Handbook of Statistics in Clinical Oncology, Second Edition

A compendium of cutting-edge statistical approaches to solving problems in clinical oncology, Handbook of Statistics in Clinical Oncology, Second Edition focuses on clinical trials in phases I, II, and III, proteomic and genomic studies, complementary outcomes and exploratory methods. Cancer Forum called the first edition a "A good reference book for statisticians who will be designing and analyzing cancer trials." The second edition includes over 1000 references, more than forty world-renowned contributors, and 300 equations, tables, and drawings. During the five years since publication of the first edition, there has been an explosion in the technological capabilities supporting genomic and proteomic research, which are is now firmly implanted in clinical oncology. Reflecting these developments, the second edition contains a new section devoted to analyses of high-throughput data and bioinformatics. Previous chapters of the first edition have been revised to reflect current state of the art in their respective domains. The intended audience is primarily statisticians working in cancer and more generally, in any discipline of medicine. But oncologists too will find the material accessible and will benefit from a rudimentary understanding of the fundamental concepts laid forth in each chapter. Completely revised while keeping the features that made the first edition a bestseller, this is the best single source for up-to-date statistical approaches to research in clinical medicine. More than just an update of the handbook that became the gold standard, this second edition brings you fully into the genomic era of medicine.

Table of Contents:
Contents Phase I Trials Overview of Phase I Trials, L. Edler and I. Burkholder Phase I and Phase I/II Dose Finding Algorithms Using Continual Reassessment Method, J. O’Quigley Choosing a Phase I Design, B. E. Storer Pharmacokinetics in Clinical Oncology: Statistical Issues, G.L. Rosner, P. Müller, S. Lunagomez, and P.A. Thompson Practical Implementation of the Continual Reassessment Method, N. Ishizuka and S. Morita Phase II Trials Overview of Phase II Clinical Trials, S. Green Designs Based on Toxicity and Response, G.R. Petroni and M.R. Conaway Phase II Trials Using Time-to-Event Endpoints, C.M. Tangen and J.J. Crowley Phase II Selection Designs, P.Y. Liu, J. Moon, and M. LeBlanc Bayesian Sensitivity Analyses of Confounded Treatment Effects, P.F. Thall and X. Wang 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, S.D. Ramsey Exploratory Analysis and Prognostic Factors Prognostic Factor Studies, M. Schumacher, N. Holländer, G. Schwarzer, and W. Sauerbrei Statistical Methods to Identify Predictive Factors, K. Ulm, M. Seebauer, S. Eberle, M. Reck, and S. Hessler Explained Variation in Propotional Hazards Regression, J.O. Quigly and R. Xu Constructing Prognostic Groups by Tree-Based Partitioning and Peeling Methods, M. LeBlanc, E. Rasmussen, and J. Crowley Clinical Monitoring Based on Joint Models for Longitudinal Biomarkers and Event Times, D. Pauler Ankerst and D.M. Finkelstein High-Throughput DatA and Bioinformatics Some Practical Considerations for Analysis of Spotted Microarray Data, L. Hsu, J.R. Faulkner, D. Grove, and D. Pauler Ankerst Statistical Applications Using DNA Microarrays for Cancer Diagnosis and Prognosis, S. Matsui Profiling High-Dimensional Protein Expression Using MALDI-TOF: Mass Spectrometry for Biomarker Discovery, Y. Yasui, T. Randolph, and Z. Feng Statistical Approaches for High Dimensional Data Derived from High Throughput Assays: A Case Study of Protein Expression Levels in Lung Cancer, Y. Shyr Spatial Modeling of Multilocus Data, D.V. Conti, D.O. Stram, J. Molitor, P. Marjoram, and D.C. Thomas Software for Genomic Data, R. Gentleman Interpreting Clinical Trials Interpreting Longitudinal Studies of QOL with Nonignorable Dropout, D.L. Fairclough Why Kaplan-Meier Fails and Cumulative Incidence Succeeds when Estimating Failure Probabilities in the Presence of Competing Risks, T.A. Gooley, W. Leisenring, J. Crowley, and B.E. Storer Pitfalls in the Design, Conduct and Analysis of Randomized Clinical Trials, R.J. Stephens Dose-Intensity Analysis, J. Pater Sequential Randomization, J. Pater and J. Crowley