Handbook of Statistics in Clinical Oncology

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This revised edition features contributions from leading cancer trial statisticians, providing expert insights into modern oncology trial design and methodology and provides a comprehensive resource for researchers, clinicians, and statisticians involved in the evolving landscape of oncology clinical trials.

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.

Obsah

SECTION 1 Cancer Prevention & Screening

Chapter 1 Cancer Screening Trials

Chapter 2 Cancer Risk Prediction Models

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

SECTION 2 Trial Design | Early-Phase Trials

Chapter 4 Phase I – Overview and Recent Trial Designs

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

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

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

Chapter 8 Phase II Selection Designs

Chapter 9 Phase II Trials with Multiple Strata

SECTION 3 Trial Design | Late-Phase Trials

Chapter 10 Cure Rate Survival Models

Chapter 11 Phase III Trials for Targeted Agents

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

Chapter 13 SMARTs in Oncology

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

Chapter 15 Alpha Splitting

Chapter 16 Early Stopping of Clinical Trials Evaluating Targeted Therapies

Chapter 17 Noninferiority Trials

Chapter 18 Considerations for Pediatric Oncology Trials

SECTION 4 Trial Conduct

Chapter 19 An Overview of Master Protocols

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

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

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

Chapter 23 Outcome-Adaptive Randomization

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

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

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

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

Chapter 28 Streamlining Data Collection and Trial Conduct

SECTION 5 Beyond the Primary Endpoint

Chapter 29 Use of Circulating Tumor DNA in Oncology – ctMoniTR

Chapter 30 Statistical Analysis of -Omics Data

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

Chapter 32 X Intermediate and Surrogate Endpoints in Phase III Randomized

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