Newly diagnosed hepatocellular carcinoma in patients with advanced hepatitis C treated with DAAs: A prospective population study.

BACKGROUND & AIMS: Direct-acting antiviral agents (DAAs) are safe and effective in patients with hepatitis C. Conflicting data were reported on the risk of hepatocellular carcinoma (HCC) during/after therapy with DAAs. The aim of this study was to evaluate the incidence of newly diagnosed HCC and associated risk factors in patients with advanced hepatitis C treated with DAAs. METHODS: The study is based on the NAVIGATORE platform, a prospectively recording database of all patients with hepatitis C receiving DAAs in the Veneto region of Italy. The inclusion criteria were: fibrosis stage ≥F3. The exclusion criteria were: Child-Turcotte-Pugh (CTP)-C, liver transplantation before DAAs, history or presence of HCC, follow-up <4 weeks after starting DAAs. A total of 3,917 out of 4,234 consecutive patients were included, with a mean follow-up of 536.2 ±â€¯197.6 days. RESULTS: Overall, HCC was diagnosed in 55 patients. During the first year, HCC incidence was 0.46% (95% CI 0.12-1.17) in F3, 1.49% (1.03-2.08) in CTP-A and 3.61% (1.86-6.31) in CTP-B cirrhotics; in the second year, HCC incidences were 0%, 0.2%, and 0.69%, respectively. By multivariate analysis, HCC was significantly associated with an aspartate aminotransferase to platelet ratio ≥2.5 (hazard ratio [HR] 2.03; 95% CI 1.14-3.61; p = 0.016) and hepatitis B virus infection (HR 3.99; 1.24-12.91; p = 0.021). Failure to achieve a sustained virological response was strongly associated with development of HCC (HR 9.09; 5.2-16.1; p = 0.0001). A total of 29% of patients with HCC had an aggressive tumor, often seen in the early phase of treatment. CONCLUSIONS: These data, obtained in a large, prospective, population-based study, indicate that in patients with advanced hepatitis C receiving DAAs, the risk of "de novo" hepatocarcinoma during the first year is not higher, and might be lower, than that of untreated patients. The risk further declines thereafter. Early hepatocarcinoma appearance may reflect pre-existing, microscopic, undetectable tumors. LAY SUMMARY: Hepatocellular carcinoma is one of the complications of hepatitis C related cirrhosis. Treating patients with advanced hepatitis C with the new interferon-free direct-acting antiviral agents has been associated with improvement in liver function and survival, while more conflicting data have been reported regarding the risk of hepatocellular carcinoma. We report the results of a prospective population study on the incidence of newly diagnosed hepatocellular carcinoma in patients with advanced hepatitis C treated with direct-acting antiviral agents, clearly indicating that the residual hepatocellular carcinoma risk is reduced and declines progressively with time after a sustained virological response. Development of a liver tumor during/after therapy was associated with known risk factors and with virological failure.

Structural properties and interaction energies affecting drug design. An approach combining molecular simulations, statistics, interaction energies and neural networks.

In order to elucidate some basic principles for protein-ligand interactions, a subset of 87 structures of human proteins with their ligands was obtained from the PDB databank. After a short molecular dynamics simulation (to ensure structure stability), a variety of interaction energies and structural parameters were extracted. Linear regression was performed to determine which of these parameters have a potentially significant contribution to the protein-ligand interaction. The parameters exhibiting relatively high correlation coefficients were selected. Important factors seem to be the number of ligand atoms, the ratio of N, O and S atoms to total ligand atoms, the hydrophobic/polar aminoacid ratio and the ratio of cavity size to the sum of ligand plus water atoms in the cavity. An important factor also seems to be the immobile water molecules in the cavity. Nine of these parameters were used as known inputs to train a neural network in the prediction of seven other. Eight structures were left out of the training to test the quality of the predictions. After optimization of the neural network, the predictions were fairly accurate given the relatively small number of structures, especially in the prediction of the number of nitrogen and sulfur atoms of the ligand.