Bayesian designs for phase I-II clinical trials

316 Pages·2016·25.638 MB·English

by  Nguyen, Hoang Q., Thall, Peter F., Yuan, Ying

Statistics
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Bayesian Designs for Phase I–II Clinical Trials presents a wide variety
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of Bayesian designs for human clinical trials of new experimental treat- e
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ment regimes. It describes how phase I–II designs can serve as a bridge
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or protective barrier between preclinical studies and large confirmatory Bayesian Designs
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clinical trials.

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The first two chapters minimize the technical language to make them ac- e
for Phase I–II
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cessible to non-statisticians. These chapters discuss many severe draw-
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backs of the conventional paradigm used for early-phase clinical trials
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and explain the phase I–II paradigm for optimizing dose, or more general
s Clinical Trials
treatment regimes, based on both efficacy and toxicity. The remainder of
f
o
the book covers a wide variety of clinical trial methodologies, including
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designs to optimize the dose pair of a two-drug combination, jointly op-
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timize dose and schedule, identify optimal personalized doses, optimize
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novel molecularly targeted agents, and choose doses in two treatment a
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cycles.
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Features I
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• Represents the first book to focus on Bayesian phase I–II clinical I
I
trials
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• Examines the problems with the conventional phase I–phase II l
i
paradigm n
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• Covers a large number of modern Bayesian phase I–II clinical trial c
a
designs
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• Presents many real applications and numerical examples T
• Describes methods for establishing priors from elicited values r
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• Explains the essentials of utility-based clinical trial design
l
s
• Provides software for some of the designs on a supplementary
website
Written by research leaders from the University of Texas MD Anderson Y
u
Cancer Center, this book shows how Bayesian designs for early-phase a
n Ying Yuan
clinical trials can explore, refine, and optimize new experimental treat- T
•
ments. It emphasizes the importance of basing decisions on both ef- ha N Hoang Q. Nguyen
l g
ficacy and toxicity. l
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Peter F. Thall
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K24998 e
n
www.crcpress.com
K24998_cover.indd 1 4/18/16 9:34 AM
Bayesian Designs
for Phase I–II
Clinical Trials
Ying Yuan
The University of Texas
MD Anderson Cancer Center
Houston, Texas, USA
Hoang Q. Nguyen
The University of Texas
MD Anderson Cancer Center
Houston, Texas, USA
Peter F. Thall
The University of Texas
MD Anderson Cancer Center
Houston, Texas, USA
Editor-in-Chief
Shein-Chung Chow, Ph.D., Professor, Department of Biostatistics and Bioinformatics,
Duke University School of Medicine, Durham, North Carolina
Series Editors
Byron Jones, Biometrical Fellow, Statistical Methodology, Integrated Information Sciences,
Novartis Pharma AG, Basel, Switzerland
Jen-pei Liu, Professor, Division of Biometry, Department of Agronomy,
National Taiwan University, Taipei, Taiwan
Karl E. Peace, Georgia Cancer Coalition, Distinguished Cancer Scholar, Senior Research Scientist
and Professor of Biostatistics, Jiann-Ping Hsu College of Public Health,
Georgia Southern University, Statesboro, Georgia
Bruce W. Turnbull, Professor, School of Operations Research and Industrial Engineering,
Cornell University, Ithaca, New York
Published Titles
Adaptive Design Methods in Clinical Bayesian Analysis Made Simple:
Trials, Second Edition An Excel GUI for WinBUGS
Shein-Chung Chow and Mark Chang Phil Woodward
Adaptive Designs for Sequential Bayesian Designs for Phase I–II
Treatment Allocation Clinical Trials
Alessandro Baldi Antognini Ying Yuan, Hoang Q. Nguyen,
and Alessandra Giovagnoli and Peter F. Thall
Adaptive Design Theory and Bayesian Methods for Measures
Implementation Using SAS and R, of Agreement
Second Edition Lyle D. Broemeling
Mark Chang
Bayesian Methods for Repeated Measures
Advanced Bayesian Methods for Lyle D. Broemeling
Medical Test Accuracy
Bayesian Methods in Epidemiology
Lyle D. Broemeling
Lyle D. Broemeling
Applied Biclustering Methods for Big
Bayesian Methods in Health Economics
and High-Dimensional Data Using R
Gianluca Baio
Adetayo Kasim, Ziv Shkedy,
Bayesian Missing Data Problems: EM,
Sebastian Kaiser, Sepp Hochreiter,
Data Augmentation and Noniterative
and Willem Talloen
Computation
Applied Meta-Analysis with R
Ming T. Tan, Guo-Liang Tian,
Ding-Geng (Din) Chen and Karl E. Peace
and Kai Wang Ng
Basic Statistics and Pharmaceutical
Bayesian Modeling in Bioinformatics
Statistical Applications, Second Edition
Dipak K. Dey, Samiran Ghosh,
James E. De Muth
and Bani K. Mallick
Bayesian Adaptive Methods for
Benefit-Risk Assessment in
Clinical Trials
Pharmaceutical Research and
Scott M. Berry, Bradley P. Carlin,
Development
J. Jack Lee, and Peter Muller
Andreas Sashegyi, James Felli,
and Rebecca Noel
Published Titles
Benefit-Risk Assessment Methods in Design and Analysis of Bioavailability
Medical Product Development: Bridging and Bioequivalence Studies, Third Edition
Qualitative and Quantitative Assessments Shein-Chung Chow and Jen-pei Liu
Qi Jiang and Weili He
Design and Analysis of Bridging Studies
Biosimilars: Design and Analysis of Jen-pei Liu, Shein-Chung Chow,
Follow-on Biologics and Chin-Fu Hsiao
Shein-Chung Chow
