participants with decompensated ACLD had high excess risk of HCC, all further analyses were focused on cACLD patients.

Compared with baseline values, post-treatment measurements showed stronger discriminative ability for the development of de novo HCC during follow-up.

Models that used post-treatment AFP levels ≥4.6 ng/mL and alcohol consumption (>30 g/day in men, >30 g/day in women) could accurately predict HCC development. Other factors involved in such predictive models included age ≥59 years, LSM ≥19.0 kPa, and albumin levels <42 g/L. These parameters were predictive of de novo HCC in both the derivation and validation cohorts.

“We provided an easily applicable score that facilitates risk stratification in clinical routine, as it identified patients in whom HCC surveillance may not be cost-effective or in whom surveillance is clearly warranted (high-risk; i.e., AFP ≥4.6ng/mL OR age ≥59 years WITH either post-treatment LSM ≥19kPa AND/OR albumin <42 g/L) due to a considerable probability of de-novo HCC despite SVR,” the researchers said.