Clinical Trial Optimization Using R

338 Pages·2017·4.598 MB·English

by  Alex Dmitrienko, Erik Pulkstenis

Clinical Trial
Optimization
Using R
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 Basic Statistics and Pharmaceutical
Trials, Second Edition Statistical Applications, Second Edition
Shein-Chung Chow and Mark Chang James E. De Muth
Adaptive Designs for Sequential Bayesian Adaptive Methods for
Treatment Allocation Clinical Trials
Alessandro Baldi Antognini Scott M. Berry, Bradley P. Carlin,
and Alessandra Giovagnoli J. Jack Lee, and Peter Muller
Adaptive Design Theory and Bayesian Analysis Made Simple:
Implementation Using SAS and R, An Excel GUI for WinBUGS
Second Edition Phil Woodward
Mark Chang
Bayesian Designs for Phase I–II
Advanced Bayesian Methods for Clinical Trials
Medical Test Accuracy Ying Yuan, Hoang Q. Nguyen,
Lyle D. Broemeling and Peter F. Thall
Analyzing Longitudinal Clinical Trial Data: Bayesian Methods for Measures
A Practical Guide of Agreement
Craig Mallinckrodt and Ilya Lipkovich Lyle D. Broemeling
Applied Biclustering Methods for Big Bayesian Methods for Repeated Measures
and High-Dimensional Data Using R Lyle D. Broemeling
Adetayo Kasim, Ziv Shkedy,
Bayesian Methods in Epidemiology
Sebastian Kaiser, Sepp Hochreiter,
Lyle D. Broemeling
and Willem Talloen
Bayesian Methods in Health Economics
Applied Meta-Analysis with R
Gianluca Baio
Ding-Geng (Din) Chen and Karl E. Peace
Bayesian Missing Data Problems: EM,
Applied Surrogate Endpoint Evaluation
Data Augmentation and Noniterative
Methods with SAS and R
Computation
Ariel Alonso, Theophile Bigirumurame,
Ming T. Tan, Guo-Liang Tian,
Tomasz Burzykowski, Marc Buyse,
and Kai Wang Ng
Geert Molenberghs, Leacky Muchene,
Nolen Joy Perualila, Ziv Shkedy,
and Wim Van der Elst
Published Titles
Bayesian Modeling in Bioinformatics Clinical Trial Optimization Using R
Dipak K. Dey, Samiran Ghosh, Alex Dmitrienko and Erik Pulkstenis
and Bani K. Mallick
Computational Methods in Biomedical
Benefit-Risk Assessment in Research
Pharmaceutical Research and Ravindra Khattree and Dayanand N. Naik
Development
Computational Pharmacokinetics
Andreas Sashegyi, James Felli,
Anders Källén
and Rebecca Noel
Confidence Intervals for Proportions
Benefit-Risk Assessment Methods in
and Related Measures of Effect Size
Medical Product Development: Bridging
Robert G. Newcombe
Qualitative and Quantitative Assessments
Controversial Statistical Issues in
Qi Jiang and Weili He
Clinical Trials
Bioequivalence and Statistics in Clinical
Shein-Chung Chow
Pharmacology, Second Edition
Data Analysis with Competing Risks
Scott Patterson and Byron Jones
and Intermediate States
Biosimilar Clinical Development:
Ronald B. Geskus
Scientific Considerations and New
Data and Safety Monitoring Committees
Methodologies
in Clinical Trials, Second Edition
Kerry B. Barker, Sandeep M. Menon,
Jay Herson
Ralph B. D’Agostino, Sr., Siyan Xu, and Bo Jin
Design and Analysis of Animal Studies
Biosimilars: Design and Analysis of
in Pharmaceutical Development
Follow-on Biologics
Shein-Chung Chow and Jen-pei Liu
Shein-Chung Chow
Design and Analysis of Bioavailability
Biostatistics: A Computing Approach
and Bioequivalence Studies, Third Edition
Stewart J. Anderson
Shein-Chung Chow and Jen-pei Liu
Cancer Clinical Trials: Current and
Design and Analysis of Bridging Studies
Controversial Issues in Design and
Jen-pei Liu, Shein-Chung Chow,
Analysis
and Chin-Fu Hsiao
Stephen L. George, Xiaofei Wang,
and Herbert Pang Design & Analysis of Clinical Trials for
Economic Evaluation & Reimbursement:
Causal Analysis in Biomedicine and
An Applied Approach Using SAS & STATA
Epidemiology: Based on Minimal
Iftekhar Khan
Sufficient Causation
Mikel Aickin Design and Analysis of Clinical Trials
for Predictive Medicine
Clinical and Statistical Considerations in
Shigeyuki Matsui, Marc Buyse,
Personalized Medicine
and Richard Simon
Claudio Carini, Sandeep Menon, and Mark Chang
Design and Analysis of Clinical Trials with
