Utility-based dose selection for phase II dose-finding studies
| Autor: | Gwladys Toulemonde, Jihane Aouni, Jean Noel Bacro, Pierre Colin, Loic Darchy |
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| Přispěvatelé: | Institut Montpelliérain Alexander Grothendieck (IMAG), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Sanofi Aventis R&D [Chilly-Mazarin], Université de Montpellier (UM), Centre National de la Recherche Scientifique (CNRS), Littoral, Environment: MOdels and Numerics (LEMON), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Montpelliérain Alexander Grothendieck (IMAG), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Hydrosciences Montpellier (HSM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Littoral, Environnement : Méthodes et Outils Numériques (LEMON), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Computer science Bayesian probability Dose selection 030226 pharmacology & pharmacy 01 natural sciences 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Range (statistics) Pharmacology (medical) 0101 mathematics Pharmacology Toxicology and Pharmaceutics (miscellaneous) Expected utility hypothesis Rank (computer programming) Bayesian approach Public Health Environmental and Occupational Health Function (mathematics) [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences Interim analysis [STAT]Statistics [stat] Sample size determination Sequential analysis Utility function Sequential trials |
| Zdroj: | Therapeutic Innovation & Regulatory Science Therapeutic Innovation & Regulatory Science, 2021, 55, pp.818-840. ⟨10.1007/s43441-021-00273-0⟩ Therapeutic Innovation & Regulatory Science, Springer, 2021, 55, ⟨10.1007/s43441-021-00273-0⟩ |
| ISSN: | 2168-4790 2168-4804 |
| Popis: | Dose selection is a key feature of clinical development. Poor dose selection has been recognized as a major driver of development failure in late phase. It usually involves both efficacy and safety criteria. The objective of this paper is to develop and implement a novel fully Bayesian statistical framework to optimize the dose selection process by maximizing the expected utility in phase III. The success probability is characterized by means of a utility function with two components, one for efficacy and one for safety. Each component refers to a dose-response model. Moreover, a sequential design (with futility and efficacy rules at the interim analysis) is compared to a fixed design in order to allow one to hasten the decision to perform the late phase study. Operating characteristics of this approach are extensively assessed by simulations under a wide range of dose-response scenarios. Simulation results illustrate the difficulty of simultaneously estimating two complex dose-response models with enough accuracy to properly rank doses using an utility function combining the two. The probability of making the good decision increases with the sample size. For some scenarios, the sequential design has good properties: with a quite large probability of study termination at interim analysis, it enables to reduce the sample size while maintaining the properties of the fixed design. |
| Databáze: | OpenAIRE |
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