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Statistical methods for dose-finding experiments /
edited by S. Chevret.
imprint
Chichester, West Sussex, England ; Hoboken, NJ : John Wiley and Sons, c2006.
description
xv, 315 p. : ill. ; 24 cm.
ISBN
0470861231 (hbk.)
format(s)
Book
Holdings
More Details
added author
series title
series title
imprint
Chichester, West Sussex, England ; Hoboken, NJ : John Wiley and Sons, c2006.
isbn
0470861231 (hbk.)
standard identifier
9780470861233
restrictions
Online version licensed for access by U. of T. users.
catalogue key
6032537
 
Includes bibliographical references and index.
A Look Inside
Reviews
Review Quotes
"It represents a good investment and would be a useful addition to the pharmaceutical researcher's library." ( Technometrics , August 2008) "This book will play an important role in establishing some of the recent innovative dose-finding methods in this fast evolving field." ( Journal of Biopharmaceutical Statistics , September 2007) "...very valuable to anyone working in the field...a very useful and complete textbook for graduate education." ( AIChE Journal , October 2007) "...an easily readable comprehensive compilation of several decades of work in dose finding designs and issues..." ( Journal of the American Statistical Association , September 2007)
"This book is an important collaboration of leading experts in the area. Primarily aimed at statisticians and clinicians working in clinical trials and medical research, there is also much to benefit graduate students of biostatistics." (Zentralblatt MATH, 2011) "It represents a good investment and would be a useful addition to the pharmaceutical researcher's library." ( Technometrics , August 2008) "This book will play an important role in establishing some of the recent innovative dose-finding methods in this fast evolving field." ( Journal of Biopharmaceutical Statistics , September 2007) "...very valuable to anyone working in the field...a very useful and complete textbook for graduate education." ( AIChE Journal , October 2007) "...an easily readable comprehensive compilation of several decades of work in dose finding designs and issues..." ( Journal of the American Statistical Association , September 2007)
"This book is an important collaboration of leading experts in the area. Primarily aimed at statisticians and clinicians working in clinical trials and medical research, there is also much to benefit graduate students of biostatistics." (Zentralblatt MATH, 2011) "It represents a good investment and would be a useful addition to the pharmaceutical researcher's library." ( Technometrics , August 2008) "This book will play an important role in establishing some of the recent innovative dose-finding methods in this fast evolving field." ( Journal of Biopharmaceutical Statistics , September 2007) "…very valuable to anyone working in the field...a very useful and complete textbook for graduate education." ( AIChE Journal , October 2007) "…an easily readable comprehensive compilation of several decades of work in dose finding designs and issues…" ( Journal of the American Statistical Association , September 2007)
"This book is an important collaboration of leading experts in the area. Primarily aimed at statisticians and clinicians working in clinical trials and medical research, there is also much to benefit graduate students of biostatistics." (Zentralblatt MATH, 2011) "It represents a good investment and would be a useful addition to the pharmaceutical researchers library." ( Technometrics , August 2008) "This book will play an important role in establishing some of the recent innovative dose-finding methods in this fast evolving field." ( Journal of Biopharmaceutical Statistics , September 2007) "…very valuable to anyone working in the field...a very useful and complete textbook for graduate education." ( AIChE Journal , October 2007) "…an easily readable comprehensive compilation of several decades of work in dose finding designs and issues…" ( Journal of the American Statistical Association , September 2007)
To find out how to look for other reviews, please see our guides to finding book reviews in the Sciences or Social Sciences and Humanities.
Summaries
Long Description
Dose-finding experiments define the safe dosage of a drug in development, in terms of the quantity given to a patient. Statistical methods play a crucial role in identifying optimal dosage. Used appropriately, these methods provide reliable results and reduce trial duration and costs. In practice, however, dose-finding is often done poorly, with widely used conventional methods frequently being unreliable, leading to inaccurate results. However, there have been many advances in recent years, with new statistical techniques being developed and it is important that these new techniques are utilized correctly. Statistical Methods for Dose-Finding Experiments reviews the main statistical approaches for dose-finding in phase I/II clinical trials and presents practical guidance on their correct use. Includes an introductory section, summarizing the essential concepts in dose-finding. Contains a section on algorithm-based approaches, such as the traditional 3+3 design, and a section on model-based approaches, such as the continual reassessment method. Explains fundamental issues, such as how to stop trials early and how to cope with delayed or ordinal outcomes. Discusses in detail the main websites and software used to implement the methods. Features numerous worked examples making use of real data. Statistical Methods for Dose-Finding Experiments is an important collaboration from the leading experts in the area. Primarily aimed at statisticians and clinicians working in clinical trials and medical research, there is also much to benefit graduate students of biostatistics.
