BACKGROUND/AIMS: Hematological abnormalities during hepatitis C virus (HCV) combination therapy with pegylated interferon alpha and ribavirin often necessitate dose reduction. Variants of the ITPA gene have been reported to protect against anemia during the early stages of HCV combination treatments but have also been associated with larger decreases in platelet counts. We aimed to identify the association between specific ITPA gene polymorphisms and hematological abnormalities in patients undergoing HCV combination therapy. METHODS: In this retrospective study, 175 patients treated with HCV combination therapy were enrolled at St. Martin De Porres Hospital in Taiwan between 2006 and 2012. Two single nucleotide polymorphisms (SNP) within or adjacent to the ITPA gene (rs1127354, rs6051702) were genotyped. We investigated the effect of ITPA gene variants on hematological abnormalities during the therapy. RESULTS: The ITPA rs1127354 minor variants were significantly associated with protection against anemia at week 4 (p=1.86 x 10(-6)) and with more severe decreases in platelet counts during HCV combination therapy. SNP rs6051702 was not associated with the hemoglobin decline to >3 g/dL at week 4 in our study (p=0.055). CONCLUSIONS: The ITPA SNP rs1127354 is a useful predictor of ribavirin-induced anemia in Taiwanese patients and may be related to more severe decreases in platelet counts during the early stage of HCV combination therapy.
Adult ; Aged ; Anemia/chemically induced/genetics ; Antiviral Agents/*adverse effects ; Cross-Sectional Studies ; Drug Therapy, Combination/adverse effects ; Female ; Hematologic Diseases/*chemically induced/genetics ; Hepacivirus ; Hepatitis C/*drug therapy ; Humans ; Interferon-alpha/adverse effects ; Male ; Middle Aged ; *Polymorphism, Single Nucleotide ; Pyrophosphatases/*genetics ; Retrospective Studies ; Ribavirin/adverse effects ; Taiwan ; Thrombocytopenia/chemically induced/genetics

BACKGROUND/AIMS: Hematological abnormalities during hepatitis C virus (HCV) combination therapy with pegylated interferon alpha and ribavirin often necessitate dose reduction. Variants of the ITPA gene have been reported to protect against anemia during the early stages of HCV combination treatments but have also been associated with larger decreases in platelet counts. We aimed to identify the association between specific ITPA gene polymorphisms and hematological abnormalities in patients undergoing HCV combination therapy. METHODS: In this retrospective study, 175 patients treated with HCV combination therapy were enrolled at St. Martin De Porres Hospital in Taiwan between 2006 and 2012. Two single nucleotide polymorphisms (SNP) within or adjacent to the ITPA gene (rs1127354, rs6051702) were genotyped. We investigated the effect of ITPA gene variants on hematological abnormalities during the therapy. RESULTS: The ITPA rs1127354 minor variants were significantly associated with protection against anemia at week 4 (p=1.86 x 10(-6)) and with more severe decreases in platelet counts during HCV combination therapy. SNP rs6051702 was not associated with the hemoglobin decline to >3 g/dL at week 4 in our study (p=0.055). CONCLUSIONS: The ITPA SNP rs1127354 is a useful predictor of ribavirin-induced anemia in Taiwanese patients and may be related to more severe decreases in platelet counts during the early stage of HCV combination therapy.
Adult ; Aged ; Anemia/chemically induced/genetics ; Antiviral Agents/*adverse effects ; Cross-Sectional Studies ; Drug Therapy, Combination/adverse effects ; Female ; Hematologic Diseases/*chemically induced/genetics ; Hepacivirus ; Hepatitis C/*drug therapy ; Humans ; Interferon-alpha/adverse effects ; Male ; Middle Aged ; *Polymorphism, Single Nucleotide ; Pyrophosphatases/*genetics ; Retrospective Studies ; Ribavirin/adverse effects ; Taiwan ; Thrombocytopenia/chemically induced/genetics

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Background/Aims: Real-world studies assessing the effectiveness and safety of sofosbuvir/velpatasvir (SOF/VEL) plus ribavirin (RBV) for Child-Pugh B/C hepatitis C virus (HCV)-related cirrhosis are limited. Methods: We included 107 patients with Child-Pugh B/C HCV-related cirrhosis receiving SOF/VEL plus RBV for 12 weeks in Taiwan. The sustained virologic response rates at off-treatment week 12 (SVR12) for the evaluable population (EP), modified EP, and per-protocol population (PP) were assessed. Thesafety profiles were reported. Results: The SVR12 rates in the EP, modified EP and PP were 89.7% (95% confidence interval [CI], 82.5–94.2%), 94.1% (95% CI, 87.8–97.3%), and 100% (95% CI, 96.2–100%). Number of patients who failed to achieve SVR12 were attributed to virologic failures. The SVR12 rates were comparable regardless of patient characteristics. One patient discontinued treatment because of adverse events (AEs). Twenty-four patients had serious AEs and six died, but none were related to SOF/VEL or RBV. Among the 96 patients achieving SVR12, 84.4% and 64.6% had improved Child-Pugh and model for endstage liver disease (MELD) scores. Multivariate analysis revealed that a baseline MELD score ≥15 was associated with an improved MELD score of ≥3 (odds ratio, 4.13; 95% CI, 1.16–14.71; P=0.02). Patients with chronic kidney disease (CKD) stage 1 had more significant estimated glomerular filtration rate declines than patients with CKD stage 2 (-0.42 mL/min/1.73 m2/month; P=0.01) or stage 3 (-0.56 mL/min/1.73 m2/month; P<0.001). Conclusions SOF/VEL plus RBV for 12 weeks is efficacious and well-tolerated for Child-Pugh B/C HCV-related cirrhosis.

Background/Aims: Real-world studies assessing the effectiveness and safety of sofosbuvir/velpatasvir (SOF/VEL) plus ribavirin (RBV) for Child-Pugh B/C hepatitis C virus (HCV)-related cirrhosis are limited. Methods: We included 107 patients with Child-Pugh B/C HCV-related cirrhosis receiving SOF/VEL plus RBV for 12 weeks in Taiwan. The sustained virologic response rates at off-treatment week 12 (SVR12) for the evaluable population (EP), modified EP, and per-protocol population (PP) were assessed. Thesafety profiles were reported. Results: The SVR12 rates in the EP, modified EP and PP were 89.7% (95% confidence interval [CI], 82.5–94.2%), 94.1% (95% CI, 87.8–97.3%), and 100% (95% CI, 96.2–100%). Number of patients who failed to achieve SVR12 were attributed to virologic failures. The SVR12 rates were comparable regardless of patient characteristics. One patient discontinued treatment because of adverse events (AEs). Twenty-four patients had serious AEs and six died, but none were related to SOF/VEL or RBV. Among the 96 patients achieving SVR12, 84.4% and 64.6% had improved Child-Pugh and model for endstage liver disease (MELD) scores. Multivariate analysis revealed that a baseline MELD score ≥15 was associated with an improved MELD score of ≥3 (odds ratio, 4.13; 95% CI, 1.16–14.71; P=0.02). Patients with chronic kidney disease (CKD) stage 1 had more significant estimated glomerular filtration rate declines than patients with CKD stage 2 (-0.42 mL/min/1.73 m2/month; P=0.01) or stage 3 (-0.56 mL/min/1.73 m2/month; P<0.001). Conclusions SOF/VEL plus RBV for 12 weeks is efficacious and well-tolerated for Child-Pugh B/C HCV-related cirrhosis.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.