Improved survival prediction and comparison of prognostic models for patients with hepatocellular carcinoma treated with sorafenib

BACKGROUND: The 'Prediction Of Survival in Advanced Sorafenib-treated HCC' (PROSASH) model addressed the heterogeneous survival of patients with hepatocellular carcinoma (HCC) treated with sorafenib in clinical trials, but requires validation in daily clinical practice. This study aimed to validate, compare and optimize this model for survival prediction. METHODS: Patients treated with sorafenib for HCC at 5 tertiary European centres were retrospectively staged according to the PROSASH model. In addition, the optimized PROSASH-II model was developed using the data of 4 centres (training set) and tested in an independent dataset. These models for overall survival (OS) were then compared with existing prognostic models. RESULTS: The PROSASH model was validated in 445 patients, showing clear differences between the 4 risk groups (OS 16.9-4.6 months). A total of 920 patients (n=615 in training set, n=305 in validation set) were available to develop PROSASH-II. This optimized model incorporated fewer and less subjective parameters: the serum albumin, bilirubin and alpha-fetoprotein, and macrovascular invasion, extrahepatic spread and largest tumour size on imaging. Both PROSASH and PROSASH-II showed improved discrimination (C-index 0.62 and 0.63, respectively) compared with existing prognostic scores (C-index ≤0.59). CONCLUSIONS: In HCC patients treated with sorafenib, individualized prediction of survival and risk group stratification using baseline prognostic and predictive parameters with the PROSASH model was validated. The refined PROSASH-II model performed at least as good with fewer and more objective parameters. PROSASH-II can be used as a tool for tailored treatment of HCC in daily practice and to define pre-planned subgroups for future studies

HLA-C and KIR combined genotype as new response marker for HBeAg-positive chronic hepatitis B patients treated with interferon-based combination therapy

Current treatment for chronic hepatitis B infection (CHB) consists of interferon-based therapy. However, for unknown reasons, a large proportion of patients with CHB do not respond to this treatment. Hence, there is a pressing need to establish response markers to select patients who will benefit from therapy and to spare potential nonresponders from unnecessary side effects of antiviral therapy. Here, we assessed whether HLA-C and KIR genotypes were associated with treatment outcome for CHB. Twelve SNPs in or near the HLA-C gene were genotyped in 86 CHB patients (41 HBeAg positive; 45 HBeAg negative) treated with peginterferon alfa-2a + adefovir. Genotyping of killer immunoglobin-like receptors (KIRs) was performed by SSP-PCR. One SNP in HLA-C (rs2308557) was significantly associated with combined response in HBeAg-positive CHB patients (P = 0.003). This SNP is linked to the HLA-C group C1 or C2 classification, which controls KIR binding. The combination of KIR2DL1 with its ligand HLA-C2 was observed significantly more often in HBeAg-positive patients with a combined response (13/14) than in nonresponders (11/27, P = 0.001). Patients with the KIR2DL1/C2 genotype had significantly higher baseline ALT levels (136 vs 50 U/L, P = 0.002) than patients without this combination. Furthermore, KIR2DL1-C2 predicted response independent of HBV genotype and ALT at baseline. HLA-C and KIR genotype is strongly associated with response in HBeAg-positive CHB patients treated with interferon-based therapy. In combination with other known response markers, HLA-C/KIR genotype could enable the selection of patients more likely to respond to interferon-based therap