title: Dose finding when the target dose is on a plateau of a dose-response curve: comparison of fully sequential designs.
abstract: Consider the problem of estimating a dose with a certain response rate. Many multistage dose-finding designs for this problem were originally developed for oncology studies where the mean dose-response is strictly increasing in dose. In non-oncology phase II dose-finding studies, the dose-response curve often plateaus in the range of interest, and there are several doses with the mean response equal to the target. In this case, it is usually of interest to find the lowest of these doses because higher doses might have higher adverse event rates. It is often desirable to compare the response rate at the estimated target dose with a placebo and/or active control. We investigate which of the several known dose-finding methods developed for oncology phase I trials is the most suitable when the dose-response curve plateaus. Some of the designs tend to spread the allocation among the doses on the plateau. Others, such as the continual reassessment method and the t-statistic design, concentrate allocation at one of the doses with the t-statistic design selecting the lowest dose on the plateau more frequently.
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Anastasia
authors.initials: A
authors.lastname: Ivanova
authors.forename: Changfu
authors.initials: C
authors.lastname: Xiao
mesh_terms: D017321:Clinical Trials, Phase I as Topic / Q000706:statistics & numerical data; D017322:Clinical Trials, Phase II as Topic / Q000706:statistics & numerical data*; D015331:Cohort Studies; D004305:Dose-Response Relationship, Drug; D016503:Drug Delivery Systems / Q000706:statistics & numerical data*; D006801:Humans; D012107:Research Design / Q000706:statistics & numerical data*
keywords: continual reassessment method; group up-and-down designs; phase II trials; proof of concept; t-statistic design
references.citation: Stat Med. 2009 Oct 30;28(24):2941-51
references.pmid: 19731265
references.citation: Contemp Clin Trials. 2005 Jun;26(3):349-64
references.pmid: 15911469
references.citation: Biometrics. 1996 Jun;52(2):673-84
references.pmid: 8672707
references.citation: J Biopharm Stat. 1994 Jul;4(2):147-64
references.pmid: 7951271
references.citation: Stat Med. 2006 Nov 15;25(21):3668-78
references.pmid: 16381057
references.citation: Biometrics. 2000 Dec;56(4):1177-82
references.pmid: 11129476
references.citation: J Stat Plan Inference. 2012 Jul 1;142(7):1899-1907
references.pmid: 22711972
references.citation: Stat Med. 2008 May 10;27(10):1612-25
references.pmid: 17876763
references.citation: Biometrics. 1990 Mar;46(1):33-48
references.pmid: 2350571
references.citation: Stat Med. 1995 Jun 15;14(11):1149-61
references.pmid: 7667557
references.citation: Stat Med. 2012 Oct 30;31(24):2872-81
references.pmid: 22865626
references.citation: J Biopharm Stat. 2007;17(6):1097-115
references.pmid: 18027219
references.citation: Biometrics. 2009 Mar;65(1):307-15
references.pmid: 18479486