Description
Book SynopsisThe goal of the book is to implement and compare different methods for quantifying the uncertainty in the probability of response, as a function of dose. Ultimately and ideally, this would be in a form compatible with integrated uncertainty analysis, comprising release, exposure, response, treatment cost, etc.
Table of ContentsAcknowledgments ix
Contributors xi
Introduction 1
Roger M. Cooke and Margaret MacDonell
1 Analysis of Dose–Response Uncertainty Using Benchmark Dose Modeling 17
Jeff Swartout
Comment: The Math/Stats Perspective on Chapter 1: Hard Problems Remain 34
Allan H. Marcus
Comment: EPI/TOX Perspective on Chapter 1: Re-formulating the Issues 37
Jouni T. Tuomisto
Comment: Regulatory/Risk Perspective on Chapter 1: A Good Baseline 42
Weihsueh Chiu
Comment: A Question Dangles 44
David Bussard
Comment: Statistical Test for Statistics-as-Usual Confi dence Bands 45
Roger M. Cooke
Response to Comments 47
Jeff Swartout
2 Uncertainty Quantifi cation for Dose–Response Models Using Probabilistic Inversion with Isotonic Regression: Bench Test Results 51
Roger M. Cooke
Comment: Math/Stats Perspective on Chapter 2: Agreement and Disagreement 82
Thomas A. Louis
Comment: EPI/TOX Perspective on Chapter 2: What Data Sets Per se Say 87
Lorenz Rhomberg
Comment: Regulatory/Risk Perspective on Chapter 2: Substantial Advances Nourish Hope for Clarity? 97
Rob Goble
Comment: A Weakness in the Approach? 105
Jouni T. Tuomisto
Response to Comments 107
Roger Cooke
3 Uncertainty Modeling in Dose Response Using Nonparametric Bayes: Bench Test Results 111
Lidia Burzala and Thomas A. Mazzuchi
Comment: Math/Stats Perspective on Chapter 3: Nonparametric Bayes 147
Roger M. Cooke
Comment: EPI/TOX View on Nonparametric Bayes: Dosing Precision 150
Chao W. Chen
Comment: Regulator/Risk Perspective on Chapter 3: Failure to Communicate 153
Dale Hattis
Response to Comments 160
Lidia Burzala
4 Quantifying Dose–Response Uncertainty Using Bayesian Model Averaging 165
Melissa Whitney and Louise Ryan
Comment: Math/Stats Perspective on Chapter 4: Bayesian Model Averaging 180
Michael Messner
Comment: EPI/TOX Perspective on Chapter 4: Use of Bayesian Model Averaging for Addressing Uncertainties in Cancer Dose–Response Modeling 183
Margaret Chu
Comment: Regulatorary/Risk Perspective on Chapter 4: Model Averages, Model Amalgams, and Model Choice 185
Adam M. Finkel
Response to Comments 194
Melissa Whitney and Louise Ryan
5 Combining Risks from Several Tumors Using Markov Chain Monte Carlo 197
Leonid Kopylev, John Fox, and Chao Chen
6 Uncertainty in Dose Response from the Perspective of Microbial Risk 207
P. F. M. Teunis
7 Conclusions 217
David Bussard, Peter Preuss, and Paul White
Author Index 225
Subject Index 229
