**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.