Hepatitis B e antigen levels and response to peginterferon: influence of precore and basal core promoter mutants.

Hepatitis B e antigen (HBeAg) levels may predict response to peginterferon (PEG-IFN) but are also influenced by presence of precore (PC) and core promoter (BCP) mutants. HBeAg was measured in 214 patients treated with PEG-IFN±lamivudine for 52weeks. Patients were classified at baseline as wildtype (WT) or non-WT (detectable PC/BCP mutants). Combined response (HBeAg loss with HBV DNA<2000IU/mL), HBeAg response (HBeAg loss with HBV DNA>2000IU/mL) or non-response was assessed at week78. Mean baseline HBeAg levels were 2.65logIU/mL in combined responders, 2.48 in non-responders and 2.24 in HBeAg responders (p=0.034). Baseline HBeAg levels were not associated with combined response after stratification by WT/non-WT. Within the PEG-IFN monotherapy group (n=104), patients with HBeAg<1logIU/mL at week24 had a higher probability of combined response (29% versus 12%, p=0.041). After stratification by WT/non-WT, WT patients with HBeAg<1logIU/mL at week24 had a probability of combined response of 78% (versus 19% in patients with >1logIU/mL, p<0.001), whereas no difference in response rates was observed in non-WT patients (p=0.848). The relationship between HBeAg levels and response to PEG-IFN depends upon the presence of PC/BCP mutants. HBeAg levels should therefore not be routinely used to select patients for PEG-IFN, nor for monitoring of therapy.

Close monitoring of hepatitis B surface antigen levels helps classify flares during peginterferon therapy and predicts treatment response.

BACKGROUND: Alanine aminotransferase (ALT) flares occur frequently during peginterferon (PEG-IFN) therapy. We related occurrence of flares to presence of precore (PC) and/or basal core promoter (BCP) mutants and studied kinetics of hepatitis B e antigen (HBeAg) and hepatitis B surface antigen (HBsAg) levels during flares. METHODS: Fifty of 214 (23%) patients treated with PEG-IFN ± lamivudine for 52 weeks experienced flares. Flares were host-induced (ALT elevation followed by HBV DNA decline, n = 19), virus-induced (HBV DNA increase with subsequent ALT elevation, n = 17) or indeterminate (n = 14). Presence of wild-type (WT) or non-WT (detectable PC/BCP mutants) was studied by lineprobe assay. RESULTS: Fifty-eight percent of host-induced flares occurred in WT HBV patients, whereas 94% of virus-induced flares occurred in patients with PC and/or BCP mutants (P = .003). HBsAg loss was only achieved in patients with a host-induced flare, and WT patients with a host-induced flare cleared HBsAg in 64% of cases. Serum HBsAg levels declined after a host-induced flare, whereas virus-induced flares were accompanied by stable or increasing levels of HBsAg. Patients with a host-induced flare achieved a mean HBsAg reduction of 3.24 log IU/mL, compared with 0.25 log IU/mL in virus-induced flares (P < .001). Patients who achieved a decline in HBsAg of >0.5 log IU/mL within 4 weeks after the flare cleared HBsAg in 64% (7 of 11) of cases. CONCLUSIONS: Host-induced flares are associated with WT virus and may result in decline and clearance of HBV DNA, HBeAg, and HBsAg. Monitoring of HBsAg levels during and after flares may help predict a favorable treatment outcome.

A comparison of two assays for quantification of Hepatitis B surface Antigen in patients with chronic hepatitis B.

BACKGROUND AND OBJECTIVES: Serum Hepatitis B surface Antigen (HBsAg) levels correlate with hepatitis B virus intrahepatic covalently closed circular DNA and may predict response to treatment. Currently, 2 commercial platforms are available for HBsAg quantification in clinical practice, the Architect HBsAg QT and the Elecsys HBsAg. We aimed to directly compare the results of these assays. STUDY DESIGN: HBsAg levels were measured in 1427 serum samples from HBeAg-positive chronic hepatitis B patients who participated in a randomized trial of peginterferon alfa-2b±lamivudine. Samples were extracted from our serum bank, thawed, and subsequently analysed for HBsAg levels using both assays. RESULTS: Of 1427 samples, 242 (17%) were taken before and 1185 during the treatment phase of the study. Distribution of HBV genotypes was 447 (31%) genotype A, 125 (9%) B, 210 (15%) C and 534 (37%) D. Correlation between Architect and Elecsys results was high (r=0.96, p<0.001). By Bland-Altman analysis, agreement between the two assays was close (mean difference between Architect and Elecsys: -0.01logIU/mL, 95% CI: -0.55-0.52logIU/mL), also when analysed separately for HBV genotypes A-D. Additionally, the performance of our recently published stopping rule for HBeAg-positive patients treated with peginterferon was comparable: the negative predictive values were 96% and 98% for Elecsys and Architect, respectively. CONCLUSIONS: There is a high correlation and close agreement between quantitative HBsAg measurements conducted with the Architect and the Elecsys. Clinical prediction rules derived from data from one platform can be applied on the other; both can therefore be used in clinical practice.

