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Chapter 4.1 176 ABSTRACT Nucleoside analogues inhibit hepatitis B virus (HBV) replication. Entecavir, a new guanine nucleoside, has also been shown to reduce covalently closed circular DNA (cccDNA) to undetectable levels in woodchucks chronically infected with hepatitis virus. Mathematical description of changes in viral load during and after therapy may help to understand the several events that take place during nucleoside analogue treatment. Ten chronic hepatitis B patients were evaluated with a mathematical model during and after withdrawal of four doses of entecavir. Blood was drawn for HBV DNA measurement at frequent intervals. Non-linear modelling was used to fit individual patient data. The median effectiveness in blocking viral production is 96% (n = 10, range 87–98%). The median half-life of viral turn-over was 16 h (range 12–29 h). The median half-life of infected hepatocytes was 257 h ( = 10.7 days) (n = 9, range 112–762 h). Rebound of viral replication also followed a bi-phasic return to baseline levels. In Conclusions decay and rebound of viral concentration during and after entecavir therapy, respectively, showed a bi phasic pattern. Both can be described with a mathematical model. Data on levels of cccDNA in the liver in these patients could be helpful in supporting the parameters as calculated with the model.
INTRODUCTION Viral dynamics during and after entecavir therapy 177 In patients with chronic hepatitis B infection, annual clearance of HBsAg and HBeAg is estimated at 1 and 10%, respectively. HBeAg clearance, which is immune mediated, is improved by alpha interferon therapy resulting in HBeAg seroconversion in 30–40% of patients. 1–4 In particular, those patients with an immune-tolerant status, a large part of which is originating from Asian countries, do not show a favourable response to alpha interferon therapy. 5 Recently, lamivudine has been registered as a second option for the treatment of chronic hepatitis B patients. Whereas HBeAg seroconversion is a solid endpoint for alpha interferon therapy, durability of HBeAg seroconversion after withdrawal of lamivudine therapy needs to be evaluated. Reports on this end-point are contradictory. 6–8 Recurrence of viral activity is attributed to the remnant covalently closed circular DNA (cccDNA) inside the nucleus of hepatocytes which is not affected by lamivudine. 9–10 Entecavir, a new guanine nucleoside analogue which is currently under investigation in phase II studies, is believed to be capable of interfering with cccDNA. 11–13 This consideration is based on observations in woodchucks chronically infected with the woodchuck hepatitis B virus (HBV). Short-term entecavir therapy markedly reduces cccDNA levels in the liver of woodchucks14 and rebound of virus after withdrawal of therapy in woodchucks. 15 Moreover, maintenance therapy in woodchucks with once weekly dosing regimens is able to reduce cccDNA in the liver to undetectable levels. 16 Mathematical modelling can be used to evaluate the mechanism of action of entecavir on both viral decline during and the return of virus after withdrawal of therapy. In previous modelling studies on the effect of nucleoside analogues in a chronic hepatitis B infection, it has been shown that viral decline can be divided into two phases: a fi rst phase of turn-over of free virus and a second phase of death of infected hepatocytes. 17–18 Return of virus after withdrawal of therapy has never been evaluated in detail, but may be helpful in clarifying the mechanisms that take place during viral replication. We therefore conducted a study to model viral decline during entecavir therapy and viral return after withdrawal of entecavir therapy. PATIENTS AND METHODS Study design All patients who were treated in the Academic Hospital <strong>Rotterdam</strong>, The Netherlands, in a study on the safety and effi cacy of entecavir were recruited for a study on viral dynamics. Patients were treated in a 1 month, double-blind, placebo-controlled dose escalating study on the safety and effi cacy of entecavir (0.05, 0.1, 0.5, 1.0 mg) vs. placebo with a follow-up of 6 months. During the fi rst month of therapy, HBV DNA was measured
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Statistical Models of Treatment Eff
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ISBN: 978-90-8559-069-9 © Bettina
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PROMOTIECOMMISSIE Promotor: Prof.dr
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CONTENTS Chapter 1. Introduction 11
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Cha pter 1 Introduction
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Chapter 1 14 Epidemiology Worldwide
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Chapter 1 16 Prediction models with
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Chapter 1 18 standard method fails
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Chapter 1 20 The extended non-linea
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Chapter 1 22 References 1. Blumberg
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Cha pter 2 Prediction of response t
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Chapter 2.1 28 ABSTRACT The aim of
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Chapter 2.1 30 been hepatitis B sur
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Chapter 2.1 32 HBV DNA decline The
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Chapter 2.1 34 Figure 2 continued.
