Health state utilities and quality of life in patients with hepatitis B.

BACKGROUND: The effect of chronic hepatitis B (CHB) infection on health-related quality of life (HRQoL) and health state utilities has not been well characterized. OBJECTIVE: To measure utility scores and HRQoL across disease states associated with CHB infection. METHODS: Patients attending four tertiary care clinics for CHB were approached between July 2007 and March 2009. Respondents completed version 2 of the Short-Form 36 Health Survey, the EQ5D, a visual analogue scale, the Health Utilities Index Mark 3, standard gamble, and demographics and risk factor surveys in English, Cantonese or Mandarin. Charts were reviewed to determine disease stage and comorbidities. RESULTS: A total of 433 patients were studied: 294 had no cirrhosis; 79 had compensated cirrhosis; seven had decompensated cirrhosis; 23 had hepatocellular carcinoma; and 30 had received a liver transplant. The mean standard gamble utilities for these disease states were 0.89, 0.87, 0.82, 0.84 and 0.86, respectively. HRQoL scores in noncirrhotic patients were similar to those of the general population. Scores of patients with compensated cirrhosis were not significantly lower; however, patients with decompensated cirrhosis and hepatocellular carcinoma had significantly lower HRQoL scores compared with noncirrhotic patients (P<0.05). Similar scores were observed among patients on and off oral antiviral treatment. Post-liver transplant patients had a higher HRQoL than patients with decompensated cirrhosis. Age, number of comorbidities and relationship status were significantly associated with HRQoL scores. CONCLUSIONS: HRQoL in CHB patients is only impaired in the later stages of liver disease. Neither CHB infection nor antiviral treatment is associated with a lower quality of life.

The cyclophilin inhibitor Debio 025 combined with PEG IFNalpha2a significantly reduces viral load in treatment-naïve hepatitis C patients.

UNLABELLED: The anti-hepatitis C virus (HCV) effect and safety of three different oral doses of the cyclophilin inhibitor Debio 025 in combination with pegylated interferon-alpha2a (PEG IFN-alpha2a) were investigated in a multicenter, randomized, double-blind, placebo-controlled escalating dose-ranging phase II study in treatment-naïve patients with chronic hepatitis C. Doses of 200, 600, and 1,000 mg/day Debio 025 in combination with PEG IFN-alpha2a 180 microg/week for 4 weeks were compared with monotherapy with either 1,000 mg/day Debio 025 or 180 microg/week PEG IFN-alpha2a. In patients with genotypes 1 and 4, the 600- and 1,000-mg combination treatments induced a continuous decay in viral load that reached -4.61 +/- 1.88 and -4.75 +/- 2.19 log(10) IU/mL at week 4, respectively. In patients with genotypes 2 and 3, HCV RNA levels at week 4 were reduced by -5.91 +/- 1.11 and -5.89 +/- 0.43 log(10) IU/mL, respectively, with the same treatment regimens. Adverse events were comparable between treatment groups apart from a higher incidence of neutropenia associated with PEG IFN-alpha2a and an increased incidence of isolated hyperbilirubinemia at the highest dose of Debio 025 (1,000 mg/day). CONCLUSION: These results confirm that Debio 025 has a potent activity and an additive effect on HCV RNA reduction in genotype 1 and 4 patients at 600 and 1,000 mg/day when combined with PEG IFN-alpha2a.

MAID : an effect size based model for microarray data integration across laboratories and platforms.

