title: Dose finding with longitudinal data: simpler models, richer outcomes.
abstract: Phase I oncology clinical trials are designed to identify the optimal dose that will be recommended for phase II trials. This dose is typically defined as the dose associated with a certain probability of severe toxicity at cycle 1, although toxicity is repeatedly measured over cycles on an ordinal scale. Recently, a proportional odds mixed-effect model for ordinal outcomes has been proposed to (i) identify the optimal dose accounting for repeated events and (ii) to provide some framework to explore time trend. We compare this approach to a method based on repeated binary variables and to a method based on an under-parameterized model of the dose-time toxicity relationship. We show that repeated binary and ordinal outcomes both improve the accuracy of dose-finding trials in the same proportion; ordinal outcomes are, however, superior to detect time trend even in the presence of nonproportional odds models. Moreover, less parameterized models led to the best operating characteristics. These approaches are illustrated on two dose-finding phase I trials. Integration of repeated measurements is appealing in phase I dose-finding trials.
authors.affiliation: INSERM U900, Institut Curie, Paris, France.
authors.forename: Xavier
authors.initials: X
authors.lastname: Paoletti
authors.affiliation: INSERM U900, Institut Curie, Paris, France.|Centre de recherche INSERM U897, & INRIA SISTM & Université de Bordeaux, ISPED, France.
authors.forename: Adélaïde
authors.initials: A
authors.lastname: Doussau
authors.affiliation: INSERM U900, Institut Curie, Paris, France.
authors.forename: Monia
authors.initials: M
authors.lastname: Ezzalfani
authors.affiliation: European Organization for Research and Treatment of Cancer Headquarters, Brussels, Belgium.
authors.forename: Elisa
authors.initials: E
authors.lastname: Rizzo
authors.affiliation: Centre de recherche INSERM U897, & INRIA SISTM & Université de Bordeaux, ISPED, France.
authors.forename: Rodolphe
authors.initials: R
authors.lastname: Thiébaut
mesh_terms: D000970:Antineoplastic Agents / Q000008:administration & dosage* / Q000009:adverse effects / Q000494:pharmacology; D059248:Chemoradiotherapy; D002648:Child; D017321:Clinical Trials, Phase I as Topic / Q000379:methods / Q000706:statistics & numerical data*; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D000069347:Erlotinib Hydrochloride / Q000008:administration & dosage / Q000494:pharmacology; D005909:Glioblastoma / Q000628:therapy; D006801:Humans; D008137:Longitudinal Studies; D020714:Maximum Tolerated Dose; D008962:Models, Theoretical; D012107:Research Design
chemical_list: D000970:Antineoplastic Agents; D000069347:Erlotinib Hydrochloride
keywords: binary; continual reassessment method; mis-specified; ordinal