Classical and adaptive clinical trial designs using ExpDesign Studio [trademark symbol] /

Classical and adaptive clinical trial designs using ExpDesign Studio [trademark symbol] /

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Bibliographic Details
Author / Creator:Chang, Mark.
Imprint:Hoboken, N.J. : John Wiley, ©2008.
Description:1 online resource (xviii, 260 pages) : illustrations
Language:English
Subject:
Drugs -- Testing -- Computer simulation.
Adaptive sampling (Statistics)
Clinical trials -- Data processing.
Drugs, Investigational.
Research Design.
Clinical Trials as Topic -- methods.
Software.
Adaptive sampling (Statistics)
Clinical trials -- Data processing.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11219459
Hidden Bibliographic Details
ISBN:9780470369975
0470369973
0470368713
9780470368718
0470276126
9780470276129
0470438568
9780470438565
1281732559
9781281732552
9786611732554
6611732551
Digital file characteristics:data file
Notes:Includes bibliographical references and index.
English.
Print version record.
Summary:ExpDesign Studio facilitates more efficient clinical trial design. This book introduces pharmaceutical statisticians, scientists, researchers, and others to ExpDesign Studio software for classical and adaptive designs of clinical trials. It includes the Professional Version 5.0 of ExpDesign Studio software that frees pharmaceutical professionals to focus on drug development and related challenges while the software handles the essential calculations and computations. After a hands-on introduction to the software and an overview of clinical trial designs encompassing numerous variations, Classi.
Other form:Print version: Chang, Mark. Classical and adaptive clinical trial designs using ExpDesign Studio [trademark symbol]. Hoboken, N.J. : John Wiley, ©2008
Standard no.:10.1002/9780470368718
Table of Contents:
  • Preface.
  • Self-Study and Practice Guide.
  • 1. ExpDesign Studio.
  • 1.1. Introduction
  • 1.2. How to Design a Trial Using ExpDesign Studio
  • 1.2.1. How to Design a Classical Trial
  • 1.2.2. How to Design a Group Sequential Trial
  • 1.2.3. How to Design an Adaptive Trial
  • 1.2.4. How to Run Adaptive Trial Simulations
  • 1.2.5. How to Design a Multistage Trial
  • 1.2.6. How to Design a Dose-Escalation Trial
  • 1.3. ExpDesign Menus
  • 2. Clinical Trial Design.
  • 2.1. Introduction
  • 2.2. Classical Clinical Trial Design
  • 2.2.1. Substantial Evidence
  • 2.2.2. Clinical Trial Endpoint
  • 2.2.3. Confirmatory Trials
  • 2.2.4. Exploratory Trials
  • 2.2.5. Multicenter Trials
  • 2.2.6. Trials to Show Superiority
  • 2.2.7. Trials to Show Equivalence or Noninferiority
  • 2.2.8. Trials to Show a DoseûResponse Relationship
  • 2.2.9. Parallel Design
  • 2.2.10. Crossover Design
  • 2.2.11. Factorial Design
  • 2.3. Selection of a Trial Design
  • 2.3.1. Balanced Versus Unbalanced Designs
  • 2.3.2. Crossover Versus Parallel Designs
  • 2.3.3. Dose Escalation Versus Titration Designs
  • 2.3.4. Bioavailability Versus Bioequivalence Designs
  • 2.3.5. Equivalence Versus Bioequivalence
  • 2.3.6. Sample-Size Determination
  • 2.4. Adaptive Clinical Trial Design
  • 2.4.1. Group Sequential Design
  • 2.4.2. Sample-Size Reestimation Design
  • 2.4.3. Drop-Loser Design
  • 2.4.4. Response-Adaptive Randomization Design
  • 2.4.5. Adaptive Dose-Escalation Design
  • 2.4.6. Biomarker-Adaptive Design
  • 2.4.7. Multistage Design of Single-Arm Trials
  • 3. Classical Trial Design.
  • 3.1. Introduction
  • 3.1.1. Hypothesis Test
  • 3.1.2. Importance of Sample-Size Calculation
  • 3.1.3. Factors Affecting Sample Size
  • 3.1.4. Avoiding Under- or Overpowered Designs
  • 3.2. How to Calculate Sample Size Using ExpDesign
  • 3.2.1. Testing the Mean Difference Between Two Groups
  • 3.2.2. Testing the Proportion Difference Between Two Groups
  • 3.2.3. Testing the Survival Difference Between Two Groups
  • 3.2.4. Testing the Survival Difference with a Follow-up Period
  • 3.2.5. Exact Test for a One-Sample Proportion
  • 3.2.6. McNemarÆs Test for Paired Data
  • 3.2.7. Noninferiority Test for Two Means
  • 3.2.8. Bioequivalence Test for Two Means
  • 3.2.9. Bioequivalence Test for Two Means of Lognormal Data
  • 3.2.10. Equivalence Test Based on the Ratio of Two Means
  • 3.2.11. Precision Method for the Mean Difference for a Paired Sample
  • 3.2.12. MantelûHaenszel Test for an Odds Ratio with Two Strata
  • 3.2.13. PearsonÆs Chi-Square Test for Rate Difference
  • 3.2.14. One-Way ANOVA for Parallel Groups
  • 3.2.15. DoseûResponse Trial for a Myocardial Infarction
  • 3.3. Mathematical Notes on Classical Design
  • 3.3.1. Large-Sample-Size Calculation for Classical Design
  • 3.3.2. Commonly Used Terms and Their Mathematical Expressions
  • 3.3.3. Relationship Between Enrollment Rate and Number of Events
  • 4. Group Sequential Trial Design.
  • 4.1. Introduction
  • 4.2. Basics of Group Sequential Design
  • 4.3. How to Design Sequential Trials Using ExpDesign
  • 4.3.1. Design Featuring Early Efficacy Stopping for Two Means
  • 4.3.2. Design Featuring Early Futility Stopping for a Proportion
  • 4.3.3. Design Featuring Early Stopping for a Survival Endpoint
  • 4.3.4. Design Featuring Early Stopping for Paired Proportions
  • 4.4. How to Monitor a Group Sequential Trial Using ExpDesign
  • 4.4.1. Need for Trial Monitoring
  • 4.4.2. Techniques for Monitoring a Sequential Trial
  • 4.4.3. How to Monitor a Trial Using ExpDesign
  • 4.5. Mathematical Notes on Sequential Trial Design
  • 4.5.1. Unified Formulation for Sequential Trial Design
  • 4.5.2. Calculation of Conditional Probability
  • 4.5.3. Conditional and Predictive Power and RCI for Trial Monitoring
  • 4.5.4. Bias-Adjusted Estimates
  • 5. Adaptive Trial Design.
  • 5.1. Introduction
  • 5.2. Basics of Adaptive Design Methods
  • 5.3. How To Design a Sample-Size Reestimation Trial Using ExpDesign
  • 5.3.1. Sample-Size Adjustment Based on the Effect-Size Ratio
  • 5.3.2. Sample-Size Adjustment Based on Conditional Power
  • 5.3.3. Adaptive Design for an Acute Ischemic Stroke Trial
  • 5.3.4. Adaptive Design for an Asthma Study
  • 5.3.5. Adaptive Design for an Oncology Trial
  • 5.3.6. Noninferiority Design with a Binary Endpoint
  • 5.4. How to Design a Drop-Loser Trial Using ExpDesign
  • 5.4.1. Drop-Loser Mechanism
  • 5.4.2. Seamless Design of an Asthma Trial
  • 5.5. How to Design a Trial Using a Classifier Biomarker
  • 5.5.1. Biomarker Classifications
  • 5.5.2. Biomarker-Adaptive Design
  • 5.6. How to Design a Play-the-Winner Trail Using ExpDesign
  • 5.6.1. Randomized Play-the-Winner Design
  • 5.6.2. Adaptive Randomization with a Normal Endpoint
  • 6. Adaptive Trial Monitoring.
  • 6.1. Introduction
  • 6.2. Error-Spending Approach
  • 6.3. How to Recalculate Stopping Boundaries Using ExpDesign
  • 6.4. Conditional Power and the Futility Index
  • 6.5. How to Reestimate Sample Size Using ExpDesign
  • 6.5.1. Calculating Conditional Power Using ExpDesign
  • 6.5.2. Reestimating Sample Size Using ExpDesign
  • 6.6. Trial Examples
  • 6.6.1. Changes in Number and Timing of the Analyses
  • 6.6.2. Recursive Two-Stage Adaptive Design
  • 6.6.3. Conditional Power and Sample-Size Reestimation
  • 7. Oncology Adaptive Trial Design.
  • 7.1. Multistage Trial Design
  • 7.1.1. Introduction
  • 7.1.2. How to Design a Multistage Design Using ExpDesign
  • 7.2. Dose-Escalation Trial Design
  • 7.2.1. Introduction
  • 7.2.2. Bayesian Continual Reassessment Method
  • 7.2.3. How to Design a Dose-Escalation Trial Using ExpDesign
  • 7.3. Dose-Escalation Trial Monitoring Using CRM
  • 7.4. Mathematical Notes on Multistage Design
  • 7.4.1. Decision Tree for a Multistage Trial
  • 7.4.1. Two-Stage Design
  • 7.4.3. Three-Stage Design
  • 7.5. Mathematical Notes on the CRM
  • 7.5.1. Probability Model for DoseûResponse
  • 7.5.2. Prior Distribution of a Parameter
  • 7.5.3. Likelihood Function
  • 7.5.4. Reassessment of a Parameter
  • 7.5.5. Assignment of the Next Patient
  • 8. Adaptive Trial Simulator.
