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Chapter 4.3 212 HBV DNA quantifi cation HBV DNA levels were measured frequently during the fi rst month of therapy (at days 0, 1, 2, 3, 4, 7, 14, 21 and 28) in a randomly selected subgroup of 38 patients (19 patients in the monotherapy group and 19 patients in the combination therapy group) using an in-house developed TaqMan real-time PCR test with a dynamic range of 4x102-1010 copies/ml. 12 Monthly HBV DNA measurements were available in all 96 patients. PEG-IFN α-2b concentration PEG-IFN α-2b serum concentrations were also measured at days 0, 1, 2, 3, 4, 7, 14, 21 and 28 using a quantitative sandwich interferon enzyme-linked immuno-sorbent assay (ELISA, Bender MedSystems Diagnostics GmbH, Vienna, Austria) in all 96 patients. Binding of (pegylated) interferon to a murine monoclonal antibody directed against interferon adsorbed onto micro wells was detected by an HRP-conjugated monoclonal antiinterferon antibody. Following 2 hours of incubation unbound complexes were removed by washing (three times) after which tetramethyl-benzidine was used to determine the amount of interferon in the sample. Absorbency was read using a spectro-photometer using 450nm as the primary wave length. Standards were prepared from diluted series of pegylated interferon in normal human serum obtained from healthy volunteers. Patient sera and standards were tested in triplicate, on the same plate. Although optical densities obtained were related to a standard of pegylated interferon, the ELISA also may detect free recombinant interferon-2b molecules and natural interferon. The detection limit of the assay is 35 pg/ml and is linear up to a concentration of 2000 pg/ml. Modelling of pharmacokinetics For modelling of the pharmacokinetics of PEG-IFN α-2b we used the absorption and elimination model recently applied by Powers et al. and Talal et al. 13-14 This model describes the concentration of drug in the blood (C) following a single injection at time t=0 as follows: C k D�F/ Vd � �k�k� �kat �k t �e�e� ( t) � a e (1) e a where t is the time after injection, ka is the rate of absorption, ke is the rate of elimination, F is the bioavailability, D is the drug dose and Vd is the volume of distribution. We used
HBV viral kinetics during PEG-IFN 213 a more general model for multiple weekly injections of PEG-IFN α-2b that accounts for random variability effects between subjects. The PEG-IFN α-2b concentration in the blood for individual i at the time point t is then described as the sum of the individual contributions of each injection d until time t, i.e. td
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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
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Chap ter 3.1 Long-term clinical out
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INTRODUCTION Glycyrrhizin for IFN-n
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Statistics Glycyrrhizin for IFN-non
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Glycyrrhizin for IFN-non responders
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Table 2. Time dependent Cox regress
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Cha pter 3.2 Discriminant analysis
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Introduction Discriminant analysis
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Discriminant analysis using a MLMM
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Estimation Discriminant analysis us
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where wi,k(y i, θ) = (k =1,...,K).
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Page 163 and 164: Discriminant analysis using a MLMM
Page 171 and 172: Appendix Discriminant analysis usin
Page 175: Cha pter 4 Statistical models of ea
Page 178 and 179: Chapter 4.1 176 ABSTRACT Nucleoside
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: INTRODUCTION HBV viral kinetics dur
Page 217 and 218: HBV viral kinetics during PEG-IFN 2
Page 229: HBV viral kinetics during PEG-IFN 2
Page 233 and 234: SUMMARY AND CONCLUSION Summary and
Page 235 and 236: Summary and conclusion 233 The mode
Page 237 and 238: Summary and conclusion 235 The infe
Page 239: Summary and conclusion 237 Early st
Page 243 and 244: SAMENVATTING EN CONCLUSIE Samenvatt
Page 245 and 246: Samenvatting en conclusie 243 Er we
Page 247 and 248: Samenvatting en conclusie 245 Data
Page 249 and 250: Samenvatting en conclusie 247 Behan
Page 253: Dan kwoord
Page 256 and 257: Dankwoord 254 Lieve Marion en Margr
Page 259 and 260: BIBLI OGRAPHY Bibliography 257 1. K
Page 261 and 262: Bibliography 259 Interferon-ribavir
Page 263 and 264: 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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