Clinical Trial Data Analysis Using R
Time-to-Event Endpoints
Ding-Geng (Din) Chen and Karl E. Peace
Karl E. Peace
Clinical Trial Data Analysis Using R and SAS,
Design and Analysis of Non-Inferiority Trials
Second Edition
Mark D. Rothmann, Brian L. Wiens,
Ding-Geng (Din) Chen, Karl E. Peace,
and Ivan S. F. Chan
and Pinggao Zhang
Difference Equations with Public Health
Clinical Trial Methodology
Applications
Karl E. Peace and Ding-Geng (Din) Chen
Lemuel A. Moyé and Asha Seth Kapadia
Published Titles
DNA Methylation Microarrays: Interval-Censored Time-to-Event Data:
Experimental Design and Statistical Methods and Applications
Analysis Ding-Geng (Din) Chen, Jianguo Sun,
Sun-Chong Wang and Arturas Petronis and Karl E. Peace
DNA Microarrays and Related Genomics Introductory Adaptive Trial Designs:
Techniques: Design, Analysis, and A Practical Guide with R
Interpretation of Experiments Mark Chang
David B. Allison, Grier P. Page,
Joint Models for Longitudinal and Time-
T. Mark Beasley, and Jode W. Edwards
to-Event Data: With Applications in R
Dose Finding by the Continual Dimitris Rizopoulos
Reassessment Method
Measures of Interobserver Agreement
Ying Kuen Cheung
and Reliability, Second Edition
Dynamical Biostatistical Models Mohamed M. Shoukri
Daniel Commenges and
Medical Biostatistics, Third Edition
Hélène Jacqmin-Gadda
A. Indrayan
Elementary Bayesian Biostatistics
Meta-Analysis in Medicine and
Lemuel A. Moyé
Health Policy
Emerging Non-Clinical Biostatistics in Dalene Stangl and Donald A. Berry
Biopharmaceutical Development and
Methods in Comparative Effectiveness
Manufacturing
Research
Harry Yang
Constantine Gatsonis and Sally C. Morton
Empirical Likelihood Method in
Mixed Effects Models for the Population
Survival Analysis
Approach: Models, Tasks, Methods
Mai Zhou
and Tools
Essentials of a Successful Biostatistical Marc Lavielle
Collaboration
Modeling to Inform Infectious Disease
Arul Earnest
Control
Exposure–Response Modeling: Methods Niels G. Becker
and Practical Implementation
Modern Adaptive Randomized Clinical
Jixian Wang
Trials: Statistical and Practical Aspects
Frailty Models in Survival Analysis Oleksandr Sverdlov
Andreas Wienke
Monte Carlo Simulation for the
Fundamental Concepts for New Clinical Pharmaceutical Industry: Concepts,
Trialists Algorithms, and Case Studies
Scott Evans and Naitee Ting Mark Chang
Generalized Linear Models: A Bayesian Multiregional Clinical Trials for
Perspective Simultaneous Global New Drug
Dipak K. Dey, Sujit K. Ghosh, and Development
Bani K. Mallick Joshua Chen and Hui Quan
Handbook of Regression and Modeling: Multiple Testing Problems in
Applications for the Clinical and Pharmaceutical Statistics
Pharmaceutical Industries Alex Dmitrienko, Ajit C. Tamhane,
Daryl S. Paulson and Frank Bretz
Inference Principles for Biostatisticians
Ian C. Marschner
Published Titles
Noninferiority Testing in Clinical Trials: Statistical Design and Analysis of Clinical
Issues and Challenges Trials: Principles and Methods
Tie-Hua Ng Weichung Joe Shih and Joseph Aisner
Optimal Design for Nonlinear Response Statistical Design and Analysis of
Models Stability Studies
Valerii V. Fedorov and Sergei L. Leonov Shein-Chung Chow
Patient-Reported Outcomes: Statistical Evaluation of Diagnostic
Measurement, Implementation and Performance: Topics in ROC Analysis
Interpretation Kelly H. Zou, Aiyi Liu, Andriy Bandos,
Joseph C. Cappelleri, Kelly H. Zou, Lucila Ohno-Machado, and Howard Rockette
Andrew G. Bushmakin, Jose Ma. J. Alvir,
Statistical Methods for Clinical Trials
Demissie Alemayehu, and Tara Symonds
Mark X. Norleans
Quantitative Evaluation of Safety in Drug
Statistical Methods for Drug Safety
Development: Design, Analysis and
Robert D. Gibbons and Anup K. Amatya
Reporting
Statistical Methods for Healthcare
Qi Jiang and H. Amy Xia
Performance Monitoring
Quantitative Methods for Traditional
Alex Bottle and Paul Aylin
Chinese Medicine Development
Statistical Methods for Immunogenicity