Design & Analysis of Clinical Trials for
Biostatistics: A Computing Approach Economic Evaluation & Reimbursement:
Stewart J. Anderson An Applied Approach Using SAS & STATA
Iftekhar Khan
Cancer Clinical Trials: Current and
Controversial Issues in Design and Design and Analysis of Clinical Trials
Analysis for Predictive Medicine
Stephen L. George, Xiaofei Wang, Shigeyuki Matsui, Marc Buyse,
and Herbert Pang and Richard Simon
Causal Analysis in Biomedicine and Design and Analysis of Clinical Trials with
Epidemiology: Based on Minimal Time-to-Event Endpoints
Sufficient Causation Karl E. Peace
Mikel Aickin
Design and Analysis of Non-Inferiority Trials
Clinical and Statistical Considerations in Mark D. Rothmann, Brian L. Wiens,
Personalized Medicine and Ivan S. F. Chan
Claudio Carini, Sandeep Menon, and Mark Chang
Difference Equations with Public Health
Clinical Trial Data Analysis using R Applications
Ding-Geng (Din) Chen and Karl E. Peace Lemuel A. Moyé and Asha Seth Kapadia
Clinical Trial Methodology DNA Methylation Microarrays:
Karl E. Peace and Ding-Geng (Din) Chen Experimental Design and Statistical
Analysis
Computational Methods in Biomedical
Sun-Chong Wang and Arturas Petronis
Research
Ravindra Khattree and Dayanand N. Naik DNA Microarrays and Related Genomics
Techniques: Design, Analysis, and
Computational Pharmacokinetics
Interpretation of Experiments
Anders Källén
David B. Allison, Grier P. Page,
Confidence Intervals for Proportions
T. Mark Beasley, and Jode W. Edwards
and Related Measures of Effect Size
Dose Finding by the Continual
Robert G. Newcombe
Reassessment Method
Controversial Statistical Issues in
Ying Kuen Cheung
Clinical Trials
Dynamical Biostatistical Models
Shein-Chung Chow
Daniel Commenges and
Data Analysis with Competing Risks
Hélène Jacqmin-Gadda
and Intermediate States
Elementary Bayesian Biostatistics
Ronald B. Geskus
Lemuel A. Moyé
Data and Safety Monitoring Committees
Empirical Likelihood Method in
in Clinical Trials
Survival Analysis
Jay Herson
Mai Zhou
Design and Analysis of Animal Studies
Exposure–Response Modeling: Methods
in Pharmaceutical Development
and Practical Implementation
Shein-Chung Chow and Jen-pei Liu
Jixian Wang
Published Titles
Frailty Models in Survival Analysis Monte Carlo Simulation for the
Andreas Wienke Pharmaceutical Industry: Concepts,
Algorithms, and Case Studies
Fundamental Concepts for New Clinical
Mark Chang
Trialists
Scott Evans and Naitee Ting Multiregional Clinical Trials for
Generalized Linear Models: A Bayesian Simultaneous Global New Drug
Perspective Development
Dipak K. Dey, Sujit K. Ghosh, and Joshua Chen and Hui Quan
Bani K. Mallick Multiple Testing Problems in
Handbook of Regression and Modeling: Pharmaceutical Statistics
Applications for the Clinical and Alex Dmitrienko, Ajit C. Tamhane,
Pharmaceutical Industries and Frank Bretz
Daryl S. Paulson Noninferiority Testing in Clinical Trials:
Inference Principles for Biostatisticians Issues and Challenges
Ian C. Marschner Tie-Hua Ng
Interval-Censored Time-to-Event Data: Optimal Design for Nonlinear Response
Methods and Applications Models
Ding-Geng (Din) Chen, Jianguo Sun, Valerii V. Fedorov and Sergei L. Leonov
and Karl E. Peace Patient-Reported Outcomes:
Introductory Adaptive Trial Designs: Measurement, Implementation and
A Practical Guide with R Interpretation
Mark Chang Joseph C. Cappelleri, Kelly H. Zou,
Andrew G. Bushmakin, Jose Ma. J. Alvir,
Joint Models for Longitudinal and Time-
Demissie Alemayehu, and Tara Symonds
to-Event Data: With Applications in R
Dimitris Rizopoulos Quantitative Evaluation of Safety in Drug
Development: Design, Analysis and
Measures of Interobserver Agreement
Reporting
and Reliability, Second Edition
Qi Jiang and H. Amy Xia
Mohamed M. Shoukri
Quantitative Methods for Traditional
Medical Biostatistics, Third Edition
Chinese Medicine Development
A. Indrayan
Shein-Chung Chow
Meta-Analysis in Medicine and
Randomized Clinical Trials of
Health Policy
Nonpharmacological Treatments
Dalene Stangl and Donald A. Berry
Isabelle Boutron, Philippe Ravaud,
Mixed Effects Models for the Population
and David Moher
Approach: Models, Tasks, Methods
Randomized Phase II Cancer
and Tools
Clinical Trials
Marc Lavielle
Sin-Ho Jung
Modeling to Inform Infectious Disease
Sample Size Calculations for Clustered
Control
and Longitudinal Outcomes in Clinical
Niels G. Becker
Research
Modern Adaptive Randomized Clinical
Chul Ahn, Moonseong Heo,
Trials: Statistical and Practical Aspects
and Song Zhang
Oleksandr Sverdlov
Published Titles
Sample Size Calculations in Clinical Statistical Methods in Drug Combination
Research, Second Edition Studies
Shein-Chung Chow, Jun Shao, Wei Zhao and Harry Yang
and Hansheng Wang
Statistical Testing Strategies in the
Statistical Analysis of Human Growth Health Sciences
and Development Albert Vexler, Alan D. Hutson,
Yin Bun Cheung and Xiwei Chen
Statistical Design and Analysis of Clinical Statistics in Drug Research:
Trials: Principles and Methods Methodologies and Recent
Weichung Joe Shih and Joseph Aisner Developments
Shein-Chung Chow and Jun Shao
Statistical Design and Analysis of
Stability Studies Statistics in the Pharmaceutical Industry,
Shein-Chung Chow Third Edition
Ralph Buncher and Jia-Yeong Tsay
Statistical Evaluation of Diagnostic
Performance: Topics in ROC Analysis Survival Analysis in Medicine and
Kelly H. Zou, Aiyi Liu, Andriy Bandos, Genetics
Lucila Ohno-Machado, and Howard Rockette Jialiang Li and Shuangge Ma
Statistical Methods for Clinical Trials Theory of Drug Development
Mark X. Norleans Eric B. Holmgren
Statistical Methods for Drug Safety Translational Medicine: Strategies and
Robert D. Gibbons and Anup K. Amatya Statistical Methods
Dennis Cosmatos and Shein-Chung Chow
Statistical Methods for Immunogenicity
Assessment
Harry Yang, Jianchun Zhang, Binbing Yu,
and Wei Zhao
CRC Press
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This book is dedicated to all the patients who suffered more than
they should have, or who died sooner than they might have,
because they were given suboptimal treatments.
To my wife Suyu and daughter Selina.
Ying Yuan
To the Lord our God who made it all possible.
Hoang Nguyen
I am grateful to Ying for inviting me to collaborate on this book.
Peter Thall

