title: Design and analysis of dose-finding studies combining multiple comparisons and modeling procedures.
abstract: The search for an adequate dose involves some of the most complex series of decisions to be made in developing a clinically viable product. Typically decisions based on such dose-finding studies reside in two domains: (i) "proof" of evidence that the treatment is effective and (ii) the need to choose dose(s) for further development. We consider a unified strategy for designing and analyzing dose-finding studies, including the testing of proof-of-concept and the selection of one or more doses to take into further development. The methodology combines the advantages of multiple comparisons and modeling approaches, consisting of a multi-stage procedure. Proof-of-concept is tested in the first stage, using multiple comparison methods to identify statistically significant contrasts corresponding to a set of candidate models. If proof-of-concept is established in the first stage, the best model is then used for dose selection in subsequent stages. This article describes and illustrates practical considerations related to the implementation of this methodology. We discuss how to determine sample sizes and perform power calculations based on the proof-of-concept step. A relevant topic in this context is how to obtain good prior values for the model parameters: different methods to translate prior clinical knowledge into parameter values are presented and discussed. In addition, different possibilities of performing sensitivity analyses to assess the consequences of misspecifying the true parameter values are introduced. All methods are illustrated by a real dose-response phase II study for an anti-anxiety compound.
authors.affiliation: Biostatistics and Statistical Reporting Department, Novartis Pharmaceuticals, East Hanover, New Jersey 07936, USA. jose.pinheiro@novartis.com
authors.forename: José
authors.initials: J
authors.lastname: Pinheiro
authors.forename: Björn
authors.initials: B
authors.lastname: Bornkamp
authors.forename: Frank
authors.initials: F
authors.lastname: Bretz
mesh_terms: D000465:Algorithms; D014151:Anti-Anxiety Agents / Q000008:administration & dosage / Q000627:therapeutic use; D001008:Anxiety Disorders / Q000188:drug therapy; D017322:Clinical Trials, Phase II as Topic / Q000379:methods / Q000706:statistics & numerical data*; D004305:Dose-Response Relationship, Drug; D006801:Humans; D015233:Models, Statistical; D012107:Research Design; D018401:Sample Size; D016896:Treatment Outcome
chemical_list: D014151:Anti-Anxiety Agents