Utility-Based Dose Optimization Approaches for Multiple-Dose Randomized Trial Designs Accounting for Multiple Endpoints

TL;DR

This paper introduces novel utility-based methods, U-MET-m and CUI-MET, for dose optimization in early-phase oncology trials that consider multiple endpoints and doses, improving the identification of the optimal biological dose.

Contribution

The paper extends existing utility score approaches to handle multiple endpoints and doses using Bayesian inference, providing new methods for dose optimization in complex trial settings.

Findings

U-MET-m and CUI-MET show satisfactory operating characteristics.

The methods effectively compare utility metrics across doses.

Recommended as primary or supportive approaches for dose selection.

Abstract

The initiation of dose optimization has driven a paradigm shift in oncology clinical trials to determine the optimal biological dose (OBD). Early-phase trials with randomized doses can facilitate additional investigation of the identified OBD in targeted populations by incorporating safety, efficacy, and biomarker data. To support dose comparison in such settings, we propose to extend the utility score-based approach (U-MET) and introduce the clinical utility index-based approach (CUI-MET) to account for multiple endpoints and doses. The utility-based dose optimization approach for multiple-dose randomized trial designs accounting for multiple endpoints and doses (U-MET-m) extends the U-MET, using a utility score to account for multiple endpoints jointly (e.g., toxicity-efficacy trade-off), while the CUI-MET uses a utility index to do this marginally. U-MET-m and CUI-MET use Bayesian inference within a hypothesis framework to compare utility metrics across doses to identify the OBD. Here we describe simulation studies and present an example to compare the U-MET-m design, CUI-MET, and empirical design. The U-MET-m design and CUI-MET were shown to have satisfactory operating characteristics for selecting the OBD. Based on these findings, we recommend using the U-MET-m and CUI-MET designs as the primary dose comparison approach or as supportive evidence to select the OBD.