Work

Implementation of a Model-Based Design in a Phase Ib Study of Combined Targeted Agents

Year: 2017

Type: article

Abstract: In recent years, investigators have recognized the rigidity of single-agent, safety-only, traditional designs, rendering them ineffective for conducting contemporary early-phase clinical trials, such as those involving combinations and/or biological agents. Novel approaches are required to address these research questions, such as those posed in trials involving targeted therapies. We describe the implementation of a model-based design for identifying an optimal treatment combination, defined by low toxicity and high efficacy, in an early-phase trial evaluating a combination of two oral targeted inhibitors in relapsed/refractory mantle cell lymphoma. Operating characteristics demonstrate the ability of the method to effectively recommend optimal combinations in a high percentage of trials with reasonable sample sizes. The proposed design is a practical, early-phase, adaptive method for use with combined targeted therapies. This design can be applied more broadly to early-phase combination studies, as it was used in an ongoing study of a melanoma helper peptide vaccine plus novel adjuvant combinations. Clin Cancer Res; 23(23); 7158–64. ©2017 AACR.

Source: Clinical Cancer Research

DOI: 10.1158/1078-0432.ccr-17-1069

Authors: Nolan A. Wages, Craig A. Portell, Michael E. Williams, Mark R. Conaway, Gina R. Petroni

Institution: University of Virginia

Language: English

Topic: Statistical Methods in Clinical Trials

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Cancer Institute