Clinical Trials in Oncology

Clinical Trials in Oncology

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This book contains studies that are unimpeachably thorough, non-political, unbiased, and properly designed! These are the standards to which everyone in clinical research aspires. Yet, the difficulties in designing trials and interpreting data are subtle and ever present. The new edition of "Clinical Trials in Oncology" provides a concise, nontechnical, and now thoroughly up-to-date review of methods and issues related to clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the major pitfalls that are seemingly inherent in these processes.This edition includes a new section that describes recent innovations in Phase I designs. Another new section on microarray data examines the challenges presented by massive data sets and describes approaches used to meet those challenges. As always, the authors use clear, lucid prose and a multitude of real-world trials as examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Although the book focuses on cancer trials, the issues and concepts are important in any clinical setting.
"Clinical Trials in Oncology, Second Edition" works to improve the mutual understanding by clinicians and statisticians of the principles of clinical trials and helps them avoid the many hazards that can jeopardize the success of a trial.
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Product details

  • Hardback | 280 pages
  • 157.48 x 236.22 x 20.32mm | 362.87g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • United States
  • English
  • Revised
  • 2nd Revised edition
  • 67 black & white illustrations, 27 black & white tables
  • 1584883022
  • 9781584883029
  • 2,523,136

Review quote

"The dedication of the authors to enhancing the quality of clinical trials in oncology is evident from this book. This book will be useful to students, clinical research nurses and medical statisticians involved in oncology trials. I also recommend it to libraries and clinical institutions." - Clinical Trials 2004 "With over 60 years combined experience, the authors are ideally positioned to discuss the various statistical issues apparent in clinical trials, identifying alternative solutions, providing logical arguments for and against the various solutions. This book is also recommended for statisticians actively involved in the design, conduct, and analysis of clinical trial data (not only cancer clinical trials)." -Journal of Biopharmaceutical Statistics "A concise, easily readable, and thorough summaryALL medical oncology, radiation oncology, surgical oncology, and clinical research nurse academic training programs should provide this important text to trainees on Day 1." -Charles R. Thomas Jr., MD, University of Texas Health Science Center at San Antonio, USA "Succinct and focused[This book] is clear, cogent, and practical. It is structured so that statisticians can use specific sections as starting point to develop shared understandings with investigators, study coordinators, and data managersIt has been useful to me and my clients, and I look forward to the second edition." -Marlene Egger, University of Utah, USA
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Table of contents

INTRODUCTION A Brief History of Clinical Trials The Southwest Oncology Group Example Trials The Reason for the Book STATISTICAL CONCEPTS Introduction The Phase II Trial-Estimation The Phase III Trial-Hypothesis Testing The Proportional Hazards Model Sample Size Calculations Concluding Remarks THE DESIGN OF CLINICAL TRIALS Introduction Endpoints Phase I Trials Phase II Trials Phase III Trials Conclusion MULTI-ARM TRIALS Introduction Types of Multi-Arm Trials Significance Level Power Interaction Other Model Assumptions To Screen or Not to Screen Timing of Randomization Conclusion INTERIM ANALYSIS AND DATA MONITORING COMMITTEES Planned Interim Analysis Data Monitoring Committees: Rationale and Responsibilities Monitoring Committees: Composition Examples Concluding Remarks DATA MANAGEMENT AND QUALITY CONTROL Introduction: Why Worry? Protocol Development Data Collection Protocol Management and Evaluation Quality Assurance Audits Training Data Base Management Conclusion Appendix: Examples 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
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