© 2005 – Chapman and Hall/CRC
640 pages | 2 Color Illus. | 97 B/W Illus.
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 “¼good 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.
"…The new topics and contributions in this edition include the recently developed tools for high-dimensional data and bioinformatics in clinical oncology research. A new section has been added emphasizing the importance and rapid developments of these topics over the 5 years since the publication of the first edition. Some of the original sections have been updated to include the state-of-the-art knowledge and tools in all topics. The end result is a comprehensive edited volume covering statistical and bioinformatics methods that provide the foundation for important research and clinical trials in cancer. … Like the last edition, this current edition will be an important addition to the libraries of all health research centers. The book will be prized as a reference book for biostatisticians, biomedical researchers, and oncologists for planning, conducting, analyzing, and interpreting cancer research."
—Journal of the American Statistical Association, Vol. 104, No. 487, September 2009
"This is a expanded and revised second edition of a text that was initially well received by the community. The book comprised of 33 chapters, grouped into 6 sections. … The text is extremely well referenced. The authorship represents the leaders in the field. A significant strength of this book is its example-driven approach to the ‘out-of-the-box’ but practical issues faced by those conducting cancer clinical trials. The book provides a critical assessment of the state of science through a thorough review of the methods, applications, and available resources. … a detailed and mostly comprehensive text on the topics of cancer clinical trial design, conduct, analysis, and interpretation."
—Daniel Sargent, Sumithra Mandrekar, and Ann Oberg, Mayo Clinic, Biometrics, December 2006
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