Dmitrienko / Pulkstenis Clinical Trial Optimization Using R

1. Auflage 2017
ISBN: 978-1-4987-3508-7
Verlag: CRC Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 337 Seiten

Reihe: Chapman & Hall/CRC Biostatistics Series

The main goal of this book is to define a unified framework for clinical trial optimization based on a comprehensive quantitative evaluation of relevant clinical scenarios (using the clinical scenario evaluation approach) and introduce best practices for simulationbased optimization. The book will be aimed at a broad audience and will emphasize a hands-on approach with a detailed discussion of practical issues arising in clinical trial optimization and R software implementation (relevant statistical methodology will be moved to the appendix).

Autoren/Hrsg.

Dmitrienko, Alex

Pulkstenis, Erik

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik
• Mathematik | Informatik Mathematik Stochastik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie

Inhaltsverzeichnis

Clinical Scenario Evaluation and Clinical Trial Optimization
Alex Dmitrienko and Gautier Paux

Introduction
Clinical scenario evaluation
Components of Clinical Scenario Evaluation
Software implementation
Case study 1.1: Clinical trial with a normally distributed endpoint
Case study 1.2: Clinical trial with two time-to-event endpoints
Clinical trial optimization
Optimization strategies
Optimization algorithm
Sensitivity assessments
Direct optimization
Case study 1.3: Clinical trial with two patient populations
Qualitative sensitivity assessment
Quantitative sensitivity assessment
Optimal selection of the target parameter
Tradeoff-based optimization
Case study 1.4: Clinical trial with an adaptive design
Optimal selection of the target parameter

Clinical Trials with Multiple Objectives
Alex Dmitrienko and Gautier Paux

Introduction
Clinical Scenario Evaluation framework
Case study 2.1: Optimal selection of a multiplicity adjustment
Qualitative sensitivity assessment
Quantitative sensitivity assessment
Software implementation
Conclusions and extensions
Case study 2.2: Direct selection of optimal procedure parameters
Case study 2.3: Tradeoff-based selection of optimal procedure parameters
Clinical trial

Subgroup Analysis in Clinical Trials
Alex Dmitrienko and Gautier Paux

Introduction
Clinical Scenario Evaluation in confirmatory subgroup analysis
Case study 3.1: Optimal selection of a multiplicity adjustment
Case study 3.2: Optimal selection of decision rules to support two potential claims
Case study 3.3: Optimal selection of decision rules to support three potential claims

Decision Making in Clinical Development
Kaushik Patra, Ming-Dauh Wang, Jianliang Zhang, Aaron Dane, Paul Metcalfe, Paul Frewer, and Erik Pulkstenis

Introduction
Clinical Scenario Evaluation in Go/No-Go decision making and determination of probability of success
Case study 4.1: Bayesian Go/No-Go decision criteria
Case study 4.2: Bayesian Go/No-Go evaluation using an alternative decision criterion
Case study 4.3: Bayesian Go/No-Go evaluation in a trial with an interim analysis
Case study 4.4: Decision criteria in Phase II trials based on Probability of Success
Case study 4.5: Updating POS using interim or external information

Bibliography

Über Autor(innen)

Alex Dmitrienko, Ph.D., Vice President, Center for Statistics in Drug Development, Quintiles Innovation, has over 15 years of pharmaceutical experience and has been actively involved in biostatistical research with emphasis on multiple testing procedures, subgroup analysis and adaptive design in clinical trials. He has authored/edited two SAS Press books (Analysis of Clinical Trials Using SAS and Pharmaceutical Statistics Using SAS) and a Chapman and Hall/CRC Press book (Multiple Testing Problems in Pharmaceutical Statistics). Dr. Dmitrienko is an Associate Editor for Statistics in Medicine and a Fellow of the American Statistical Association.