Shein-Chung Chow
Assessment
Randomized Clinical Trials of
Harry Yang, Jianchun Zhang, Binbing Yu,
Nonpharmacological Treatments
and Wei Zhao
Isabelle Boutron, Philippe Ravaud,
Statistical Methods in Drug Combination
and David Moher
Studies
Randomized Phase II Cancer
Wei Zhao and Harry Yang
Clinical Trials
Statistical Testing Strategies in the
Sin-Ho Jung
Health Sciences
Repeated Measures Design with
Albert Vexler, Alan D. Hutson,
Generalized Linear Mixed Models for
and Xiwei Chen
Randomized Controlled Trials
Statistics in Drug Research:
Toshiro Tango
Methodologies and Recent
Sample Size Calculations for Clustered
Developments
and Longitudinal Outcomes in Clinical
Shein-Chung Chow and Jun Shao
Research
Statistics in the Pharmaceutical Industry,
Chul Ahn, Moonseong Heo,
Third Edition
and Song Zhang
Ralph Buncher and Jia-Yeong Tsay
Sample Size Calculations in Clinical
Survival Analysis in Medicine and
Research, Second Edition
Genetics
Shein-Chung Chow, Jun Shao,
Jialiang Li and Shuangge Ma
and Hansheng Wang
Theory of Drug Development
Statistical Analysis of Human Growth
Eric B. Holmgren
and Development
Yin Bun Cheung Translational Medicine: Strategies and
Statistical Methods
Dennis Cosmatos and Shein-Chung Chow

Clinical Trial
Optimization
Using R
Edited by
Alex Dmitrienko
Erik Pulkstenis
Harry Yang
CRC Press
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Library of Congress Cataloging‑in‑Publication Data
Names: Dmitrienko, Alex. | Pulkstenis, Erik.
Title: Clinical trial optimization using R / Alex Dmitrienko, Erik Pulkstenis.
Description: Boca Raton : CRC Press, 2017. | Includes bibliographical
references and index.
Identifiers: LCCN 2016057709 | ISBN 9781498735070 (hardback : alk. paper)
Subjects: LCSH: Clinical trials--Statistical methods. | R (Computer program language)
Classification: LCC R853.C55 D6525 2017 | DDC 610.72/7--dc23
LC record available at https://lccn.loc.gov/2016057709
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Contents
Preface xiii
List of Contributors xvii
1 Clinical Scenario Evaluation and Clinical Trial Optimization 1
Alex Dmitrienko and Gautier Paux
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Clinical Scenario Evaluation . . . . . . . . . . . . . . . . . . 2
1.2.1 Components of Clinical Scenario Evaluation . . . . . . 2
1.2.2 Software implementation . . . . . . . . . . . . . . . . 4
1.2.3 Casestudy1.1: Clinicaltrialwithanormallydistributed
endpoint . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.2.4 Case study 1.2: Clinical trial with two time-to-event
endpoints . . . . . . . . . . . . . . . . . . . . . . . . . 20
1.3 Clinical trial optimization . . . . . . . . . . . . . . . . . . . . 28
1.3.1 Optimization strategies . . . . . . . . . . . . . . . . . 30
1.3.2 Optimization algorithm . . . . . . . . . . . . . . . . . 33
1.3.3 Sensitivity assessments . . . . . . . . . . . . . . . . . . 34
1.4 Direct optimization . . . . . . . . . . . . . . . . . . . . . . . 38
1.4.1 Case study 1.3: Clinical trial with two patient popula-
tions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
1.4.2 Qualitative sensitivity assessment . . . . . . . . . . . . 43
1.4.3 Quantitative sensitivity assessment . . . . . . . . . . . 44
1.4.4 Optimal selection of the target parameter . . . . . . . 53
1.5 Tradeoff-based optimization . . . . . . . . . . . . . . . . . . 59
1.5.1 Case study 1.4: Clinical trial with an adaptive design 59
1.5.2 Optimal selection of the target parameter . . . . . . . 67
2 Clinical Trials with Multiple Objectives 71
Alex Dmitrienko and Gautier Paux
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
2.2 Clinical Scenario Evaluation framework . . . . . . . . . . . . 73
2.2.1 Data models . . . . . . . . . . . . . . . . . . . . . . . 74
2.2.2 Analysis models . . . . . . . . . . . . . . . . . . . . . 74
2.2.3 Evaluation models . . . . . . . . . . . . . . . . . . . . 85
2.3 Case study 2.1: Optimal selection of a multiplicity adjustment 91
ix