The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. In addition, the book has been restructured to have separate chapters and expanded discussions on general clinical trials issues, and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data. Although this book focuses on cancer trials, the same issues and concepts are important in any clinical setting. As always, the authors use clear, lucid prose and a multitude of real-world examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Armed with Clinical Trials in Oncology, Third Edition, clinicians and statisticians can avoid the many hazards that can jeopardize the success of a trial.
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Introduction A Brief History of Clinical Trials The Southwest Oncology Group (SWOG) The Reason for This Book Statistical Concepts Introduction The Single-Arm Phase II Trial-Estimation The Randomized Phase III Trial-Hypothesis Testing The Proportional Hazards Model Sample Size Calculations Concluding Remarks The Design of Clinical Trials Objectives Eligibility Treatment Arms Randomized Treatment Assignment Endpoints Differences to be Detected or Precision of Estimates and Other Assumptions Use of Independent Data Monitoring Committees Ethical Considerations Conclusion Phase I and Phase I/II Trials Phase I Trials Phase I/II Designs Phase II Trials Single-Arm Phase II Designs Multi-Arm Phase II Trials Other Phase II Designs Randomized versus Single-Arm: The Pros and Cons Conclusion Phase III Trials Randomization Other Design Considerations Equivalence or Noninferiority Trials Designs for Targeted Agents Multi-Arm Trials Interim Analyses Phase II/III Trials Concluding Remark Data Management and Quality Control Introduction: Why Worry? Protocol Development Data Collection Data Submission Data Evaluation Publication Quality Assurance Audits Training Database Management Conclusion Reporting of Results Timing of Report Required Information Analyses Conclusion Pitfalls Introduction Historical Controls Competing Risks Outcome by Outcome Analyses Subset Analyses Surrogate Endpoints Exploratory Analyses Introduction Some Background and Notation Identification of Prognostic Factors Forming Prognostic Groups Analysis of Microarray Data Meta-Analysis Concluding Remarks Summary and Conclusions References Index
