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Chapter 4.3 218 Table 2: Pharmacokinetic and viral kinetic parameters for the fi rst week of treatment for the 19 patients treated with PEG-IFN monotherapy. Pharmacokinetic parameters Viral kinetic parameters1 Patient ke ka F/Vd tmax Cmax EC50 AUC v0 decl. wk 1 c ε (day-1 ) (day-1 ) (pg/mL) (days) (pg/mL) (pg.wk/ mL) (log10cp/mL) (log10cp/mL) (day-1 ) 1 0.42 0.60 1.30 1.98 5630 5852 26415 9.30 0.20 0.97 0.49 3 0.48 2.73 1.80 0.77 12410 6485 35918 9.49 0.35 0.96 0.66 5 0.48 1.02 1.55 1.40 7940 6713 30267 10.04 -0.48 0.90 0.54 8 0.47 4.47 1.62 0.56 12430 1400 33228 9.06 0.30 0.80 0.89 9 0.55 2.93 1.86 0.70 12610 1480 32823 8.68 0.34 0.91 0.89 11 0.46 0.91 1.43 1.52 7160 3782 28890 8.69 0.53 0.77 0.65 12 0.43 1.34 1.31 1.25 7630 3969 28079 8.36 0.24 0.87 0.66 22 0.56 4.29 1.63 0.54 12020 276 28295 9.57 1.15 0.97 0.98 24 0.50 2.07 1.93 0.91 12300 2017 37259 8.65 0.71 0.55 0.86 27 0.37 2.08 0.88 1.01 6020 5881 21372 9.03 -0.28 1.43 0.50 29 0.55 1.14 2.43 1.24 12320 3717 42477 8.36 0.10 1.58 0.77 32 0.58 0.69 3.37 1.57 13500 9634 54171 10.26 0.07 1.09 0.58 39 0.39 4.43 0.65 0.60 5140 570 15541 9.30 0.69 1.05 0.90 41 0.36 1.09 0.76 1.52 4420 3844 18654 9.94 -0.07 1.09 0.54 43 0.45 1.23 1.43 1.29 8030 12684 29735 9.53 0.11 1.08 0.39 45 0.37 1.56 0.87 1.21 5540 1078 21063 9.13 0.42 1.26 0.84 50 0.58 3.34 1.83 0.64 12660 5325 31017 9.91 0.03 0.89 0.70 51 0.58 0.71 3.29 1.56 13360 5282 53428 8.85 -0.16 1.03 0.71 73 0.43 4.09 0.87 0.61 6690 3228 19105 10.03 0.17 0.87 0.67 Median 0.47 1.56 1.55 1.21 8030 3844 29735 9.30 0.20 0.97 0.67 Q 25 0.42 1.02 0.88 0.64 6020 1480 21372 8.69 0.06 0.87 0.54 Q 75 0.55 3.34 1.86 1.52 12430 5881 35918 9.91 0.39 1.09 0.86 decl. wk 1 = the decline in viral load in the fi rst week of treatment, Q = quartile 1Identical estimates for all patients (fi xed effects) were obtained for the pharmacokinetic time delay t0 (0.9 day), the infected cell loss rate δ (0.07 per day) and the Hill coeffi cient (n=1).
HBV viral kinetics during PEG-IFN 219 per patient AUC of the PEG-IFN α-2b concentration for the fi rst week of treatment and the body mass index (BMI) (p=.024) as well as a signifi cant relation between the AUC and sex; AUC was higher in females than in males (p=.002). Modelling of viral kinetics and its relation to pharmacokinetics and response Using the non-linear mixed model it was possible to fi t the fi rst month viral kinetics data in the PEG-IFN α-2b monotherapy arm (n = 19) using the results of the modelled pharmacokinetics for the fi rst month of treatment with ε dependant on time (Figure 3, Table 2). Thus, a clear biphasic viral load decline is not observed using PEG-IFN α-2b monotherapy in HBeAg-positive chronic hepatitis B patients. In the fi rst week, the modelled viral load was minimal at 3.6 days (2.8-4.5) after administration of PEG-IFN α-2b. The mean and maximum estimated population antiviral effectiveness εmean and εmax in patients receiving PEG-IFN α-2b monotherapy 48% and 70% (24-80% and 39 - 98%), respectively. The infected cell loss rate δ was estimated as 0.07 per day and the time delay of pharmacokinetics t0 as 0.9 days. No clear association was found between the estimated maximum antiviral effectiveness and baseline HBV DNA levels, ALT levels, sex and BMI. Maximal effectiveness but not mean effectiveness was signifi cantly smaller in older patients (p=0.046). HBeAg loss at the end of follow-up was observed in 9 out of 19 patients. Despite the correlation between the AUC of the PEG-IFN α-2b concentration and BMI and sex, no signifi cant difference was observed between the AUC in relation to treatment response (HBeAg loss at the end of follow-up) or viral decline at the end of treatment and followup. Furthermore, viral decline in the fi rst month of treatment was 0.45 log10 copies/ml (range -0.12 – 1.56) in patients with a lower than median AUC and also 0.45 log10 copies/ ml (range -0.03 – 1.87) in those with a higher than median AUC of the PEG-IFN α-2b concentration. DISCUSSION In this study, we analyzed early pharmacokinetics and HBV viral kinetics in HBeAg-positive chronic hepatitis B patients during the fi rst 4 weeks of treatment with PEG-IFN α-2b and used the PEG-IFN α-2b pharmacokinetics to model viral decline. We observed only a minimal decline in viral load during the fi rst month of PEG-IFN α-2b monotherapy, without a clear biphasic pattern. Given the fact that a signifi cant number of patients are able to control the infection after 52 week of PEG-IFN α-2b treatment, immunomodulatory
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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 169 and 170: 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 and 216: HBV viral kinetics during PEG-IFN 2
Page 219: 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
Page 267 and 268: Bibliography 265 Genetic characteri
Page 269: Bibliography 267 106. Reijnders JG,
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