Table of Contents
Contributorsp. xiii
Prefacep. xv
Introductionp. 1
General Principles and Controversial Issues in Dose-Findingsp. 3
Basic concepts in dose-findingp. 5
Main conceptsp. 5
Main issues from a pharmaceutical point of viewp. 7
Statistical issues of dose-finding phase I trialsp. 7
Ethical concernsp. 8
Designp. 9
Inferencep. 11
Conclusionp. 14
Referencesp. 15
Philosophy and methodology of dose-finding - a regulatory perspectivep. 19
Introductionp. 19
In search of the optimal dosep. 22
What is an optimal dose?p. 22
When to determine the dose and duration of treatment?p. 23
Limitations of clinical trialsp. 24
Identification of the therapeutic windowp. 28
How many dose levels should be licensed?p. 29
Determining the duration of treatmentp. 34
Regulatory requirements for drug licensurep. 39
Introductionp. 39
The product licencep. 40
ICH E4p. 41
Benefits to the sponsor and the patient of providing data on dose-response over and above those required for licensingp. 43
Increasing the likelihood that the product is a successp. 43
Achieving consistent posology worldwidep. 45
Trial designs for determining dose-responsep. 45
Introductionp. 45
Issues relating to the design of a dose-response programmep. 46
Designing a dose-finding trial for monotherapyp. 47
Designing a dose-finding trial for a combination productp. 49
Use of 'adaptive designs' in dose-responsep. 50
Discussionp. 53
Referencesp. 55
Algorithm-Based Approachesp. 59
Traditional and modified algorithm-based designs for phase I cancer clinical trialsp. 61
Introductionp. 61
Notation and conventionp. 62
Traditional algorithm-based designsp. 63
Traditional A + B design without dose de-escalationp. 63
Traditional A + B design with dose de-escalationp. 64
Modified algorithm-based designsp. 65
M1 A + B designp. 65
M2 A + B designp. 67
M3 A + B designp. 68
Probability of a dose being chosen as the MTDp. 69
M1 A + B designp. 70
M2 A + B designp. 71
M3 A + B designp. 72
Expected number of patients treated at each dose levelp. 74
M1 A + B designp. 75
M2 A + B designp. 76
M3 A + B designp. 77
Other statistical propertiesp. 80
Examplesp. 81
Example 1: M1 3 + 2 design without dose de-escalationp. 81
Example 2: M2 3 + 3 design with dose de-escalationp. 81
Example 3: M3 3 + 3 design without dose de-escalationp. 83
Discussionp. 87
Acknowledgmentsp. 89
Referencesp. 89
Accelerated titration designsp. 91
Introductionp. 91
Designp. 92
Intrapatient dose-escalationp. 94
Evaluation of performancep. 94
Model-based analysisp. 97
Clinical applicationsp. 100
Conclusionsp. 108
Referencesp. 109
Group up-and-down designs in toxicity studiesp. 115
Introductionp. 115
Group up-and-down designs for phase I clinical trialsp. 116
Designs for acute toxicity studiesp. 120
Fully sequential designs for phase I clinical trialsp. 121
Start-up rulesp. 122
Estimationp. 124
The empirical mean estimatorp. 124
The mode of the treatment distributionp. 124
The maximum likelihood estimator (MLE)p. 124
The isotonic regression-based estimatorp. 125
Up-and-down designs to find the dose with maximum success probabilityp. 126
An optimizing up-and-down designp. 126
A balancing up-and-down designp. 127
Discussionp. 127
Referencesp. 128
Model-Based Approachesp. 131
The continual reassessment methodp. 133
Introductionp. 133
The original continual reassessment method (CRM)p. 134
Trial planificationp. 134
Design and inferencep. 137
Inferencep. 137
Practical considerationsp. 139
CRM for phase II dose-finding studiesp. 140
Examplep. 140
Likelihood CRM (CRML)p. 140
Modified continual reassessment method (MCRM)p. 142
Modifications in designp. 142
Modifications in modelling the dose-response relationshipp. 143
Examplep. 145
Concluding remarksp. 145
Referencesp. 146