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Chapter 2.1 36 Figure 4. Estimated
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Chapter 2.1 38 DNA was observed in
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Chapter 2.1 40 15. Kao JH. Role of
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Chapter 2.2 44 ABSTRACT Background:
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Chapter 2.2 46 low baseline HBV DNA
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Chapter 2.2 48 patient subgroups wa
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Chapter 2.2 50 p=0.002). Previous I
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Chapter 2.2 52 Application of the m
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Chapter 2.2 54 PEG-IFN, the proport
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Chapter 2.2 56 References 1. Lavanc
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Chapter 2.2 58 26. Bonino F, Lau GK
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Chap ter 2.3 Prediction of the resp
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INTRODUCTION Dynamic prediction of
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Statistical analysis Dynamic predic
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Dynamic prediction of response to P
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References Dynamic prediction of re
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Cha pter 2.4 Dynamic prediction of
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INTRODUCTION Dynamic prediction of
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For the indirect approach we rewrit
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logit pi,j = logit Pr(Ri =1|visit =
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Dynamic prediction of response usin
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Table 1. Results of different stopp
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Chapter 2.5 106 ABSTRACT Peginterfe
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Chapter 2.5 108 and placebo daily.
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Chapter 2.5 110 for patients with a
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Chapter 2.5 112 Mean HBV DNA declin
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Chapter 2.5 114 peginterferon and n
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Chapter 2.5 116 hepatocellular carc
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Chapter 2.5 118 13. Werle-Lapostoll
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Chapter 2.5 120 Greece - G Germanid
Page 127 and 128: Chap ter 3.1 Long-term clinical out
Page 129 and 130: INTRODUCTION Glycyrrhizin for IFN-n
Page 131 and 132: Statistics Glycyrrhizin for IFN-non
Page 133 and 134: Glycyrrhizin for IFN-non responders
Page 135 and 136: Table 2. Time dependent Cox regress
Page 143 and 144: Cha pter 3.2 Discriminant analysis
Page 145 and 146: Introduction Discriminant analysis
Page 147 and 148: Discriminant analysis using a MLMM
Page 149 and 150: Estimation Discriminant analysis us
Page 153 and 154: where wi,k(y i, θ) = (k =1,...,K).
Page 171 and 172: Appendix Discriminant analysis usin
Page 175: Cha pter 4 Statistical models of ea
Page 180 and 181: Chapter 4.1 178 at day 1 at t =0 an
Page 182 and 183: Chapter 4.1 180 Table 1. Baseline c
Page 184 and 185: Chapter 4.1 182 Figure 1.
Page 186 and 187: Chapter 4.1 184 Figure 1. Viral dec
Page 188 and 189: Chapter 4.1 186 suppression in seru
Page 190 and 191: Chapter 4.1 188 13. Seifer M, Hamat
Page 193 and 194: Cha pter 4.2 Viral dynamics during
Page 195 and 196: INTRODUCTION Viral dynamics during
Page 197 and 198: Viral dynamics during tenofovir the
Page 201 and 202: log HBV DNA (copies/mL) 10.0 9.0 8.
Page 211 and 212: Chap ter 4.3 Modelling of early vir
Page 213 and 214: INTRODUCTION HBV viral kinetics dur
Page 215 and 216: HBV viral kinetics during PEG-IFN 2
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HBV viral kinetics during PEG-IFN 2
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SUMMARY AND CONCLUSION Summary and
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Summary and conclusion 233 The mode
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Summary and conclusion 235 The infe
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Summary and conclusion 237 Early st
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SAMENVATTING EN CONCLUSIE Samenvatt
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Samenvatting en conclusie 243 Er we
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Samenvatting en conclusie 245 Data
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Samenvatting en conclusie 247 Behan
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Dan kwoord
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Dankwoord 254 Lieve Marion en Margr
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BIBLI OGRAPHY Bibliography 257 1. K
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Bibliography 259 Interferon-ribavir
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Bibliography 261 Long term clinical
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Bibliography 263 Flares in chronic
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Bibliography 265 Genetic characteri
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Bibliography 267 106. Reijnders JG,
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