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CONTENTS Chapter 1. Introduction 11 Chapter 2. Prediction of response to treatment Chapter 2.1. Stronger HBV DNA suppression in HBeAg-positive chronic hepatitis B patients with peginterferon induced fl ares or HBeAg loss compared with placebo Chapter 2.2. Factors that predict response of patients with hepatitis B e antigen-positive chronic hepatitis B to peginterferon-alfa Chapter 2.3. Prediction of the response to peginterferon-alpa in patients with HBeAg positive chronic hepatitis B using decline of HBV DNA during treatment Chapter 2.4. Dynamic prediction of response to HBV-treatment using multivariate longitudinal profi les Chapter 2.5. Early on-treatment prediction of response to peginterferon alfa-2a for HBeAg-negative chronic hepatitis B using HBsAg and HBV DNA levels Chapter 3. Statistical models of long-term treatment effects Chapter 3.1. Long-term clinical outcome and effect of glycyrrhizin in 1093 chronic hepatitis C patients with non-response or relapse to interferon Chapter 3.2. Discriminant analysis using a multivariate linear mixed model with a normal mixture in the random effects distribution Chapter 4. Statistical models of early treatment effects Chapter 4.1. Viral dynamics during and after entecavir therapy in patients with chronic hepatitis B 27 43 61 79 105 125 141 175
Page 1: Statistical Models of Treatment Eff
Page 4 and 5: ISBN: 978-90-8559-069-9 © Bettina
Page 6 and 7: PROMOTIECOMMISSIE Promotor: Prof.dr
Page 10: Chapter 4.2. Viral dynamics during
Page 15 and 16: INTRODUCTION Introduction 13 This t
Page 17 and 18: Introduction 15 patients becomes ch
Page 19 and 20: Introduction 17 approach to directl
Page 21 and 22: ln V(t) ln(1-A) 1 st phase: ln(V 0)
Page 23 and 24: AIMS Introduction 21 In this thesis
Page 25: Introduction 23 17. Ohto H, Terazaw
Page 29 and 30: Chap ter 2.1 HBV DNA suppression in
Page 31 and 32: INTRODUCTION PEG-IFN versus placebo
Page 33 and 34: PEG-IFN versus placebo for HBeAg-po
Page 35 and 36: Figure 2 PEG-IFN versus placebo for
Page 41 and 42: References 1. Liaw YF, Chu CM. Hepa
Page 45 and 46: Cha pter 2.2 Factors that predict r
Page 47 and 48: INTRODUCTION Factors that predict r
Page 49 and 50: Factors that predict response to PE
Page 51 and 52: Table 1. Baseline characteristics a
Page 53 and 54: ��
Page 59 and 60:
Factors that predict response to PE
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Factors that predict response to PE
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Chapter 2.3 62 ABSTRACT Peginterfer
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Chapter 2.3 64 only provides the be
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Chapter 2.3 66 optimal cut-off poin
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Chapter 2.3 68 Table 2. Logistic re
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Chapter 2.3 70 and p=0.056 for the
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Chapter 2.3 72 DISCUSSION Recently
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Chapter 2.3 74 Taqman PCR. A reliab
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Chapter 2.3 76 13. Robins JM, Herna
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Chapter 2.4 80 ABSTRACT Dynamic upd
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Chapter 2.4 82 prediction is necess
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Chapter 2.4 84 a. b. c. Figure 1.Th
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Chapter 2.4 86 suggested above a sm
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Chapter 2.4 88 Finally in the rando
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Chapter 2.4 90 more or less no chan
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Chapter 2.4 92 a. b. c. Figure 3. B
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Chapter 2.4 94 Figure 4. Dynamic pr
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Chapter 2.4 96 overall baseline pre
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Chapter 2.4 98 Finally some compari
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Chapter 2.4 100 mixed effect models
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Chapter 2.4 102 References 1. Janss
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Cha pter 2.5 Early on-treatment pre
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INTRODUCTION Early on-treatment pre
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Statistical analysis Early on-treat
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Early on-treatment prediction of re
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Page 119 and 120:
References Early on-treatment predi
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Page 125:
Cha pter 3 Statistical models of lo
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Chapter 3.1 126 ABSTRACT Background
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Chapter 3.1 128 METHODS Study desig
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Chapter 3.1 130 the presence of a c
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Chapter 3.1 132 ure 2 30 >3 x ULN 2
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Chapter 3.1 134 DISCUSSION The aim
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Chapter 3.1 136 References 1. Poyna
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Chapter 3.1 138 U i = Time to failu
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Chapter 3.2 142 Abstract We have de
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Chapter 3.2 144 multiple markers wa
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Chapter 3.2 146 The correlation bet
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Chapter 3.2 148 for our MLMM is fac
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Chapter 3.2 150 X and Z matrices fr
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Chapter 3.2 152 For each g =0,...,G
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Chapter 3.2 154 Focus of marginal,
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Chapter 3.2 156 Figure 1. Dutch PBC
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Chapter 3.2 158 Table 2. Dutch PBC
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Page 164 and 165:
Page 166 and 167:
Chapter 3.2 164 effects correct the
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Chapter 3.2 166 References 1. Kuipe
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Chapter 3.2 168 32. Tsiatis AA, Dav
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Chapter 3.2 170 Table 4. Structure
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Cha pter 4.1 Viral dynamics during
Page 179 and 180:
INTRODUCTION Viral dynamics during
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V(t) = V 0 { A exp (-λ 1 t ) + (1-
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Table 2. Dynamic parameters during
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Figure 1. Viral dynamics during and
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Viral dynamics during and after ent
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References Viral dynamics during an
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Viral dynamics during and after ent
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Chapter 4.2 192 ABSTRACT Tenofovir,
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Chapter 4.2 194 PATIENTS AND METHOD
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Chapter 4.2 196 2 Slow: decline bet
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Chapter 4.2 198 Table 2. Parameter
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Chapter 4.2 200 9.0 8.0 7.0 6.0 5.0
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Chapter 4.2 202 release. Although w
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Chapter 4.2 204 References 1. Perri
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Chapter 4.2 206 29. Lewin SR, Ribei
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Chapter 4.3 210 ABSTRACT Treatment
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Chapter 4.3 212 HBV DNA quantifi ca
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Chapter 4.3 214 The resulting model
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Chapter 4.3 216 Figure 1. Median HB
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Chapter 4.3 218 Table 2: Pharmacoki
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Chapter 4.3 220 Figure 3. effects r
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Chapter 4.3 222 13-14 This model ta
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Chapter 4.3 224 References 1. Kane
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Chapter 4.3 226 25. Wolters LM, Han
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Cha pter 5 Summary and conclusion
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Summary and conclusion 232 Therapy
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Summary and conclusion 234 who deve
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Summary and conclusion 236 fi t mod
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Cha pter 6 Samenvatting en conclusi
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Samenvatting en conclusie 242 posit
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Samenvatting en conclusie 244 De ve
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Samenvatting en conclusie 246 en na
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Samenvatting en conclusie 248 In ee
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DANKWOORD Dankwoord 253 Met oplucht
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CUR RICULUM VITAE Curriculum Vitae
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Bibliography 258 Mechanical factors
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Bibliography 260 35. Wolters LM, Ha
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Bibliography 262 Volume Measurement
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Bibliography 264 Quantitative HBV D
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Bibliography 266 to Peginterferon-a
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ISBN: 978-90-8559-069-9
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