Aim: to develop an algorithm for predicting HCC incidence over time in a cohort of mixed
etiologies of cirrhosis.
Methods: We retrospectively collected data of cirrhotic patients evaluated in our center between
2004 – 2014. In the same session HVPG measurements, laboratory parameters and AFP
were determined. Patients with HCC at first presentation and those with a follow-up
shorter than 90 days were excluded. HCC diagnosis was established by imaging techniques/biopsy
during followed-up.
Results: We identified 940 cirrhotic patients that were evaluated with HVPG and laboratory
blood tests and those which fulfilled the inclusion criteria were divided in 2 groups:
training (379 patients evaluated between 2004 – 2009) and validation cohort (301 patients:
2010 – 2014). The HCC incidence in the training and validation cohort was: 8.7% and
6.3%.
Univariate analysis in the training cohort showed that presence of clinically significant
portal hypertension (p = 0.007), platelet count< 100000cel/mm3 (p < 0.0001), AFP> 10 ng/ml (p = 0.002), presence of varices (p = 0.03), and age>
50 years (p = 0.04) were associated with HCC occurrence. The following factors were
not associated with HCC occurrence: gender, etiology of liver cirrhosis, presence
of diabetes mellitus, HIV coinfection, BMI, Child-Pugh class, MELD score, presence/history
of ascites, presence/history of hepatic encephalopathy, aminotransferases values,
bilirubin, albumin.
In multivariate analysis, platelet count< 100000/mm3 (OR = 4.36), age> 50 years (OR = 2.46) and AFP> 10 ng/ml (OR = 2.36) reached statistical
significance.
Based on the odds-ratio, the following points were assigned: platelet count< 100000/mm3-2 points, age> 50 years-1 point and AFP> 10 ng/ml-1 point.
The patients were classified in three groups: group 1: 0 – 1 points, group 2: 2 –
3 points and group 3: 4 points.
The HCC incidence/year in the three groups in the training and validation cohort was:
0.6%, 3.2% and 9.2% (p < 0.0001) and respectively 0.3%, 5.5% and 9.2% (p < 0.0001).
Conclusions: The proposed algorithm can identify the patients with very low, moderate and high
risk of HCC, which could be used for more targeted screening approaches.