4th Edition

Handbook of Statistics in Clinical Oncology

Edited By Antje Hoering, Megan Othus, John Crowley Copyright 2026
540 Pages 94 B/W Illustrations
by Chapman & Hall

Since the third edition of this handbook, significant advances have transformed the field of oncology. Most cancer types now offer multiple treatment options, with immunotherapies and targeted therapies becoming the standard of care. Master protocols, which allow the addition of new treatment arms without requiring new protocols, have gained popularity—not only to expedite the approval process for new therapies but also to ensure that patients receive the most beneficial treatments tailored to their individual needs. This revised edition features contributions from leading cancer trial statisticians, providing expert insights into modern oncology trial design and methodology. The handbook is structured into five key parts:

  • Part 1: Cancer prevention and screening trial designs, including risk prediction models and prevention trials
  • Part 2: Early-phase trial designs, covering dose-finding studies, selection designs, and multi-strata trials
  • Part 3: Late-stage trial designs, including approaches for IO therapies, cure-rate models, targeted agents, and considerations for pediatric oncology trials
  • Part 4: Trial conduct and operations, addressing best practices for Data Monitoring Committees (DMCs), SWOG/CRAB calculators, pragmatic trials, and clinical trial innovation
  • Part 5: Beyond primary endpoints, exploring surrogate endpoints, microbiome research, patient-reported outcomes (PROs), and tree-based partitioning methods

This updated edition provides a comprehensive resource for researchers, clinicians, and statisticians involved in the evolving landscape of oncology clinical trials.

SECTION 1 Cancer Prevention & Screening

Chapter 1 Cancer Screening Trials

by Ruth Etzioni and Noel S Weiss

Chapter 2 Cancer Risk Prediction Models

by Oksana Chernova, Ruth M. Pfeiffer, and Donna P. Ankerst

Chapter 3 Incorporating External Registry Data Into Cohort-based Cancer Risk Prediction Tools

by Oksana Chernova, Ruth M. Pfeiffer, and Donna P. Ankerst

 

SECTION 2 Trial Design | Early-Phase Trials

Chapter 4 Phase I – Overview and Recent Trial Designs

by Motomi Mori

Chapter 5 Statistical and Machine Learning Methods for Phase I Dose-Finding

by Keiichiro Seno, Masataka Igeta, Kota Matsui, Takashi Daimon, and Shigeyuki Matsui

Chapter 6 Seamless Phase I/II Trial Design for Assessing Toxicity and Efficacy for Targeted Agents

by by Antje Hoering, Michael LeBlanc, and John Crowley

Chapter 7 Designs Using Time to Event Endpoints / Single Arm versus Randomized Phase II Designs

by Cathy Tangen and John Crowley

Chapter 8 Phase II Selection Designs

by James Moon, Michael LeBlanc, Michael Wu, P. Y. Liu, and Sarah Samorodnitsky

Chapter 9 Phase II Trials with Multiple Strata

by Michael LeBlanc, Cathryn Rankin, and John Crowley

 

SECTION 3 Trial Design | Late-Phase Trials

Chapter 10 Cure Rate Survival Models

by Subodh Selukar and Megan Othus

Chapter 11 Phase III Trials for Targeted Agents

by Antje Hoering, Michael LeBlanc, and John Crowley

Chapter 12 Phase II and III Clinical Trial Designs for Precision Medicine

by Shigeyuki Matsui and Masataka Igeta

Chapter 13 SMARTs in Oncology

by Sarah Medley and Kelley M. Kidwell  

Chapter 14 Statistical Considerations in the Design and Analysis of Cancer Trials with Immune-Oncology Therapies

by Susan Halabi

Chapter 15 Alpha Splitting

by Steve Snapinn

Chapter 16 Early Stopping of Clinical Trials Evaluating Targeted Therapies

by Mary W. Redman and Megan Othus

Chapter 17 Noninferiority Trials

by Ken Kopecky and Stephanie Green

Chapter 18 Considerations for Pediatric Oncology Trials

by Lindsay Renfro and Todd Alonzo

 

SECTION 4 Trial Conduct

 

Chapter 19 An Overview of Master Protocols

by Megan Othus and Michael LeBlanc

Chapter 20 On Use of Covariates in Randomization and Analysis of Clinical Trials

by Garnet Anderson, Michael LeBlanc, PY Liu, and John Crowley

Chapter 21 Pragmatic Clinical Trials in Clinical Oncology: A Statistical Perspective

by Aasthaa Bansal and Scott Ramsey

Chapter 22 Dynamic Treatment Regimens and Sequential Multiple Assignment Randomized Trial in Cancer Research

by Yingqi Zhao

Chapter 23 Outcome-Adaptive Randomization

by Ed Korn and Boris Freidlin

Chapter 24 Current Suggested Practices and Issues for Data and Safety Monitoring Committees in Cancer Clinical Trials

by Catherine M. Tangen and John Crowley

Chapter 25 Improving Data Collection: EHR-to-EDC Assisted Data Transfer

by Keith Goodman and Chris Cook

Chapter 26 Barriers and Disparities in Access to Cancer Clinical Trials – Causes and Implications 

by Joseph M. Unger

Chapter 27 SWOG Statistical Calculators for Design and Analysis of Clinical Trials

by Adam Rosenthal, Rachael Sexton, Katie Snapinn, Emily Goren, Antje Hoering, John Crowley, and Michael Leblanc

Chapter 28 Streamlining Data Collection and Trial Conduct

by Mandrekar and Shauna Hillman

 

SECTION 5 Beyond the Primary Endpoint

Chapter 29 Use of Circulating Tumor DNA in Oncology – ctMoniTR

by Emily Goren, Katie Nishimura, Adam Rosenthal, Megan Eisele, Nevine Zariffa, Mark Stewart, Hillary S. Andrews, Antje Hoering, and Jeff Allen

Chapter 30 Statistical Analysis of -Omics Data

by Amarise Little, Wodan Ling, Anna M. Plantinga, Sarah Samorodnitsky, Michael C. Wu, and Ni Zhao

Chapter 31 Principles of Design and Analysis for Patient-Reported Outcomes

by Joseph M. Unger and Riha Vaidya

Chapter 32 X Intermediate and Surrogate Endpoints in Phase III Randomized

by Edward L. Korn and Boris Freidlin

Chapter 33 Prognostic Groups via Interpretable Function Approximation: Tree-based and Extreme Regression Models

by Michael LeBlanc, Antje Hoering Caleb McKinney, and John Crowley  

Biography

Antje Hoering is the President and CEO of Cancer Research And Biostatistics (CRAB) and leads a team of approximately eighty talented and dedicated oncology research professionals, all united in our mission to help conquer cancer. She also serves as the lead statistician of the SWOG Myeloma Committee and holds affiliate appointments at the University of Washington Biostatistics department and the Fred Hutch Cancer Center.

Megan Othus is a Professor of Biostatistics at the Fred Hutchinson Cancer. She serves as the lead statistician of the SWOG Leukemia and Rare Cancer Committees. Her research interests focus on the design and endpoints in oncology clinical trials.

John Crowley received his master’s and doctorate degrees (in 1970 and 1973, respectively) in Biomathematics from the University of Washington, and was the Director of the SWOG Statistical Center from 1984 to 2012. In 1997 Dr. Crowley founded Cancer Research And Biostatistics (CRAB), was the President and CEO of CRAB until 2014, and currently serves as the Chief of Strategic Alliances. Dr. Crowley's research interests focus on the design and analysis of cancer clinical and translation trials.