Design and Analysis of Clinical Trials for Predictive Medicine (Chapman & Hall/CRC Biostatistics Series Book 72)

An emerging clinical trials paradigm for predictive medicine involves the development of molecular diagnostics to enable the prediction of the effects of treatment or outcomes of individual patients. This book offers statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics. The book explains how to identify molecular biomarkers using DNA microarrays, validate the developed biomarkers, and confirm their clinical utility in randomized clinical trials. � Read more... Content: Cover; Contents; Preface; Editors; Contributors; Section I: Introductory Overview; 1: Clinical Trials for Predictive Medicine: New Paradigms and Challenges; 2: An Industry Statistician's Perspective on Personalized Health Care Drug Development; 3: Analytical Validation of In Vitro Diagnostic Tests; Section II: Early Clinical Trials Using Biomarkers; 4: Phase I Dose-Finding Designs and Their Applicability to Targeted Therapies; 5: An Overview of Phase II Clinical Trial Designs with Biomarkers; 6: Bayesian Adaptive Methods for Clinical Trials of Targeted Agents 7: Outcome-Adaptive Randomization in Early Clinical Trials8: Challenges of Using Predictive Biomarkers in Clinical Trials; Section III: Phase III Randomized Clinical Trials Using Biomarkers; 9: Comparison of Randomized Clinical Trial Designs for Targeted Agents; 10: Phase III All-Comers Clinical Trials with a Predictive Biomarker; 11: Evaluation of Clinical Utility and Validation of Gene Signatures in Clinical Trials; Section IV: Analysis of High-Dimensional Data and Genomic Signature Developments; 12: Statistical Issues in Clinical Development and Validation of Genomic Signatures 13: Univariate Analysis for Gene Screening: Beyond the Multiple Testing14: Statistical and Machine-Learning Methods for Class Prediction in High Dimension; 15: Survival Risk Prediction Using High-Dimensional Molecular Data; Section V: Randomized Trials with Biomarker Development and Validation; 16: Adaptive Clinical Trial Designs with Biomarker Development and Validation; 17: Development and Validation of Continuous Genomic Signatures in Randomized Clinical Trials; Section VI: Evaluation of Surrogate Biomarkers; 18: Biomarker-Based Surrogate Endpoints; Color Insert Abstract: An emerging clinical trials paradigm for predictive medicine involves the development of molecular diagnostics to enable the prediction of the effects of treatment or outcomes of individual patients. This book offers statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics. The book explains how to identify molecular biomarkers using DNA microarrays, validate the developed biomarkers, and confirm their clinical utility in randomized clinical trials Cover 1 Contents 8 Preface 12 Editors 14 Contributors 16 Section I: Introductory Overview 20 1: Clinical Trials for Predictive Medicine: New Paradigms and Challenges 22 2: An Industry Statistician’s Perspective on Personalized Health Care Drug Development 30 3: Analytical Validation of In Vitro Diagnostic Tests 52 Section II: Early Clinical Trials Using Biomarkers 70 4: Phase I Dose-Finding Designs and Their Applicability to Targeted Therapies 72 5: An Overview of Phase II Clinical Trial Designs with Biomarkers 90 6: Bayesian Adaptive Methods for Clinical Trials of Targeted Agents 108 7: Outcome-Adaptive Randomization in Early Clinical Trials 130 8: Challenges of Using Predictive Biomarkers in Clinical Trials 148 Section III: Phase III Randomized Clinical Trials Using Biomarkers 164 9: Comparison of Randomized Clinical Trial Designs for Targeted Agents 166 10: Phase III All-Comers Clinical Trials with a Predictive Biomarker 184 11: Evaluation of Clinical Utility and Validation of Gene Signatures in Clinical Trials 206 Section IV: Analysis of High-Dimensional Data and Genomic Signature Developments 224 12: Statistical Issues in Clinical Development and Validation of Genomic Signatures 226 13: Univariate Analysis for Gene Screening: Beyond the Multiple Testing 246 14: Statistical and Machine-Learning Methods for Class Prediction in High Dimension 272 15: Survival Risk Prediction Using High-Dimensional Molecular Data 290 Section V: Randomized Trials with Biomarker Development and Validation 312 16: Adaptive Clinical Trial Designs with Biomarker Development and Validation 314 17: Development and Validation of Continuous Genomic Signatures in Randomized Clinical Trials 334 Section VI: Evaluation of Surrogate Biomarkers 350 18: Biomarker-Based Surrogate Endpoints 352 Color Insert 390 Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming