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Textbook of Clinical Trials in Oncology : A Statistical Perspective.

By: Contributor(s): Material type: TextTextPublisher: Milton : CRC Press LLC, 2019Copyright date: ©2019Edition: 1st edDescription: 1 online resource (645 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781351620970
Subject(s): Genre/Form: Additional physical formats: Print version:: Textbook of Clinical Trials in OncologyDDC classification:
  • 616.99400727
LOC classification:
  • RC267 .T498 2019
Online resources:
Contents:
Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgment -- Editors -- Contributors -- 1. Introduction to Clinical Trials -- 1.1 Scope and Motivation -- 1.2 Resources -- 1.3 Conclusion -- References -- Section I: Early to Middle Development -- 2. Selection of Endpoints -- 2.1 Introduction -- 2.2 Key Definitions and Endpoint Selection -- 2.3 Patient-Centered Endpoints -- 2.3.1 Overall Survival -- 2.3.2 Adverse Events and Toxicity -- 2.3.2.1 Dose-Limiting Toxicity -- 2.3.3 Health-Related Quality of Life -- 2.3.3.1 European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire Core 30 Items -- 2.3.3.2 Functional Assessment of Cancer Therapy - General Version -- 2.3.3.3 Short-Form 36 Survey -- 2.4 Tumor-Centered Endpoints -- 2.4.1 Assessment of Response in Tumor-Centered Endpoints -- 2.4.2 Progression-Free Survival and Time to Progression -- 2.4.3 Disease-Free Survival -- 2.4.4 Time to Treatment Failure -- 2.4.5 Objective Response Rate and Duration of Response -- 2.5 Endpoints under Evaluation -- 2.5.1 Pathologic Complete Response (pCR) -- 2.5.2 Immune-Related Response Criteria (irRC) -- References -- 3. Innovative Phase I Trials -- 3.1 Early-Phase Designs for Cytotoxic Agents -- 3.1.1 Designs Based on Safety Endpoints -- 3.1.1.1 Rule-Based Algorithms: "A + B" Designs -- 3.1.1.2 Dose-Expansion Cohorts (DECs) -- 3.1.1.3 Model-Based Designs -- 3.1.2 Designs Based on Safety and Efficacy Endpoints -- 3.2 Early-Phase Designs: Moving Beyond Cytotoxic Agents -- 3.2.1 The Bayesian Quasi-CRM for Continuous Toxicity Endpoints -- 3.2.1.1 Illustrative Example of Modeling Toxicity Scores: Quasi-CRM versus Conventional CRM -- 3.2.2 Novel Endpoints in Early-Phase Trials -- 3.2.2.1 Dose-Finding Designs Incorporating Pharmacokinetics (PK) Measures -- 3.2.2.2 Dose-Finding Designs for Immunotherapies.
3.3 Conclusion -- References -- 4. Current Issues in Phase II Cancer Clinical Trials -- 4.1 Introduction -- 4.2 Single-Arm Phase II Trials -- 4.2.1 Optimal Two-Stage Designs -- 4.2.2 Estimation of Response Rate -- 4.2.3 Confidence Interval -- 4.2.4 P-Value Calculation -- 4.3 Phase II Trials with Heterogeneous Patient Populations -- 4.3.1 Single-Stage Designs -- 4.3.2 Example 4.6 -- 4.3.3 Two-Stage Designs -- 4.3.4 Example 4.7 -- 4.3.5 Conditional P-Value -- 4.4 Randomized Phase II Trials -- 4.4.1 Single-Stage Design -- 4.4.2 Two-Stage Design -- 4.4.2.1 Choice of a1 and a2 -- 4.4.2.2 Choice of n1 and n2 -- 4.4.3 Numerical Studies -- 4.5 Conclusion -- References -- 5. Design and Analysis of Immunotherapy Clinical Trials -- 5.1 Introduction -- 5.2 Immune-Related Toxicity -- 5.3 Delayed Treatment Benefit -- 5.4 Marker Stratification -- 5.5 Treatment Benefit in a Subset of Patients -- 5.6 Conclusion -- Acknowledgment -- References -- 6. Adaptive Designs -- 6.1 Introduction -- 6.2 Adaptive Designs for Dose-Finding Studies -- 6.3 Population Finding -- 6.4 Response-Adaptive Randomization -- 6.5 Sample Size Re-Estimation -- 6.6 Adaptive Seamless Designs -- 6.7 Conclusion -- References -- Section II: Late Phase Clinical Trials -- 7. Sample Size Calculations for Phase III Trials in Oncology -- 7.1 Introduction -- 7.2 Basics of Sample Size Calculation in Phase III Oncology Trials -- 7.2.1 Required Parameters and Settings -- 7.2.2 Relationships among Survival Parameters -- 7.2.3 Basic Parameters: -- 7.2.4 Sample Size Calculations Using Additional Parameters -- 7.2.5 Sample Size Calculations Based on the Log-Rank Test -- 7.3 Software for Sample Size Calculations -- 7.4 Superiority Trials -- 7.4.1 Purpose of Superiority Trials -- 7.4.2 The Sample Size Calculation Methods Used in Various Software Programs -- 7.4.2.1 SAS Power Procedure: TWOSAMPLESURVIVAL Statement.
7.4.2.2 PASS: Log-Rank Tests and Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.4.2.3 SWOG Statistical Tool: Two-Arm Survival -- 7.4.3 Example of a Superiority Trial (the EAGLE Trial) -- 7.4.4 Comparison of the Sample Size Calculated with Each Software Program -- 7.4.4.1 SAS Power Procedure -- 7.4.4.2 PASS: Log-Rank Tests (Input Median Survival Times) -- 7.4.4.3 PASS: Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.4.4.4 SWOG Statistical Tool Website -- 7.4.4.5 Interpretation of the Results -- 7.5 Non-Inferiority Trials -- 7.5.1 Purpose of Non-Inferiority Trials and Formulas to Calculate the Sample Size -- 7.5.2 Specification of the Non-Inferiority Margin, -- 7.5.3 The Sample Size-Calculation Methods Used in Each Software Program -- 7.5.3.1 SAS -- 7.5.3.2 PASS: Non-Inferiority Log-Rank Tests and Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.5.3.3 SWOG Statistical Tool: Two-Arm Survival -- 7.5.4 Example Trial (JCOG0404 Trial) -- 7.5.5 Comparison of Sample Sizes Calculated with Each Software Program -- 7.5.5.1 SAS Power Procedure -- 7.5.5.2 PASS: Non-Inferiority Log-Rank Tests -- 7.5.5.3 PASS: Non-Inferiority Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.5.5.4 SWOG Statistical Tool Website -- 7.5.6 Interpretation of the Results -- 7.6 Other -- 7.6.1 Consideration for One-Sided or Two-Sided Tests -- 7.6.2 Violation of the Proportional-Hazards and Exponential-Curve Assumptions -- 7.7 Conclusion -- References -- 8. Non-Inferiority Trial -- 8.1 Introduction -- 8.2 Assumptions for NI Trials -- 8.2.1 The Constancy of the Control Effect -- 8.2.2 Assay Sensitivity -- 8.3 Design -- 8.3.1 Selecting the Active Control -- 8.3.2 Determining the NI Margin -- 8.3.3 Statistical Algorithm for Assessing Non-Inferiority -- 8.3.3.1 The Fixed-Margin Approach.
8.3.3.2 Synthesis Approach -- 8.3.4 Sample Size -- 8.3.5 Other Design Alternatives and Issues -- 8.3.5.1 Three-Arm Studies -- 8.3.5.2 Switching between NI and Superiority -- 8.3.5.3 Interim Analyses -- 8.4 Trial Conduction -- 8.5 Analyses -- 8.5.1 Analysis Populations -- 8.5.2 Missing Data -- 8.5.3 NI and Superiority -- 8.6 Reporting -- 8.7 Examples -- References -- 9. Design of Multi-Arm, Multi-Stage Trials in Oncology -- 9.1 Introduction -- 9.2 Notation -- 9.2.1 Multi-Arm Trial -- 9.2.2 Multi-Arm, Multi-Stage -- 9.3 Determining Statistical Quantities for Multi-Arm Trials -- 9.3.1 Distribution of Test Statistics from a Multi-Arm Trial -- 9.3.1.1 Normal Outcomes -- 9.3.1.2 Binary Outcome -- 9.3.1.3 Time-to-Event Outcome -- 9.3.2 Evaluating the Operating Characteristics of a Multi-Arm Design -- 9.3.2.1 Type I Error Rate -- 9.3.3 Power -- 9.3.3.1 Conjunctive Power -- 9.3.3.2 Disjunctive Power -- 9.3.3.3 Least Favorable Configuration -- 9.3.3.4 Comparison of Power -- 9.3.4 Case Study -- 9.4 Designing Multi-Arm Multi-Stage Trials -- 9.4.1 Distribution of Test Statistics -- 9.4.2 Group-Sequential MAMS -- 9.4.2.1 Example -- 9.4.2.2 Extensions -- 9.4.3 Drop-the-Loser Multi-Arm Trials -- 9.4.3.1 Notation and Operating Characteristics -- 9.4.3.2 Extensions -- 9.4.4 Case Study -- 9.5 Conclusion -- References -- 10. Multiple Comparisons, Multiple Primary Endpoints and Subpopulation Analysis -- 10.1 Sources of Multiplicity in Oncology Trials -- 10.1.1 Introductory Example -- 10.2 Multiple Testing Procedures -- 10.2.1 Basic Concepts -- 10.2.1.1 Error Rate in Confirmatory Clinical Trials -- 10.2.1.2 Single-Step and Stepwise Procedures -- 10.2.1.3 Closed Testing Procedures -- 10.2.1.4 Adjusted Critical Values and Adjusted p-Values -- 10.2.1.5 Simultaneous Confidence Intervals -- 10.2.2 Common Multiple Testing Procedures -- 10.2.2.1 Bonferroni Test.
10.2.2.2 Holm Procedure -- 10.2.2.3 Hochberg Procedure -- 10.2.2.4 Numerical Illustration -- 10.2.3 Gatekeeping and Graphical Procedures Based on the CTP -- 10.2.3.1 Bonferroni-Based Graphical Procedures -- 10.2.3.2 Procedures Based on Asymptotic Normality -- 10.2.4 Multiplicity Adjustment for Other Types of Endpoints -- 10.3 Multiple Comparison Procedures in Oncology -- 10.3.1 The Scope of Multiplicity Adjustment -- 10.3.2 Multiple Endpoints Complications in Group Sequential Designs -- 10.3.3 Outlook on Future Developments -- 10.4 Conclusion -- References -- 11. Cluster Randomized Trials -- 11.1 Introduction -- 11.2 Randomization -- 11.2.1 Matching and Stratification -- 11.2.2 Constrained Randomization -- 11.2.3 Minimization -- 11.3 Analysis -- 11.3.1 Continuous Outcomes -- 11.3.1.1 Model -- 11.3.1.2 Estimation and Inference -- 11.3.1.3 Example -- 11.3.2 Dichotomous Outcomes -- 11.3.2.1 Cluster-Level Proportions Model -- 11.3.2.2 Cluster-Level Log-Odds Model -- 11.3.2.3 Estimation and Inference -- 11.3.2.4 Example -- 11.3.3 Other Analysis Methods -- 11.4 Sample Size and Power -- 11.4.1 Continuous Outcomes -- 11.4.1.1 Power -- 11.4.1.2 Sample Size: Number of Clusters -- 11.4.1.3 Sample Size per Cluster -- 11.4.1.4 Unequal ICCs in Treatment Arms -- 11.4.1.5 Unequal Allocation -- 11.4.1.6 Covariates -- 11.4.1.7 Varying Cluster Sizes -- 11.4.1.8 Matching and Stratification -- 11.4.2 Dichotomous Outcomes -- 11.4.2.1 Sample Size and Power -- 11.4.2.2 Sample Size per Cluster -- 11.4.2.3 Unequal ICCs in Treatment Arms -- 11.4.2.4 Unequal Allocation -- 11.4.2.5 Covariates -- 11.4.2.6 Varying Cluster Sizes -- 11.5 Additional Resources -- 11.5.1 Resources for Other Designs -- 11.5.2 Resources for Power and Sample Size Calculation -- References -- 12. Statistical Monitoring of Safety and Efficacy -- 12.1 Introduction -- 12.2 Monitoring of Safety.
12.2.1 Introduction.
Summary: This is a textbook on the design and analysis of cancer clinical trials. It opens with a discussion of the choice of endpoints before moving onto discuss various types of trials across all phases of study, including basket trials, non-inferiority trials and multi-arm trials.
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Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgment -- Editors -- Contributors -- 1. Introduction to Clinical Trials -- 1.1 Scope and Motivation -- 1.2 Resources -- 1.3 Conclusion -- References -- Section I: Early to Middle Development -- 2. Selection of Endpoints -- 2.1 Introduction -- 2.2 Key Definitions and Endpoint Selection -- 2.3 Patient-Centered Endpoints -- 2.3.1 Overall Survival -- 2.3.2 Adverse Events and Toxicity -- 2.3.2.1 Dose-Limiting Toxicity -- 2.3.3 Health-Related Quality of Life -- 2.3.3.1 European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire Core 30 Items -- 2.3.3.2 Functional Assessment of Cancer Therapy - General Version -- 2.3.3.3 Short-Form 36 Survey -- 2.4 Tumor-Centered Endpoints -- 2.4.1 Assessment of Response in Tumor-Centered Endpoints -- 2.4.2 Progression-Free Survival and Time to Progression -- 2.4.3 Disease-Free Survival -- 2.4.4 Time to Treatment Failure -- 2.4.5 Objective Response Rate and Duration of Response -- 2.5 Endpoints under Evaluation -- 2.5.1 Pathologic Complete Response (pCR) -- 2.5.2 Immune-Related Response Criteria (irRC) -- References -- 3. Innovative Phase I Trials -- 3.1 Early-Phase Designs for Cytotoxic Agents -- 3.1.1 Designs Based on Safety Endpoints -- 3.1.1.1 Rule-Based Algorithms: "A + B" Designs -- 3.1.1.2 Dose-Expansion Cohorts (DECs) -- 3.1.1.3 Model-Based Designs -- 3.1.2 Designs Based on Safety and Efficacy Endpoints -- 3.2 Early-Phase Designs: Moving Beyond Cytotoxic Agents -- 3.2.1 The Bayesian Quasi-CRM for Continuous Toxicity Endpoints -- 3.2.1.1 Illustrative Example of Modeling Toxicity Scores: Quasi-CRM versus Conventional CRM -- 3.2.2 Novel Endpoints in Early-Phase Trials -- 3.2.2.1 Dose-Finding Designs Incorporating Pharmacokinetics (PK) Measures -- 3.2.2.2 Dose-Finding Designs for Immunotherapies.

3.3 Conclusion -- References -- 4. Current Issues in Phase II Cancer Clinical Trials -- 4.1 Introduction -- 4.2 Single-Arm Phase II Trials -- 4.2.1 Optimal Two-Stage Designs -- 4.2.2 Estimation of Response Rate -- 4.2.3 Confidence Interval -- 4.2.4 P-Value Calculation -- 4.3 Phase II Trials with Heterogeneous Patient Populations -- 4.3.1 Single-Stage Designs -- 4.3.2 Example 4.6 -- 4.3.3 Two-Stage Designs -- 4.3.4 Example 4.7 -- 4.3.5 Conditional P-Value -- 4.4 Randomized Phase II Trials -- 4.4.1 Single-Stage Design -- 4.4.2 Two-Stage Design -- 4.4.2.1 Choice of a1 and a2 -- 4.4.2.2 Choice of n1 and n2 -- 4.4.3 Numerical Studies -- 4.5 Conclusion -- References -- 5. Design and Analysis of Immunotherapy Clinical Trials -- 5.1 Introduction -- 5.2 Immune-Related Toxicity -- 5.3 Delayed Treatment Benefit -- 5.4 Marker Stratification -- 5.5 Treatment Benefit in a Subset of Patients -- 5.6 Conclusion -- Acknowledgment -- References -- 6. Adaptive Designs -- 6.1 Introduction -- 6.2 Adaptive Designs for Dose-Finding Studies -- 6.3 Population Finding -- 6.4 Response-Adaptive Randomization -- 6.5 Sample Size Re-Estimation -- 6.6 Adaptive Seamless Designs -- 6.7 Conclusion -- References -- Section II: Late Phase Clinical Trials -- 7. Sample Size Calculations for Phase III Trials in Oncology -- 7.1 Introduction -- 7.2 Basics of Sample Size Calculation in Phase III Oncology Trials -- 7.2.1 Required Parameters and Settings -- 7.2.2 Relationships among Survival Parameters -- 7.2.3 Basic Parameters: -- 7.2.4 Sample Size Calculations Using Additional Parameters -- 7.2.5 Sample Size Calculations Based on the Log-Rank Test -- 7.3 Software for Sample Size Calculations -- 7.4 Superiority Trials -- 7.4.1 Purpose of Superiority Trials -- 7.4.2 The Sample Size Calculation Methods Used in Various Software Programs -- 7.4.2.1 SAS Power Procedure: TWOSAMPLESURVIVAL Statement.

7.4.2.2 PASS: Log-Rank Tests and Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.4.2.3 SWOG Statistical Tool: Two-Arm Survival -- 7.4.3 Example of a Superiority Trial (the EAGLE Trial) -- 7.4.4 Comparison of the Sample Size Calculated with Each Software Program -- 7.4.4.1 SAS Power Procedure -- 7.4.4.2 PASS: Log-Rank Tests (Input Median Survival Times) -- 7.4.4.3 PASS: Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.4.4.4 SWOG Statistical Tool Website -- 7.4.4.5 Interpretation of the Results -- 7.5 Non-Inferiority Trials -- 7.5.1 Purpose of Non-Inferiority Trials and Formulas to Calculate the Sample Size -- 7.5.2 Specification of the Non-Inferiority Margin, -- 7.5.3 The Sample Size-Calculation Methods Used in Each Software Program -- 7.5.3.1 SAS -- 7.5.3.2 PASS: Non-Inferiority Log-Rank Tests and Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.5.3.3 SWOG Statistical Tool: Two-Arm Survival -- 7.5.4 Example Trial (JCOG0404 Trial) -- 7.5.5 Comparison of Sample Sizes Calculated with Each Software Program -- 7.5.5.1 SAS Power Procedure -- 7.5.5.2 PASS: Non-Inferiority Log-Rank Tests -- 7.5.5.3 PASS: Non-Inferiority Tests for Two Survival Curves Using Cox's Proportional Hazards Model -- 7.5.5.4 SWOG Statistical Tool Website -- 7.5.6 Interpretation of the Results -- 7.6 Other -- 7.6.1 Consideration for One-Sided or Two-Sided Tests -- 7.6.2 Violation of the Proportional-Hazards and Exponential-Curve Assumptions -- 7.7 Conclusion -- References -- 8. Non-Inferiority Trial -- 8.1 Introduction -- 8.2 Assumptions for NI Trials -- 8.2.1 The Constancy of the Control Effect -- 8.2.2 Assay Sensitivity -- 8.3 Design -- 8.3.1 Selecting the Active Control -- 8.3.2 Determining the NI Margin -- 8.3.3 Statistical Algorithm for Assessing Non-Inferiority -- 8.3.3.1 The Fixed-Margin Approach.

