Principles of clinical cancer research

Cover
Title
Copyright
Contents
Contributors
Foreword
Preface
Share Principles of Clinical Cancer Research
Part I: Introduction
	Chapter 1: Introduction to Clinical Cancer Research
		Overview
		The Hierarchy of Evidence
		Ethics in Clinical Science
		A Career in Clinical Cancer Research
		Practical Aspects of Running a Lab
		Writing Manuscripts and Protocols
		Funding Your Research
		Conclusions
		Glossary
		References
	Chapter 2: Bias and Pitfalls in Cancer Research
		Architecture of Clinical Research: A Brief Overview
		Bias in Therapeutic Research
		Bias in Randomized Trials
		Bias in Observational Studies
		Conclusion: Methodological Quality Versus Quality of Reporting
		Glossary
		References
Part II: Translational Cancer Research
	Chapter 3: Principles of Molecular Biology
		Central Dogma
		Cancer Genetics and Epigenetics
		Signal Transduction Pathways
		Genome Maintenance
		Glossary
		References
	Chapter 4: The Cell Cycle, Cellular Death, and Metabolism
		The Cell Cycle
		Mechanisms of Cell Death
		Cell Metabolism
		Glossary
		References
	Chapter 5: Metastasis and the Tumor Microenvironment
		Tumor Microenvironment
		Metastasis
		Glossary
		References
	Chapter 6: Preclinical Methods
		Rational Target Selection
		In Vitro Methods
		In Vivo Methods
		Conclusion
		Glossary
		References
	Chapter 7: Cancer Therapeutic Strategies and Treatment Resistance
		Traditional Chemotherapy and Early Cancer Models
		Hormonal Therapy and Molecularly Targeted Therapy
		Radiation Therapy
		Immunotherapy and other Biological Therapies
		Therapeutic Resistance Mechanisms
		Conclusion
		Glossary
		References
	Chapter 8: Prognostic and Predictive Biomarkers
		Definition of Cancer Biomarkers
		Prognostic and Predictive Biomarkers
		Methods for Biomarker Detection
		Cancer Biomarkers by Site
		Pitfalls in the Development and Validation of Biomarkers
		Conclusions/Future Directions
		Glossary
		References
	Chapter 9: Working With Industry
		Traditional Roles of Academia and Industry
		Drug Discovery and Development
		Classic Successful Collaborations
		Evolving Collaborative Efforts
		Funding Studies With Industry
		Investigational New Drug (IND) Applications
		FDA Registration
		Working With Technology and Device Companies
		Training Researchers
		Conclusion
		Glossary
		References
Part III: Population and Outcomes Research
	Chapter 10: Study Designs
		Descriptive Studies
		Analytical Studies
		Conclusion
		Glossary
		References
	Chapter 11: Basic Statistics for Clinical Cancer Research
		Describing Data
		Plotting Data
		Types of Distributions
		Central Limit Theorem
		Drawing Comparisons and Testing Hypotheses
		Basic Statistics: Which Test to Use?
		Binary (Dichotomous) Data
		Normally Distributed and Continuous Data
		Paired or Correlated Data
		Ordinal and Categorical (Nominal) Data
		Measures of Correlation
		Censored Data
		Multiple Hypothesis Testing
		Other Specialized Statistics
		Statistical Modeling
		Model Specification and Building
		Testing Model Fit and Function
		Mixed Effects Modeling
		Missing Data
		Conclusion: A Note on Terminology
		Glossary
		References
	Chapter 12: Statistical Modeling for Clinical Cancer Research
		Statistical Modeling
		Sample Research Question
		Ordinary Least Squares (Linear) Regression
		Multiple (Multivariable) Linear Regression
		Assumptions of Linear Regression
		Example: OLS Regression
		Example: Multivariable Regression
		Conclusion
		Glossary
		References
	Chapter 13: Cancer Epidemiology: Measuring Exposures, Outcomes, and Risk
		Measures Used in Cancer Epidemiology
		Association and Causation
		Selected Statistical Tests in Cancer Epidemiology
		Modeling Exposures and Outcomes
		Generalized Linear Modeling
		Glossary
		References
	Chapter 14: Survivorship: Effects of Cancer Treatment on Long-Term Morbidity
		Radiation, Breast Cancer, and Heart Disease
		Measurement Error
		Measuring Heart Dose
		Dose–Response Model of RIHD
		Modern Analytic Techniques
		Problems in Study Design: Innovation to Extinction
		Conclusion
		Glossary
		References
	Chapter 15: Longitudinal and Observational Data
		Longitudinal Study Designs
		Advantages and Disadvantages of Longitudinal Studies
		Examples of Longitudinal Studies
		Implementation of a Longitudinal Study
		Statistical Considerations
		Analytic Considerations
		Conclusion
		Glossary
		References
	Chapter 16: Time-to-Event Analysis
		Statistical Model of Time-to-Event Data
		Estimating Time-to-Event Functions
		Cause Specificity, Competing Risks, and Cumulative Incidence
		Testing Effects on the Hazard Function: Cox Proportional Hazards Model
		Testing Effects on the Cumulative Incidence Function: Fine–Gray Model
		Evaluating Time-to-Event Models Using Martingale Residuals
		Evaluating the Proportional Hazards Assumption
		Sample Size and Power Estimation for Time-to-Event Data
		Composite Time-to-Event Endpoints
		Power, Cost, and Personalized Medicine in Competing Risks Settings
		Competing Event Theory
		Conclusion
		Glossary
		References
		Appendix
	Chapter 17: Machine Learning and High-Dimensional Data Analysis
		What is Machine Learning?
