Description:

Biostatistics for Oncologists is the first practical guide providing the essential biostatistical concepts, oncology-specific examples, and applicable problem sets for medical oncologists, radiation oncologists, and surgical oncologists. In addition, it serves as a review for medical oncology and radiation oncology residents or fellows preparing for in-service and board exams. All examples are relevant to oncology and demonstrate how to apply core conceptual knowledge and applicable methods related to hypothesis testing, correlation and regression, categorical data analysis and survival analysis to the field of oncology. The book also provides guidance on the fundamentals of study design and analysis.

Written for oncologists by oncologists, this practical text demystifies challenging statistical concepts and provides concise direction on how to interpret, analyze, and critique data in oncology publications, as well as how to apply statistical knowledge to understanding, designing, and analyzing clinical trials. With practical problem sets and twenty-five multiple choice practice questions with answers, the book is an indispensable review for anyone preparing for in-service exams, boards, MOC, or looking to hone a lifelong skill.

Key Features:

• Practically explains biostatistics concepts important for passing the hematology, medical oncology, and  radiation oncology boards and MOC exams
• Provides guidance on how to read, understand, and critique data in oncology publications
• Gives relevant examples that are important for analyzing data in oncology, including the design and analysis of clinical trials
• Tests your comprehension of key biostatistical concepts with problem sets at the end of each section and a final section devoted to board-style multiple choice questions and answers
• Includes digital access to the eBook

Contents:

Preface
Share Biostatistics for Oncologists

 SECTION I. GENERAL STATISTICAL CONCEPTS

Chapter 1. Why Study Biostatistics? • What Is Biostatistics? • How Is Biostatistics Useful for Oncologists             

Chapter 2. Summarizing and Graphing Data • Types of Data • Quantitative Data • Discrete Data • Continuous Data • Qualitative Data • Nominal Data • Ordinal Categorical Data • Data Summaries • Measures of Central Tendency • Mean • Median • Mode • Measures of Dispersion • Variance • Standard Deviation • Interquartile Range • Statistical Graphs • Histograms • Box Plot • Scatter Plot

Chapter 3. Sampling • Populations and Sample • Simple Random Sample • Other Sampling Methods

Chapter 4. Statistical Estimation • Some Basic Distributions • Normal Distribution • Central Limit Theorem • Student’s T-Distribution • Standard Error of the Mean • Binomial Distribution • Poisson Distribution • Estimation • Point Estimates • Interval Estimates

Section I Problem Set

Section I Problem Set Solutions

SECTION II. IMPORTANT STATISTICAL CONCEPTS FOR ONCOLOGISTS

Chapter 5. Hypothesis Testing • Type I and Type II Errors • p-Values • t-Tests • One-Tailed Versus Two-Tailed • Independent Samples • Paired Data • Wilcoxon Tests • Wilcoxon Rank-Sum Test • Wilcoxon Signed-Rank Test • Analysis of Variance • Testing Binomial Proportions • Confidence Intervals and Hypothesis Tests: How Are They Related? • Sensitivity and Specificity • Negative Predictive Value • Positive Predictive Value • Positive Likelihood Ratio • Negative Likelihood Ratio

Chapter 6. Correlation and Regression • Correlation • Pearson Correlation Coefficient • Spearman Rank Correlation • Regression • Simple Linear Regression • Multiple Linear Regression • Logistic Regression

Chapter 7. Categorical Data Analysis • Contingency Tables • 2 × 2 Tables • R × C Tables • Fisher’s Exact Test
• Chi-Square Test • Chi-Square Test Versus Logistic Regression • Effect Size Estimators • Relative Risk • Odds Ratio • Relative Risk Versus Odds Ratio • McNemar’s Test • Mantel–Haenszel Method • Homogeneity Test • Summary Odds Ratio

Chapter 8. Survival Analysis Methods • Time-to-Event Data • Kaplan–Meier Curves • Median Survival • Log-Rank Test • Wilcoxon Rank-Sum Test • Cox Proportional Hazards Model • Hazard Ratio

Chapter 9. Guide to Choosing the Appropriate Statistical Test

Chapter 10. Noninferiority Analysis

Section II Problem Set

Section II Problem Set Solutions

SECTION III. BASICS OF EPIDEMIOLOGY

Chapter 11. Study Designs • Experimental Studies • Clinical Trials • Common Outcomes for Clinical Trials in Oncology • Phase I Clinical Trials • Phase II Clinical Trials • Phase III Clinical Trials • Phase IV Clinical Trials • Meta-Analysis • Primary Outcomes • Field Trials • Community Intervention Trials • Nonexperimental Studies • Cohort Studies • Retrospective Cohort Study • Prospective Cohort Study • Case-Control Studies • Cohort Studies Versus Case-Control Studies • Cross-Sectional Studies • Matched Studies • Analysis of Studies • Crude Analysis • Bias • Confounding • Stratified Analysis • Effect Modification • Connections to Regressions • Sample Size • Hypothesis Testing • t-Test • Testing Binomial Proportions • Survival Analysis • Regression Analysis

Section III Problem Set

Section III Problem Set Solutions

SECTION IV. SELF-ASSESSMENT QUESTIONS AND ANSWERS

Chapter 12. Self-Study Multiple Choice Questions

Chapter 13. Self-Study Answers and Rationales

Index

About the Authors:

Kara Lynne Leonard, MD, MS

Assistant Professor of Radiation Oncology, Alpert Medical School of Brown University, Providence, Rhode Island.

Adam J. Sullivan, PhD

Assistant Professor of Biostatistics, Alpert Medical School of Brown University, Providence, Rhode Island.

Target Audience:

Provides biostatistical concepts to medical oncologists, radiation oncologists and surgical oncologists.