Contents
Preface xiii
1 Why Conduct Phase I–II Trials? 1
1.1 The Conventional Paradigm . . . . . . . . . . . . . . . . . . 1
1.2 The Continual Reassessment Method . . . . . . . . . . . . . 5
1.3 Problems with Conventional Dose-Finding Methods . . . . . 8
1.3.1 3+3 Algorithms. . . . . . . . . . . . . . . . . . . . . . 8
1.3.2 Some Comparisons . . . . . . . . . . . . . . . . . . . . 10
1.3.3 Problems Going from Phase I to Phase II . . . . . . . 18
1.3.4 Consequences of Ignoring Information . . . . . . . . . 19
1.3.5 Late-Onset Outcomes . . . . . . . . . . . . . . . . . . 22
1.3.6 Expansion Cohorts . . . . . . . . . . . . . . . . . . . . 23
1.3.7 Guessing a Schedule . . . . . . . . . . . . . . . . . . . 25
1.3.8 Patient Heterogeneity . . . . . . . . . . . . . . . . . . 26
2 The Phase I–II Paradigm 29
2.1 Efficacy and Toxicity . . . . . . . . . . . . . . . . . . . . . . 29
2.2 Elements of Phase I–II Designs . . . . . . . . . . . . . . . . . 30
2.3 Treatment Regimes and Clinical Outcomes . . . . . . . . . . 31
2.4 Sequentially Adaptive Decision Making . . . . . . . . . . . . 33
2.5 Risk–Benefit Trade-Offs . . . . . . . . . . . . . . . . . . . . . 35
2.6 Stickiness and Adaptive Randomization . . . . . . . . . . . . 37
2.7 Simulation as a Design Tool . . . . . . . . . . . . . . . . . . 41
3 Establishing Priors 43
3.1 Pathological Priors . . . . . . . . . . . . . . . . . . . . . . . 43
3.2 Prior Effective Sample Size . . . . . . . . . . . . . . . . . . . 46
3.3 Computing Priors from Elicited Values . . . . . . . . . . . . 50
3.3.1 Least Squares Algorithm. . . . . . . . . . . . . . . . . 54
3.3.2 Pseudo Sampling Algorithm . . . . . . . . . . . . . . . 55
ix