Statistical Operating Characteristics of Current Early Phase Dose Finding Designs with Toxicity and Efficacy in Oncology

TL;DR

This paper reviews and compares current model-assisted dose finding designs in oncology that incorporate both toxicity and efficacy to identify the optimal biological dose, especially for emerging therapies where traditional methods may not apply.

Contribution

It provides a comprehensive comparison of existing dose finding designs that consider toxicity and efficacy, highlighting their performance under various scenarios through extensive simulations.

Findings

STEIN, PRINTE, and BOIN12 outperform others in various metrics

Performance varies with dose-response relationship

Simulation and case study validate findings

Abstract

Traditional phase I dose finding cancer clinical trial designs aim to determine the maximum tolerated dose (MTD) of the investigational cytotoxic agent based on a single toxicity outcome, assuming a monotone dose-response relationship. However, this assumption might not always hold for newly emerging therapies such as immuno-oncology therapies and molecularly targeted therapies, making conventional dose finding trial designs based on toxicity no longer appropriate. To tackle this issue, numerous early phase dose finding clinical trial designs have been developed to identify the optimal biological dose (OBD), which takes both toxicity and efficacy outcomes into account. In this article, we review the current model-assisted dose finding designs, BOIN-ET, BOIN12, UBI, TEPI-2, PRINTE, STEIN, and uTPI to identify the OBD and compare their operating characteristics. Extensive simulation studies and a case study using a CAR T-cell therapy phase I trial have been conducted to compare the performance of the aforementioned designs under different possible dose-response relationship scenarios. The simulation results demonstrate that the performance of different designs varies depending on the particular dose-response relationship and the specific metric considered. Based on our simulation results and practical considerations, STEIN, PRINTE, and BOIN12 outperform the other designs from different perspectives.