		Machine Learning Versus Traditional Statistical Models
		Metrics for Evaluating Machine Learning Algorithms
		Common Machine Learning Algorithms for Dimensionality Reduction
		Principal Component Analysis
		Manifold Learning
		Support Vector Machines
		Decision Trees and Random Forest Models
		Deep Learning Models
		Unsupervised Learning Methods
		Conclusion
		Glossary
		References
	Chapter 18: Health Outcomes and Disparities Research
		Overview of Health Outcomes Research
		Types of Data Used in Health Outcomes Research
		Health Outcomes Research Study Designs
		Quantitative Versus Qualitative Research
		Conclusion
		Glossary
		References
	Chapter 19: Cost-Effectiveness Analysis
		Overview of Cost-Effectiveness Research
		Measuring Cost
		Measuring Effectiveness
		Cost-Effectiveness Analysis
		Sensitivity Analyses
		Conclusion
		Glossary
		References
Part IV: Clinical Trials
	Chapter 20: Introduction to Clinical Trials
		Regulatory Aspects of Clinical Trials
		Practical Elements of Designing Clinical Trials
		Running Trials: The Big Picture
		Glossary
		References
	Chapter 21: Early Phase Clinical Trials
		Single-Agent Phase I Study Designs
		Comparison of Phase I Designs
		Software
		Single-Agent Trials With Molecularly Targeted and Immunotherapy Agents
		Drug-Combination Trials
		Combination Trials to Find One MTD
		Combination Trials to Find Multiple MTDS
		Phase II Clinical Trial Designs
		Glossary
		References
		Appendix
	Chapter 22: Late Phase Clinical Trials
		Two-Arm Trial Designs
		Endpoints
		Statistical Considerations
		Study Monitoring
		Real-World Example
		Other Trial Designs
		Software for Clinical Trial Design
		Conclusion
		Glossary
		References
	Chapter 23: Quality of Life and Patient-Reported Outcome Analysis
		Development of QOL and PRO Instruments
		Common QOL and PRO Instruments in Cancer Clinical Trials
		Patient-Versus Clinician-Reported Adverse Events
		Utilities in Clinical Trials
		Designing Studies With QOL/PRO Endpoints
		Analysis of QOL and PRO Data
		Integrating Electronic Technology to Obtain QOL Assessments
		Reporting of QOL and PRO Data
		Importance of QOL/PRO Data
		Conclusion
		Glossary
		References
	Chapter 24: Trials in Cancer Screening, Prevention, and Public Health
		Screening and Public Health
		Sensitivity and Specificity of Screening Tests
		Bias in Screening Tests
		Screening Trials
		Prevention Trials
		Dietary Interventions to Prevent Cancer
		Conclusions
		Glossary
		References
	Chapter 25: Imaging and Technology Trials
		Diagnostic Imaging
		Imaging Metrics as Endpoints in Therapeutic Clinical Trials
		Clinical Trials of Image-Guided Interventions
		Conclusion
		Glossary
		References
	Chapter 26: Adaptive and Innovative Clinical Trial Designs
		Types of Adaptive Designs
		Conclusion
		Glossary
		References
	Chapter 27: Noninferiority and Equivalence Trials
		Gold Standard for Assessing Treatment Efficacy
		Why Active-Control Trials?
		Placebo Control Versus Active Control
		Sample Size Determination
		Notations and Assumptions
		Statistical Hypotheses
		Statistical Approaches for Testing Noninferiority
		Analyses of Randomized Controlled Trials
		Conclusion
		Glossary
		References
		Appendix
		Acknowledgments
	Chapter 28: Systematic Reviews and Meta-Analyses
		Overview of Terminology
		Steps to Perform a Systematic Review
		Systematic Reviews of Nonrandomized Studies
		Individual Patient Data
		Network Meta-Analysis
		Conclusion
		Helpful Resources
		Glossary
		References
Part V: Conclusion
	Chapter 29: Future Directions in Clinical Cancer Research
		Genomics
		Transcriptomics
		Proteomics
		Metabolomics
		Radiomics
		Conclusion
		Glossary
		References
Index