BACKGROUND: Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarray technology matures, the number of microarray studies has increased, resulting in many different datasets available for any given disease. The increase in sensitivity and reliability of measurements of gene expression changes can be improved through a systematic integration of different microarray datasets that address the same or similar biological questions. RESULTS: Traditional effect size models can not be used to integrate array data that directly compare treatment to control samples expressed as log ratios of gene expressions. Here we extend the traditional effect size model to integrate as many array datasets as possible. The extended effect size model (MAID) can integrate any array datatype generated with either single or two channel arrays using either direct or indirect designs across different laboratories and platforms. The model uses two standardized indices, the standard effect size score for experiments with two groups of data, and a new standardized index that measures the difference in gene expression between treatment and control groups for one sample data with replicate arrays. The statistical significance of treatment effect across studies for each gene is determined by appropriate permutation methods depending on the type of data integrated. We apply our method to three different expression datasets from two different laboratories generated using three different array platforms and two different experimental designs. Our results indicate that the proposed integration model produces an increase in statistical power for identifying differentially expressed genes when integrating data across experiments and when compared to other integration models. We also show that genes found to be significant using our data integration method are of direct biological relevance to the three experiments integrated. CONCLUSION: High-throughput genomics data provide a rich and complex source of information that could play a key role in deciphering intricate molecular networks behind disease. Here we propose an extension of the traditional effect size model to allow the integration of as many array experiments as possible with the aim of increasing the statistical power for identifying differentially expressed genes.

Nutritional assessment and hepatic fatty acid composition in non-alcoholic fatty liver disease (NAFLD): a cross-sectional study.

BACKGROUND/AIMS: Low hepatic n-6 and n-3 polyunsaturated fatty acid (PUFA) may contribute to steatosis and steatohepatitis and can be affected by diet and oxidative stress. METHODS: Seventy-three patients referred for elevated liver enzymes and suspected NAFLD were assessed. Nutritional assessment, hepatic FA composition and oxidative stress were compared between these groups: simple steatosis (SS, n=18), steatohepatitis (NASH, n=38) and minimal findings on liver biopsy (MF, n=17). RESULTS: Patients with NASH had higher: BMI, central obesity, body fat, insulin resistance, dyslipidemia and lower physical activity compared to the other groups. They also had relatively lower hepatic n-3 and n-6 PUFA, a decrease in the ratio of metabolites to essential FA precursors for both n-6 and n-3 FA (eicosapentaenoic+docosahexaenoic/linolenic and arachidonic/linoleic acid ratios) and higher liver lipid peroxides with lower antioxidant power, when compared to MF. Overall, there was no significant difference between SS and NASH in FA composition. Self-reported dietary intake and red blood cell FA composition were similar among the three groups. CONCLUSIONS: NASH patients have more metabolic abnormalities. This is associated with higher oxidative stress and lower n-3 and n-6 PUFA in the liver in the absence of any differences in dietary FA composition.

HIV-positive patients with nonalcoholic fatty liver disease have a lower body mass index and are more physically active than HIV-negative patients.

OBJECTIVE: To determine whether the clinical and metabolic features associated with nonalcoholic fatty liver disease (NAFLD) are similar between HIV-positive and HIV-negative male subjects. METHODS: Twenty-six HIV-positive and 25 HIV-negative subjects with liver biopsy-proven NAFLD were compared for liver histology (extent of steatosis, steatosis grading, and fibrosis staging), blood biochemistry (glucose, insulin, C-peptide, hemoglobin A1c, and lipid profile), insulin resistance (IR) using a homeostasis model assessment, anthropometry (body mass index [BMI], waist circumference, and arm muscle area), dietary intake, and physical activity. RESULTS: The 2 groups were similar for age, liver histology, and IR. HIV-positive patients had a lower BMI (26.3 +/- 0.5 vs. 30.2 +/- 1.0 kg/m; P = 0.001) and lower percentage of fat mass (19.4 +/- 0.9 vs. 22.7 +/- 1.2; P = 0.026) when compared with HIV-negative patients. Although caloric intake was similar between groups, HIV-positive patients had a higher physical activity level (8.3 +/- 1.6 vs. 4.1 +/- 0.8 units of exercise per day; P = 0.029). Blood triglycerides were significantly higher (3.14 +/- 0.39 vs. 1.86 +/- 0.20 mmol/L; P = 0.006) in HIV-positive patients. CONCLUSION: Although NAFLD was similar between the 2 groups, HIV-positive patients had a lower BMI and were more physically active compared with HIV-negative patients. This may suggest that in HIV, NAFLD is associated with factors other than those related to body fatness, such as HIV infection and treatment.