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Chapter 4.3 214 The resulting model function V i (t) describes the viral load of individual i at time point t and depends on the virion clearance rate c i and the infected cell loss rate δ i . The total number of cells (i.e. infected target cells, I i , and uninfected target cells, T i ) is assumed to remain constant in each individual during treatment motivated by a fast liver regeneration. As usual, the infection rate βi and the viral production rate pi were substituted by the other parameters assuming that they remained unchanged from the steady state situation. Modelling and data fi tting The PROC NLMIXED procedure of SAS 9.1 (SAS Institute Inc., Cary, NC) was used to fi t the fi rst month pharmacokinetic data of all 96 patients with a non-linear mixed modelling approach. The NLME procedure of R (R Foundation for Statistical Computing) yield highly comparable results (data not shown). The prediction of the PEG-IFN α-2b concentration (equation 2) and the model for effectiveness (equation 3) was thereafter incorporated in the model of the viral load as solution from equations 4 and 5 of the patients treated with PEG-IFN α-2b monotherapy. The viral load was hereafter fi tted with non-linear mixed modelling with the NLME procedure of R including the ordinary differential equation solver LSODA from the ODESOLVE package in a nested way to estimate the infected cell loss rate δ, the baseline levels of viral load as well as the IC50 levels and the time delay t0 . Because interindividual variation could already be modelled by baseline viral load and IC50 levels, the other parameters were set constant between patients (fi xed effects). Furthermore, relatively few data points can lead to biased estimates of the viral clearance rate c. 16 Therefore, we fi xed c to 1.3 per day. Different Hill coeffi cients (n=1, n=2, n=3 and n=4) were checked and we used a coeffi cient of 1 because this gave the best results. SPSS (version 14.0.1, SPSS Inc., Chicago, IL) was used for further data analyses. All tests for signifi cance and resulting P values were two-sided, with a level of signifi cance of 0.05. RESULTS Patient characteristics Demographic and baseline characteristics of the 96 included patients in this study are shown in table 1. Forty-eight patients received PEG-IFN α-2b monotherapy; the other 48 patients received combination therapy consisting of PEG-IFN α-2b and lamivudine. There were no signifi cant differences between the two groups with respect to ALT, viral load, age, sex, weight and race. PEG-IFN α-2b concentration was measured in all 96
HBV viral kinetics during PEG-IFN 215 patients whereas frequent HBV DNA measurements were obtained in a representative subset of 38 patients (19 in each treatment arm). Table 1: Baseline characteristics PEG-IFN + lamivudine (n=48) PEG-IFN + placebo (n=48) Age (years)* 33 ± 12 32 ± 12 Sex M/F (% male) 32/16 (67%) 37/11 (77%) Weight (kg)* Race (%) 72 ± 16 71 ± 13 Caucasian 42 (88%) 43 (90%) Asian 2 (4%) 3 (6%) Other Genotype (%) 4 (8%) 2 (4%) A 13 (27%) 15 (31%) B 1 (2%) 2 (4%) C 2 (4%) 2 (4%) D 31 (65%) 29 (61%) E 1 (2%) 0 (0%) ALT (U/L)* 175 ± 193 167 ± 130 HBV DNA (log10 copies/mL)* * Mean ± standard deviation. 9.2 ± 1.1 9.3 ± 0.7 Viral kinetics In the PEG-IFN α-2b monotherapy group (n=19), the median viral decline after one month of treatment was 0.45 log10 copies/ml (range, -0.03 – 1.56) (Figure 1) and 0.40 log10 copies/ml (range, -0.28 – 2.30) at week 8 of treatment. The median viral decline was 0.028 log10 copies/mL per day (range, -0.069 – 0.165) for the fi rst week and 0.017 log10 copies/mL per day (range, -0.006 – 0.046) between week 1 and 4. In the fi rst week of treatment, there was a median decline in viral load of 0.20 log10 copies/ml (range, -0.48 – 1.15). There was an initial decline in viral load until 4 days after drug administration in all patients in the PEG-IFN α-2b monotherapy group. Thereafter there was a rebound towards the end of the week. The median slope of viral rebound at the end of the fi rst week (day 4 to day 7) was 0.060 log10 copies/ml per day (range, -0.117 – 0.393). There was no effect of the baseline viral load level on the amount of viral decline in the fi rst month of treatment. When viral decline was analyzed in the PEG-IFN α-2b and lamivudine combination therapy group (n=19) on the other hand, a median decline in viral load of 2.94 log10 copies/ml (range, 0.55 – 5.02) after one month of treatment was observed (Figure 1). There was a viral decline of 3.43 log10 copies/ml (range, 0.71 – 6.25) at week 8 of treatment. The median viral decline was 0.228 log10 copies/ml per day (range, -0.037 – 0.337) for the fi rst week of treatment and 0.055 log10 copies/ml per day (range, 0.010 – 0.127) between
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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 165 and 166: 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 and 214: INTRODUCTION HBV viral kinetics dur
Page 215: HBV viral kinetics during PEG-IFN 2
Page 219 and 220: 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
Page 265 and 266: 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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