Handbook of Statistics in Clinical Oncology focuses on clinical trials in phases I, II, and III, proteomic and genomic studies, complementary outcomes and exploratory methods.

Features:

• Provides a comprehensive discussion of sample size
• Explores analytical problems generated by controlling treatment costs and maintaining quality of life
• Demonstrates the breadth and depth of current activity in the field of survival analysis
• Includes recommendations and pointers for free software that allows you to implement programs
• Sets the limits on what can and cannot be concluded from single and multiple clinical trials

Contents

Phase I Trials

• Overview of Phase I Trials
• Phase I and Phase I/II Dose Finding Algorithms Using Continual Reassessment Method
• Choosing a Phase I Design
• Pharmacokinetics in Clinical Oncology: Statistical Issues
• Practical Implementation of the Continual Reassessment Method

Phase II Trials

• Overview of Phase II Clinical Trials
• Designs Based on Toxicity and Response
• Phase II Trials Using Time-to-Event Endpoints
• Phase II Selection Designs
• Bayesian Sensitivity Analyses of Confounded Treatment Effects

Phase III Trials

• On Use of Covariates in Randomization and Analysis of Clinical Trials, G.L. Anderson, M. LeBlanc, P.Y. Liu, and J. Crowley
• Factorial Designs with Time to Event Endpoints, S. Green
• Noninferiority Trials, K.J. Kopecky and S. Green
• Power and Sample Size for Phase III Clinical Trials of Survival, J.J. Shuster
• Early Stopping of Cancer Clinical Trials, J.J. Dignam, J. Bryant, and H.S. Wieand
• Design and Analysis of Quality of Life Data, A.B. Troxel, and C.M. Moinpour
• Economic Analyses Alongside Cancer Clinical Trials

Exploratory Analysis and Prognostic Factors

• Prognostic Factor Studies
• Statistical Methods to Identify Predictive Factors
• Explained Variation in Propotional Hazards Regression
• Constructing Prognostic Groups by Tree-Based Partitioning and Peeling Methods
• Clinical Monitoring Based on Joint Models for Longitudinal Biomarkers and Event Times

High-Throughput Data and Bioinformatics

• Some Practical Considerations for Analysis of Spotted Microarray Data
• Statistical Applications Using DNA Microarrays for Cancer Diagnosis and Prognosis
• Profiling High-Dimensional Protein Expression Using MALDI-TOF: Mass Spectrometry for Biomarker Discovery
• Statistical Approaches for High Dimensional Data Derived from High Throughput Assays: A Case Study of Protein Expression Levels in Lung Cancer
• Spatial Modeling of Multilocus Data
• Software for Genomic Data

Interpreting Clinical Trials

• Interpreting Longitudinal Studies of QOL with Nonignorable Dropout
• Why Kaplan-Meier Fails and Cumulative Incidence Succeeds when Estimating Failure Probabilities in the Presence of Competing Risks
• Pitfalls in the Design, Conduct and Analysis of Randomized Clinical Trials
• Dose-Intensity Analysis
• Sequential Randomization

Index

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