Introductory adaptive trial designs: a practical guide with R Chang, Mark

Table of Contents:

1. Introduction

Motivation
Adaptive Designs in Clinical Trials
Clinical Trial Simulation
Characteristics of Adaptive Designs
FAQs about Adaptive Designs

2. Classical Design


Introduction
Two-Group Superiority
Two-Group Noninferiority Trial
Two-Group Equivalence Trial
Trial with Any Number of Groups
Multigroup Dose-Finding Trial
Summary and Discussion

3. Two-Stage Adaptive Confirmatory Design Method

General Formulation
Method Based on Sum of p-Values
Method with Product of p-Values
Method with Inverse-Normal p-Values
Comparisons of Adaptive Design Methods

4. K-Stage Adaptive Confirmatory Design Methods

Test Statistics
Determination of Stopping Boundary
Error-Spending Function
Power and Sample Size
Error Spending Approach

5. Sample-Size Reestimation Design

Sample Size Reestimation Methods
Comparisons of SSR Methods
K-Stage Sample Size Reestimaion Trial
Summary

6. Special Two-Stage Group Sequential Trials

Event-Based Design
Equivalence Trial
Adaptive Design with Farrington-Manning Margin
Noninferiority Trial with Paired Binary Data
Trial with Incomplete Paired Data
Trial with Coprimary Endpoints
Trial with Multiple Endpoints

7. Pick-the-Winners Design

Overview of Multiple-Arm Designs
Pick-the-Winner Design
Stopping Boundary and Sample Size
Summary and Discussion

8. The Add-Arms Design

Introduction
The Add-Arm Design
Clinical Trial Examples
Extension of Add-Arms Designs
Summary

9. Biomarker-Adaptive Design

Taxonomy
Biomarker-Enrichment Design
Biomarker-Informed Adaptive Design
Summary

10. Response-Adaptive Randomization

Basic Response-Adaptive Randomizations
Generalized Response-Adaptive Randomization
Summary and Discussion

11. Adaptive Dose-Escalation Trial

Oncology Dose-Escalation Trial
Continual Reassessment Method
Alternative Form CRM
Evaluation of Dose-Escalation Design
Summary and Discussion

12. Deciding Which Adaptive Design to Use

Determining the Objectives
Determining Design Parameters
Evaluation Matrix of Adaptive Design

13. Monitoring Trials and Making Adaptations

Stopping and Arm-Selection
Conditional Power
Sample-Size Reestimation
New Randomization Scheme

14. Data Analyses of Adaptive Trials

Orderings in Sample Space
Adjusted p-Value
Parameter Estimation
Confidence Interval
Summary

15. Planning and Execution

Study Planning
Working with a Regulatory Agency
Trial Execution
Summary

Appendix A: Thirty-Minute Tutorial to R

Appendix B: R Functions for Adaptive Designs

Bibliography

Index

All the Essentials to Start Using Adaptive Designs in No Time

Compared to traditional clinical trial designs, adaptive designs often lead to increased success rates in drug development at reduced costs and time. Introductory Adaptive Trial Designs: A Practical Guide with R motivates newcomers to quickly and easily grasp the essence of adaptive designs as well as the foundations of adaptive design methods.

The book reduces the mathematics to a minimum and makes the material as practical as possible. Instead of providing general, black-box commercial software packages, the author includes open-source R functions that enable readers to better understand the algorithms and customize the designs to meet their needs. Readers can run the simulations for all the examples and change the input parameters to see how each input parameter affects the simulation outcomes or design operating characteristics.

Taking a learning-by-doing approach, this tutorial-style book guides readers on planning and executing various types of adaptive designs. It helps them develop the skills to begin using the designs immediately.


(https://www.crcpress.com/Introductory-Adaptive-Trial-Designs-A-Practical-Guide-with-R/Chang/9781498717465)