title: Statistical Challenges in the Design of Late-Stage Cancer Immunotherapy Studies.
abstract: The past several years have witnessed a revival of interest in cancer immunology and immunotherapy owing to striking immunologic and clinical responses to immune-directed anticancer therapies and leading to the selection of "Cancer Immunotherapy" as the 2013 Breakthrough of the Year by Science. But statistical challenges exist at all phases of clinical development. In phase III trials of immunotherapies, survival curves have been shown to demonstrate delayed clinical effects, as well as long-term survival. These unique survival kinetics could lead to loss of statistical power and prolongation of study duration. Statistical assumptions that form the foundations for conventional statistical inference in the design and analysis of phase III trials, such as exponential survival and proportional hazards, require careful considerations. In this article, we describe how the unique characteristics of patient response to cancer immunotherapies will impact our strategies on statistical design and analysis in late-stage drug development.
authors.affiliation: Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania.
authors.forename: Rosemarie
authors.initials: R
authors.lastname: Mick
authors.affiliation: Department of Global Biometric Sciences, Bristol-Myers Squibb, Princeton, New Jersey. Department of Biostatistics, Columbia University, New York, New York. tai-tsang.chen@bms.com.
authors.forename: Tai-Tsang
authors.initials: TT
authors.lastname: Chen
mesh_terms: D019496:Cancer Vaccines / Q000276:immunology*; D006801:Humans; D007167:Immunotherapy / Q000379:methods*; D009369:Neoplasms / Q000276:immunology* / Q000628:therapy*; D012107:Research Design
chemical_list: D019496:Cancer Vaccines