8.3.3.2 Synthesis Approach -- 8.3.4 Sample Size -- 8.3.5 Other Design Alternatives and Issues -- 8.3.5.1 Three-Arm Studies -- 8.3.5.2 Switching between NI and Superiority -- 8.3.5.3 Interim Analyses -- 8.4 Trial Conduction -- 8.5 Analyses -- 8.5.1 Analysis Populations -- 8.5.2 Missing Data -- 8.5.3 NI and Superiority -- 8.6 Reporting -- 8.7 Examples -- References -- 9. Design of Multi-Arm, Multi-Stage Trials in Oncology -- 9.1 Introduction -- 9.2 Notation -- 9.2.1 Multi-Arm Trial -- 9.2.2 Multi-Arm, Multi-Stage -- 9.3 Determining Statistical Quantities for Multi-Arm Trials -- 9.3.1 Distribution of Test Statistics from a Multi-Arm Trial -- 9.3.1.1 Normal Outcomes -- 9.3.1.2 Binary Outcome -- 9.3.1.3 Time-to-Event Outcome -- 9.3.2 Evaluating the Operating Characteristics of a Multi-Arm Design -- 9.3.2.1 Type I Error Rate -- 9.3.3 Power -- 9.3.3.1 Conjunctive Power -- 9.3.3.2 Disjunctive Power -- 9.3.3.3 Least Favorable Configuration -- 9.3.3.4 Comparison of Power -- 9.3.4 Case Study -- 9.4 Designing Multi-Arm Multi-Stage Trials -- 9.4.1 Distribution of Test Statistics -- 9.4.2 Group-Sequential MAMS -- 9.4.2.1 Example -- 9.4.2.2 Extensions -- 9.4.3 Drop-the-Loser Multi-Arm Trials -- 9.4.3.1 Notation and Operating Characteristics -- 9.4.3.2 Extensions -- 9.4.4 Case Study -- 9.5 Conclusion -- References -- 10. Multiple Comparisons, Multiple Primary Endpoints and Subpopulation Analysis -- 10.1 Sources of Multiplicity in Oncology Trials -- 10.1.1 Introductory Example -- 10.2 Multiple Testing Procedures -- 10.2.1 Basic Concepts -- 10.2.1.1 Error Rate in Confirmatory Clinical Trials -- 10.2.1.2 Single-Step and Stepwise Procedures -- 10.2.1.3 Closed Testing Procedures -- 10.2.1.4 Adjusted Critical Values and Adjusted p-Values -- 10.2.1.5 Simultaneous Confidence Intervals -- 10.2.2 Common Multiple Testing Procedures -- 10.2.2.1 Bonferroni Test.

10.2.2.2 Holm Procedure -- 10.2.2.3 Hochberg Procedure -- 10.2.2.4 Numerical Illustration -- 10.2.3 Gatekeeping and Graphical Procedures Based on the CTP -- 10.2.3.1 Bonferroni-Based Graphical Procedures -- 10.2.3.2 Procedures Based on Asymptotic Normality -- 10.2.4 Multiplicity Adjustment for Other Types of Endpoints -- 10.3 Multiple Comparison Procedures in Oncology -- 10.3.1 The Scope of Multiplicity Adjustment -- 10.3.2 Multiple Endpoints Complications in Group Sequential Designs -- 10.3.3 Outlook on Future Developments -- 10.4 Conclusion -- References -- 11. Cluster Randomized Trials -- 11.1 Introduction -- 11.2 Randomization -- 11.2.1 Matching and Stratification -- 11.2.2 Constrained Randomization -- 11.2.3 Minimization -- 11.3 Analysis -- 11.3.1 Continuous Outcomes -- 11.3.1.1 Model -- 11.3.1.2 Estimation and Inference -- 11.3.1.3 Example -- 11.3.2 Dichotomous Outcomes -- 11.3.2.1 Cluster-Level Proportions Model -- 11.3.2.2 Cluster-Level Log-Odds Model -- 11.3.2.3 Estimation and Inference -- 11.3.2.4 Example -- 11.3.3 Other Analysis Methods -- 11.4 Sample Size and Power -- 11.4.1 Continuous Outcomes -- 11.4.1.1 Power -- 11.4.1.2 Sample Size: Number of Clusters -- 11.4.1.3 Sample Size per Cluster -- 11.4.1.4 Unequal ICCs in Treatment Arms -- 11.4.1.5 Unequal Allocation -- 11.4.1.6 Covariates -- 11.4.1.7 Varying Cluster Sizes -- 11.4.1.8 Matching and Stratification -- 11.4.2 Dichotomous Outcomes -- 11.4.2.1 Sample Size and Power -- 11.4.2.2 Sample Size per Cluster -- 11.4.2.3 Unequal ICCs in Treatment Arms -- 11.4.2.4 Unequal Allocation -- 11.4.2.5 Covariates -- 11.4.2.6 Varying Cluster Sizes -- 11.5 Additional Resources -- 11.5.1 Resources for Other Designs -- 11.5.2 Resources for Power and Sample Size Calculation -- References -- 12. Statistical Monitoring of Safety and Efficacy -- 12.1 Introduction -- 12.2 Monitoring of Safety.

12.2.1 Introduction.

This is a textbook on the design and analysis of cancer clinical trials. It opens with a discussion of the choice of endpoints before moving onto discuss various types of trials across all phases of study, including basket trials, non-inferiority trials and multi-arm trials.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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