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Chapter 2.5 114 peginterferon and nucleos(t)ide analogues as initial treatment options 20, 22-23 , but the optimal choice for individual patients remains controversial. Due to the higher chance of disease relapse after treatment discontinuation peginterferon is relatively less often prescribed to HBeAg-negative as compared to HBeAg-positive patients. A treatment course with peginterferon should however be considered for HBeAg-negative patients with a high likelihood of response, because a fi nite treatment course can lead to an off-treatment SR. Otherwise prolonged or indefi nite treatment with a nucleos(t)ide analogue is likely. Unfortunately, baseline predictors of response to peginterferon are poorly defi ned in comparison with HBeAg-positive disease. 24-25 One study reported that baseline serum HBV DNA and ALT levels, patient age and gender, and infecting HBV genotype were signifi cantly associated with response to peginterferon alfa-2a with or without lamivudine therapy, 26 but this was not confi rmed in our patient population. Recent studies on peginterferon in HBeAg-negative patients have focussed on the identifi cation of markers allowing on-treatment prediction of response. 15-17 We found that accurate prediction of SR to peginterferon for HBeAg-negative disease in an early treatment phase is not possible based on serum HBsAg levels alone. However, combining on-treatment declines in serum HBsAg and HBV DNA concentration resulted in a solid stopping rule. At week 12, the absence of a decline in HBsAg level combined with less than 2 log copies/mL decrease in HBV DNA level identifi ed a substantial proportion of the total study population (20%) in which therapy could be discontinued without losing sustained responders. In contrast, patients in whom both declines were present had the highest probability of SR (39%). This patient group should be encouraged to complete the 48-week treatment phase because they are the most likely group to benefi t from therapy. Table 2 provides recommendations for (dis)continuation of therapy for patient groups based on the chance of developing SR. Obviously, the fi nal decision to (dis)continue therapy is at the discretion of the treating physician, taking into account other factors like drug tolerability as well. Another important fi nding is that a guiding rule before 12 weeks of therapy could not be established because discrimination of Table 2. Recommendations for continuation of peginterferon alfa-2a therapy for HBeAg-negative CHB at week 12. Week 12 versus baseline HBsAg decline HBV DNA decline ≥2 log copies/mL Chance of SR Recommendation to continue no no Absent stop no yes Intermediate continue yes no Intermediate continue yes yes High strong recommendation for continuation
Early on-treatment prediction of response to PEG 115 serum HBsAg and HBV DNA levels during the fi rst 8 weeks of treatment did not prove suffi cient. Also, the decision to discontinue therapy should not be postponed, because the prediction of SR did not improve signifi cantly at week 24 compared to week 12. The kinetics of serum HBsAg and HBV DNA levels clearly differed during the treatment phase. HBV DNA decreased throughout the entire treatment period, while a later decline was observed in serum HBsAg levels. HBsAg and HBV DNA levels were not correlated at baseline and early during the treatment phase, further underlining the additional value of HBsAg levels in the prediction of SR. The added information that is provided by quantitative assessment of serum HBsAg may be explained by the dual antiviral and immunomodulatory mode of action of peginterferon. The on-treatment reduction in serum HBV DNA primarily refl ects the direct antiviral effect of peginterferon. In contrast, the decline in serum HBsAg may be a marker of its immunomodulatory effects resulting in gradual clearance of infected hepatocytes from the liver through the induction of cytotoxic T-cell activity. 27 In line with these fi ndings, it has been demonstrated that reductions in serum HBsAg mirror the decline in intrahepatic cccDNA. 13-14 Recently high predictive values for on-treatment HBsAg declines at weeks 12 and 24 on sustained virological response (HBV DNA
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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
Page 65 and 66: INTRODUCTION Dynamic prediction of
Page 67 and 68: Statistical analysis Dynamic predic
Page 69 and 70: Dynamic prediction of response to P
Page 77 and 78: References Dynamic prediction of re
Page 81 and 82: Cha pter 2.4 Dynamic prediction of
Page 83 and 84: INTRODUCTION Dynamic prediction of
Page 85 and 86: For the indirect approach we rewrit
Page 87 and 88: logit pi,j = logit Pr(Ri =1|visit =
Page 89 and 90: Dynamic prediction of response usin
Page 101 and 102: Table 1. Results of different stopp
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Page 108 and 109: Chapter 2.5 106 ABSTRACT Peginterfe
Page 110 and 111: Chapter 2.5 108 and placebo daily.
Page 112 and 113: Chapter 2.5 110 for patients with a
Page 114 and 115: Chapter 2.5 112 Mean HBV DNA declin
Page 118 and 119: Chapter 2.5 116 hepatocellular carc
Page 120 and 121: Chapter 2.5 118 13. Werle-Lapostoll
Page 122: 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).
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Discriminant analysis using a MLMM
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Discriminant analysis using a MLMM
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Appendix Discriminant analysis usin
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Cha pter 4 Statistical models of ea
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Chapter 4.1 176 ABSTRACT Nucleoside
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Chapter 4.1 178 at day 1 at t =0 an
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Chapter 4.1 180 Table 1. Baseline c
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Chapter 4.1 182 Figure 1.
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Chapter 4.1 184 Figure 1. Viral dec
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Chapter 4.1 186 suppression in seru
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Chapter 4.1 188 13. Seifer M, Hamat
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Cha pter 4.2 Viral dynamics during
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INTRODUCTION Viral dynamics during
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Viral dynamics during tenofovir the
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log HBV DNA (copies/mL) 10.0 9.0 8.
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Chap ter 4.3 Modelling of early vir
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INTRODUCTION HBV viral kinetics dur
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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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