The association of the dopamine transporter gene and the dopamine receptor 2 gene with delirium, a meta-analysis.

Delirium is the most common neuropsychiatric syndrome in elderly ill patients. Previously, associations between delirium and the dopamine transporter gene (solute carrier family 6, member 3 (SLC6A3)) and dopamine receptor 2 gene (DRD2) were found. The aim of this study was to validate whether markers of the SLC6A3 and DRD2 genes are were associated with delirium in independent populations. Six European populations collected DNA of older delirious patients. Associations were determined per population and results were combined in a meta-analysis. In total 820 medical inpatients, 185 cardiac surgery patients, 134 non-cardiac surgery patients and 502 population-based elderly subjects were included. Mean age was 82 years (SD 7.5 years), 598 (36%) were male, 665 (41%) had pre-existing cognitive impairment, and 558 (34%) experienced delirium. The SLC6A3 rs393795 homozygous AA genotype was more frequent in patients without delirium in all populations. The meta-analysis showed an Odds Ratio (OR) for delirium of 0.4 (95% confidence interval (C.I.) 0.2-0.6, P = 0.0003) for subjects with AA genotype compared to the AG and GG genotypes. SLC6A3 marker rs1042098 showed no association with delirium. In meta-analysis the DRD2 rs6276 homozygous GG genotype showed an OR of 0.8 for delirium (95% C.I. 0.6-1.1, P = 0.24). When subjects were stratified for cognitive status the rs6276 GG genotype showed ORs of 0.6 (95% C.I. 0.4-1.0, P = 0.06) and 0.8 (95% C.I. 0.5-1.5, P = 0.51) for delirium in patients with and without cognitive impairment, respectively. In independent cohorts, a variation in the SLC6A3 gene and possibly the DRD2 gene were found to protect for delirium.

Atorvastatin affects low density lipoprotein and non-high density lipoprotein cholesterol relations with apolipoprotein B in type 2 diabetes mellitus: modification by triglycerides and cholesteryl ester transfer protein.

OBJECTIVES: Non-HDL-cholesterol (non-HDL-C) and apolipoprotein (apo) B are proposed as treatment targets. The extent to which statin therapy affects relationships of LDL-C and non-HDL-C with apoB was examined in type 2 diabetes. METHODS: Analyses were performed in 217 hypertriglyceridaemic type 2 diabetic patients (Diabetes Atorvastatin Lipid Intervention (DALI) cohort). 61 patients randomized to placebo, 70 to 10 mg atorvastatin daily and 65 - 80 mg atorvastin daily completed follow-up. RESULTS: Baseline fasting LDL-C of 2.42 mmol/l and non-HDL-C of 3.69 mmol/l corresponded to the apoB guideline target of 0.90 g/l. During atorvastatin (10 and 80 mg daily), the LDL-C target was achieved most frequently, and lower LDL-C (2.38 and 2.29 mmol/l) and non-HDL-C (3.24 and 3.19 mmol/l) concentrations corresponded to this apoB goal. Decreases in LDL-C during atorvastatin treatment were negatively related (p < 0.001), but decreases in non-HDL-C were positively related to changes in triglycerides (p < 0.001), independently from decreases in apoB (p < 0.001 for all). Decreases in LDL-C and non-HDL-C were positively associated with decreases in cholesteryl ester transfer protein mass (p < 0.001). CONCLUSIONS: During atorvastatin lower LDL-C and non-HDL-C levels correspond to the apoB guideline target, which would favour its use as treatment target.