Save 40% Site-Wide + Free Shipping With Code GIFT40. Fast checkout with Amazon Pay! Shop Now

Principles of Clinical Cancer Research

Double click on above image to view full picture

Zoom Out
Zoom In
Read a Sample Chapter
New Edition

Principles of Clinical Cancer Research

SKU# 9781620700693

Editors:

  • Loren K. Mell MD
  • Phuoc T. Tran MD, PhD
  • James B. Yu MD, MHS
  • Qiang (Ed) Zhang PhD
$99.00

Buy eBook:

Amazon Kindle

Description 

Principles of Clinical Cancer Research provides comprehensive coverage of the fundamentals of clinical cancer research, including the full spectrum of methodologies used in the field. For those involved in research or considering research careers, this book offers a mix of practical advice and analytical tools for effective training in theoretical principles as well as specific, usable teaching examples. The clinical oncologist or trainee will find a high-yield, practical guide to the interpretation of the oncology literature and the application of data to real-world settings. Valuable for both researchers and clinicians who wish to sharpen their skills, this book contains all of the cornerstones and explanations needed to produce and recognize quality clinical science in oncology.

Written from the physician-scientist’s perspective, the book lays a strong foundation in preclinical sciences that is highly relevant to careers in translational oncology research along with coverage of population and outcomes research and clinical trials. It brings together fundamental principles in oncology with the statistical concepts one needs to know to design and interpret studies successfully. With each chapter including perspectives of both clinicians and scientists or biostatisticians, Principles of Clinical Cancer Research provides balanced, instructive, and high-quality topic overviews and applications that are accessible and thorough for anyone in the field.

KEY FEATURES:

  • Gives real-world examples and rationales behind which research methods to use when and why
  • Includes numerous tables featuring key statistical methods and programming commands used in everyday clinical research
  • Contains illustrative practical examples and figures in each chapter to help the reader master concepts
  • Provides tips and pointers for structuring a career, avoiding pitfalls, and achieving success in the field of clinical cancer research
  • Access to fully downloadable eBook

Product Details 

  • Publication Date November 16, 2018
  • Page Count 456
  • Product Form Paperback / softback
  • ISBN 13 9781620700693

Table of Contents 

Contents

Contributors

Foreword Ralph R. Weichselbaum

Preface

I. INTRODUCTION

1. Introduction to Clinical Cancer Research

Loren K. Mell

2. Bias and Pitfalls in Cancer Research

Mak Djulbegovic, Mia Djulbegovic, and Benjamin Djulbegovic

II. TRANSLATIONAL CANCER RESEARCH

3. Principles of Molecular Biology

Reem A. Malek and Phuoc T. Tran

4. The Cell Cycle, Cellular Death, and Metabolism

Jacqueline Douglass, Andrew Sharabi, and Phuoc T. Tran

5. Metastasis and the Tumor Microenvironment

Jacqueline Douglass, Andrew Sharabi, and Phuoc T. Tran

6. Preclinical Methods

Hailun Wang and Phuoc T. Tran

7. Cancer Therapeutic Strategies and Treatment Resistance

Kekoa Taparra and Phuoc T. Tran

8. Prognostic and Predictive Biomarkers

Ariel E. Marciscano and Phuoc T. Tran

9. Working With Industry

Swan Lin, Yazdi K. Pithavala, and Sandip Pravin Patel

III. POPULATION AND OUTCOMES RESEARCH

10. Study Designs

Michael Milligan and Aileen Chen

11. Basic Statistics for Clinical Cancer Research

Loren K. Mell, Hanjie Shen, and Benjamin E. Leiby

12. Statistical Modeling for Clinical Cancer Research

Sanjay Aneja and James B. Yu

13. Cancer Epidemiology: Measuring Exposures, Outcomes, and Risk

Rishi Deka and Loren K. Mell

14. Survivorship: Effects of Cancer Treatment on Long-Term Morbidity

Zorimar Rivera-Núñez, Kaveh Zakeri, and Sharad Goyal

15. Longitudinal and Observational Data

Jeff Burkeen, Scott Keith, and Jona Hattangadi-Gluth

16. Time-to-Event Analysis

Loren K. Mell, Kaveh Zakeri, and Hanjie Shen

17. Machine Learning and High-Dimensional Data Analysis

Sanjay Aneja and James B. Yu

18. Health Outcomes and Disparities Research

Paige Sheridan and James Murphy

19. Cost-Effectiveness Analysis

Reith Roy Sarkar and James Murphy

IV. CLINICAL TRIALS

20. Introduction to Clinical Trials

Loren K. Mell

21. Early Phase Clinical Trials

Ying Yuan, Yanhong Zhou, and Jack J. Lee

22. Late Phase Clinical Trials

Karla V. Ballman

23. Quality of Life and Patient-Reported Outcome Analysis

Minh Tam Truong and Michael A. Dyer

24. Trials in Cancer Screening, Prevention, and Public Health

Rishi Deka and Loren K. Mell

25. Imaging and Technology Trials

Aaron B. Simon, Daniel R. Simpson, and Brent S. Rose

26. Adaptive and Innovative Clinical Trial Designs

Mark Chang, Xuan Deng, and Qiang (Ed) Zhang

27. Noninferiority and Equivalence Trials

Tie-Hua Ng

28. Systematic Reviews and Meta-Analyses

Enoch Chang, Nicholas G. Zaorsky, and Henry S. Park

V. CONCLUSION

29. Future Directions in Clinical Cancer Research

Brandon E. Turner and Aadel A. Chaudhuri

Index