title: Statistical methods for analyzing sequentially randomized trials.
abstract: In this issue of the Journal, Thall et al. present the results of a clinical trial that makes use of sequential randomization, a novel trial design that allows the investigator to study adaptive treatment strategies. Our aim is to complement this groundbreaking work by reviewing the current state of the art of statistical methods available for such analyses. Using the data collected by Thall et al. as an example, we focus on two different approaches for estimating the success rates of different adaptive treatment strategies of interest. By emphasizing the intuitive appeal and straightforward implementation of these methods and illustrating the striking findings to which these methods can lead, we hope to convince the reader that this novel trial design provides a rich source of information that is made readily accessible through current analytical approaches.
authors.affiliation: Division of Biostatistics, School of Public Health, University of California at Berkeley, Berkeley, CA 94720-7360, USA.
authors.forename: Oliver
authors.initials: O
authors.lastname: Bembom
authors.forename: Mark J
authors.initials: MJ
authors.lastname: van der Laan
mesh_terms: D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D003627:Data Interpretation, Statistical; D006801:Humans; D016015:Logistic Models; D008432:Mathematical Computing; D016017:Odds Ratio; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design; D016879:Salvage Therapy; D016896:Treatment Outcome