  • 8.1. Adjusting the Critical Region Method
  • 8.2. Classical Design with Two Parallel Treatment Groups
  • 8.3. Flexible Design with Sample-Size Reestimation
  • 8.4. Design with Random-Play-the-Winner Randomization
  • 8.5. Group Sequential Design with One Interim Analysis
  • 8.6. Design Permitting Early Stopping and Sample-Size Reestimation
  • 8.7. Classical Design with Multiple Treatment Groups
  • 8.8. Multigroup Trial with Response-Adaptive Randomization
  • 8.9. Adaptive Design Featuring Dropping Losers
  • 8.10. DoseûResponse Trial Design
  • 8.11. Dose-Escalation Design for an Oncology Trial
  • 9. Further Assistance from ExpDesign Studio.
  • 9.1. ExpDesign Probability Functions
  • 9.2. Virtual Trial Data Generation Using ExpDesign Randomizor
  • 9.2.1. Random Number Generation Using ExpDesign
  • 9.2.2. How to Generate a Random Univariate Using ExpDesign
  • 9.2.3. How to Generate a Random Multivariate Using ExpDesign
  • 9.2.4. How to Generate a Random Multibinomial Using ExpDesign
  • 9.3. ExpDesign Toolkits
  • 9.3.1. Graphic Calculator
  • 9.3.2. Statistical Calculator
  • 9.3.3. Confidence Interval Calculator
  • 10. Classical Design Method Reference.
  • 10.1. Single-Group Design
  • 10.1.1. One/Paired-Sample Hypothesis Test for the Mean
  • 10.1.2. One/Paired-Sample Hypothesis Test for the Proportion
  • 10.1.3. One/Paired-Sample Hypothesis Test for Others
  • 10.1.4. Paired-Sample Equivalence Test for the Mean
  • 10.1.5. Paired-Sample Equivalence Test for the Proportion
  • 10.1.6. One-Sample Confidence Interval for the Mean
  • 10.1.7. One-Sample Confidence Interval for the Proportion
  • 10.1.8. One-Sample Confidence Interval for Others
  • 10.2. Two-Group Design
  • 10.2.1. Two-Sample Hypothesis Test for the Mean
  • 10.2.2. Two-Sample Hypothesis Test for the Proportion
  • 10.2.3. Two-Sample Hypothesis Test for Others
  • 10.2.4. Two-Sample Equivalence/Noninferiority Test for the Mean
  • 10.2.5. Two-Sample Equivalence/Noninferiority Test for the Proportion
  • 10.2.6. Two-Sample Equivalence/Noninferiority Test for Survival
  • 10.2.7. Two-Sample Confidence Interval for the Mean
  • 10.2.8. Two-Sample Confidence Interval for the Proportion
  • 10.3. Multigroup Trial Design
  • 10.3.1. Multisample Hypothesis Test for the Mean
  • 10.3.2. Multisample Hypothesis Test for the Proportion
  • 10.3.3. Multisample Hypothesis Test for Others
  • 10.3.4. Multisample Confidence Interval for Others
  • Afterword.
  • Appendix A: Validation of ExpDesign Studio..
  • A.1. Validation Process for ExpDesign Studio
  • A.1.1. Algorithm Validation
  • A.1.2. Statistical Outcome Validation
  • A.1.3. Criteria for Passing Validation
  • A.1.4. Input and GUI Validation
  • A.2. Validation of the Classical Design Module
  • A.3. Validation of the Group Sequential Design Module
  • A.3.1. Stopping Boundary and Type I Error Rate Validation
  • A.3.2. Power and Sample-Size Validation
  • A.4. Validation of the Adaptive Design Module
  • A.4.1. Stopping Boundary and Type I Error Rate Validation
  • A.4.2. Validation of Adaptive Design Monitoring
  • A.5. Validation of the Multistage Design Module
  • A.6. Validation of the Traditional Dose-Escalation Design Module
  • A.6.1. Validation of the Traditional Escalation Rule
  • A.6.2. Validation of the Bayesian Continual Reassessment Method
  • A.7. Validation of the Trial Simulation Module
  • A.8. Validation of the Randomizor
  • A.9. Validation of the ExpDesign Toolkits
  • A.10. Computer Programs for Validations
  • A.10.1. SAS Macro for Three-Stage Design Validation
  • A.10.2. Traditional 3 + 3 Escalation Design Validation
  • A.10.3. SAS Program for CRM Validation
  • Appendix B. Sample-Size Calculation Methods: Classical Design.
  • References.
  • Index.
  • System Requirements, Software Installation, and Software License Agreement.

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