Controversial Issues in Clinical Trials

In clinical trial practice, controversial statistical issues inevitably occur regardless of the compliance with good statistical practice and good clinical practice. But by identifying the causes of the issues and correcting them, the study objectives of clinical trials can be better achieved. Controversial Statistical Issues in Clinical Trials covers commonly encountered controversial statistical issues in clinical trials and, whenever possible, makes recommendations to resolve these problems.

The book focuses on issues occurring at various stages of clinical research and development, including early-phase clinical development (such as bioavailability/bioequivalence), bench-to-bedside translational research, and late-phase clinical development. Numerous examples illustrate the impact of these issues on the evaluation of the safety and efficacy of the test treatment under investigation. The author also offers recommendations regarding possible resolutions of the problems.

Written by one of the preeminent experts in the field, this book provides a useful desk reference and state-of-the art examination of problematic issues in clinical trials for scientists in the pharmaceutical industry, medical/statistical reviewers in government regulatory agencies, and researchers and students in academia.

Shein-Chung Chow, Ph.D., is a professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine. Dr. Chow is also an adjunct professor of clinical sciences at Duke–National University of Singapore Graduate Medical School and the editor-in-chief of the Journal of Biopharmaceutical Statistics. He has authored or co-authored more than 200 papers and 19 books, including the recently published Handbook of Adaptive Designs in Pharmaceutical and Clinical Development. He earned his Ph.D. in statistics from the University of Wisconsin–Madison.

IntroductionPharmaceutical DevelopmentControversial IssuesAim and Structure of the Book

Good Statistical PracticesStatistical PrinciplesGood Statistical Practices in EuropeImplementation of GSP

Bench-to-Bedside Translational ResearchBiomarker DevelopmentOne-Way/Two-Way Translational ProcessLost in TranslationAnimal Model versus Human Model

Bioavailability and BioequivalenceBioequivalence AssessmentDrug InterchangeabilityControversial IssuesFrequently Asked Questions

Hypotheses for Clinical Evaluation and Significant DigitsHypotheses for Clinical EvaluationStatistical Methods for Testing Composite Hypotheses of NSThe Impact on Power and Sample Size CalculationSignificant Digits

Instability of Sample Size CalculationSample Size CalculationInstability and Bootstrap-Median ApproachSimulation StudyAn Example

Integrity of Randomization/BlindingThe Effect of Mixed-Up RandomizationBlocking Size in RandomizationTest for Integrity of BlindingAnalysis under Breached BlindnessAn Example

Clinical Strategy for Endpoint SelectionClinical Strategy for Endpoint SelectionTranslations among Clinical EndpointsComparison of Different Clinical StrategiesA Numerical Study

Protocol AmendmentsMoving Target Patient PopulationAnalysis with Covariate AdjustmentAssessment of Sensitivity IndexSample Size Adjustment

Seamless Adaptive Trial DesignsControversial IssuesTypes of Two-Stage Seamless Adaptive DesignsAnalysis for Seamless Design with Same Study Objectives/EndpointsAnalysis for Seamless Design with Different EndpointsAnalysis for Seamless Design with Different Objectives/Endpoints

Multiplicity in Clinical TrialsGeneral ConceptRegulatory Perspective and Controversial IssuesStatistical Method for Adjustment of MultiplicityGatekeeping Procedures

Independence of Data Monitoring CommitteeRegulatory RequirementsDMC Composition and CharterDMC’s Functions and ActivitiesIndependence of DMC

Two-Way ANOVA versus One-Way ANOVA with Repeated MeasuresOne-Way ANOVA with Repeated MeasuresTwo-Way ANOVAStatistical EvaluationSimulation StudyAn ExampleDiscussion

Validation of QOL InstrumentsQOL AssessmentPerformance CharacteristicsResponsiveness and SensitivityUtility Analysis and CalibrationAnalysis of Parallel QuestionnaireAn Example

Missing Data ImputationLast Observation Carry ForwardMean/Median ImputationRegression ImputationMarginal/Conditional Imputation for ContingencyTesting for IndependenceControversial IssuesRecent Development

Center GroupingSelection of the Number of CentersImpact of Treatment Imbalance on PowerCenter GroupingProcedure for Center GroupingAn Example

Non-Inferiority MarginNon-Inferiority MarginStatistical Test Based on Treatment DifferenceStatistical Tests Based on Relative RiskMixed Non-Inferiority MarginRecent Developments

QT Studies with Recording ReplicatesStudy Designs and ModelsPower and Sample Size CalculationAdjustment for CovariatesOptimization for Sample Size AllocationTest for QT/QTc ProlongationRecent Developments

Multiregional Clinical TrialsMultiregional (Multinational), Multicenter TrialsSelection of the Number of SitesSample Size Calculation and AllocationStatistical Methods for Bridging Studies

Dose Escalation TrialsTraditional Escalation RuleContinual Reassessment MethodDesign Selection and Sample Size

Enrichment Process in Target Clinical TrialsIdentification of Differentially Expressed GenesOptimal Representation of In Vitro Diagnostic Multivariate Index AssaysValidation of In Vitro Diagnostic Multivariate Index AssaysEnrichment ProcessStudy Designs of Target Clinical TrialsAnalysis of Target Clinical TrialsDiscussion

Clinical Trial SimulationProcess for Clinical Trial SimulationEM AlgorithmResampling Method: BootstrappingClinical Applications

Traditional Chinese MedicineFundamental DifferencesBasic ConsiderationsControversial IssuesRecent Development

The Assessment of Follow-On Biologic ProductsRegulatory RequirementsCriteria for BiosimilarityScientific IssuesAssessing Similarity Using Genomic Data

Generalizability/Reproducibility ProbabilityThe Estimated Power ApproachThe Confidence Bound ApproachThe Bayesian ApproachApplications

Good Review PracticesRegulatory Process and RequirementsGood Review PracticesObstacles and Challenges

Probability of SuccessGo/No-Go Decision in Development ProcessPOS Assessment

References
Index