Using Bayesian decision theory in dose-escalation studiesp. 149
Introductionp. 149
Example of a dose-escalation studyp. 151
A statistical model for the studyp. 152
Prior informationp. 156
Gain functionsp. 159
Safety constraints and stopping rulesp. 164
Evaluation of the Bayesian approachp. 166
Discussionp. 168
Referencesp. 170
Dose-escalation with overdose controlp. 173
Introductionp. 173
Escalation with overdose control designp. 175
EWOC designp. 175
Examplep. 177
Adjusting for covariatesp. 178
Modelp. 178
Examplep. 180
Choice of prior distributionsp. 182
Independent priorsp. 183
Correlated priorsp. 184
Simulationsp. 186
Concluding remarksp. 186
Referencesp. 187
Dose-escalation methods for phase I healthy volunteer studiesp. 189
Introductionp. 189
Frequentist analysisp. 191
A Bayesian analysisp. 194
Conducting dose-escalation using a Bayesian decision-theoretic approachp. 197
Multiple simulationsp. 200
Conclusionsp. 202
Acknowledgementsp. 203
Referencesp. 203
Future Trends for Past Issuesp. 205
Defining stopping rulesp. 207
Introductionp. 207
Backgroundp. 208
Dose-finding specificitiesp. 209
Algorithm-based stopping rulesp. 211
Model-based stopping rules: frequentist approachesp. 211
Model-based stopping rules: Bayesian approachesp. 212
Examplesp. 214
The Nalmefene trialp. 214
The Prantal trialp. 216
The nitroglycerin trialp. 218
Conclusionsp. 221
Acknowledgmentp. 221
Referencesp. 221
Dose-finding with delayed binary outcomes in cancer trialsp. 225
Introductionp. 225
Review of current practicep. 227
Group CRMp. 227
Look-ahead methodsp. 227
Time-to-event methodsp. 228
Basic methodsp. 228
The CRMp. 228
The TITE-CRMp. 228
A dose-adjusted weightp. 229
An examplep. 230
Intensity modulated radiation therapy (IMRT)p. 230
A single trialp. 231
Weight calculationp. 233
Simulation resultsp. 234
The IMRT scenariosp. 235
The late-onset scenariosp. 237
Practical guidelinesp. 237
Chronic toxicitiesp. 239
Discussionp. 240
Bibliographic notesp. 240
Referencesp. 241
Dose-finding based on multiple ordinal toxicities in phase I oncology trialsp. 243
Introductionp. 243
Probability modelp. 245
Dose-finding algorithmp. 247
Elicitation processp. 248
Application to the sarcoma trialp. 249
Simulation study and sensitivity analysesp. 251
Simulation study designp. 251
Simulation resultsp. 253
Sensitivity analysesp. 255
Concluding remarksp. 257
Referencesp. 258
A two-stage design for dose-finding with two agentsp. 259
Introductionp. 259
Dose-toxicity modelp. 261
Toxicity probabilitiesp. 261
Establishing priorsp. 262
A two-stage dose-finding algorithmp. 264
Geometry of L[subscript 1] and L[subscript 2]p. 264
Dose-finding algorithmp. 265
Criteria for stage 2p. 266
Computingp. 267
Applicationp. 267
Discussionp. 273
Referencesp. 273
Using both efficacy and toxicity for dose-findingp. 275
Introductionp. 275
Illustrative trialp. 276
Dose-outcome modelsp. 276
Bivariate binary probability distributionsp. 276
Priors and posteriorsp. 277
The dose-finding algorithmp. 278
Acceptability limitsp. 278
Trade-off contoursp. 279
The algorithmp. 281
Simulation studiesp. 281
Discussionp. 284
Referencesp. 285
Conclusionsp. 287
Websites and softwarep. 289
Introductionp. 289
Computation methods using statistical softwarep. 290
Phase I or phase II dose-finding softwarep. 293
Software for the continual reassessment method and its modificationsp. 293
Bayesian ADEPT: assisted decision making in early phase trialsp. 298
ATDPH1: accelerated titration designs for phase I clinical trialsp. 298
PMTD: traditional algorithm-based designs for phase Ip. 300
EWOC: escalation with overdose controlp. 301
Phase I/II dose-finding softwarep. 302
EFFTOX2p. 302
Conclusionsp. 305
Referencesp. 305
Random numbers generationp. 306
Indexp. 307
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