title: Spline-based procedures for dose-finding studies with active control.
abstract: In a dose-finding study with an active control, several doses of a new drug are compared with an established drug (the so-called active control). One goal of such studies is to characterize the dose-response relationship and to find the smallest target dose concentration d(*), which leads to the same efficacy as the active control. For this purpose, the intersection point of the mean dose-response function with the expected efficacy of the active control has to be estimated. The focus of this paper is a cubic spline-based method for deriving an estimator of the target dose without assuming a specific dose-response function. Furthermore, the construction of a spline-based bootstrap CI is described. Estimator and CI are compared with other flexible and parametric methods such as linear spline interpolation as well as maximum likelihood regression in simulation studies motivated by a real clinical trial. Also, design considerations for the cubic spline approach with focus on bias minimization are presented. Although the spline-based point estimator can be biased, designs can be chosen to minimize and reasonably limit the maximum absolute bias. Furthermore, the coverage probability of the cubic spline approach is satisfactory, especially for bias minimal designs.
authors.affiliation: Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.
authors.forename: Hans-Joachim
authors.initials: HJ
authors.lastname: Helms
authors.forename: Norbert
authors.initials: N
authors.lastname: Benda
authors.forename: Jörg
authors.initials: J
authors.lastname: Zinserling
authors.forename: Thomas
authors.initials: T
authors.lastname: Kneib
authors.forename: Tim
authors.initials: T
authors.lastname: Friede
mesh_terms: D015982:Bias; D017322:Clinical Trials, Phase II as Topic / Q000379:methods*; D003198:Computer Simulation; D016001:Confidence Intervals; D004305:Dose-Response Relationship, Drug; D023381:Endpoint Determination / Q000379:methods; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models; D012044:Regression Analysis; D012107:Research Design
keywords: active control; design considerations; dose-finding study; spline interpolation