TWICEBEE: A Two-stage Intra-patient Curve-free Bayesian Decision-Theoretic Dose Escalation Design

TL;DR

This paper introduces TWICEBEE, a Bayesian dose-escalation method for multi-cycle immunotherapy, accounting for decreasing toxicity over cycles, with a two-stage design validated through simulations.

Contribution

It extends the c-CFBD Bayesian framework to handle decreasing toxicity across treatment cycles in intra-patient dose escalation.

Findings

The design effectively estimates cycle-specific maximum tolerated doses.

Simulation results show favorable safety and efficiency characteristics.

The method is tailored for CAR T cell therapy and similar treatments.

Abstract

We propose a novel Phase I intra-patient dose-escalation design tailored for multi-cycle immunotherapy settings, in which toxicity at a fixed dose level is clinically expected to decrease over successive treatment cycles. This design was motivated by a phase I trial of CAR T cell therapy, an emerging cellular immunotherapy with established applications in cancer and growing investigation in autoimmune disease. The design is intended for settings in which nonincreasing cycle-specific toxicity assumption is clinically justified. Specifically, we build on the extrapolation property of the modified curve-free Bayesian decision-theoretic (c-CFBD) design for two-agent trials (Xu, et al. 2025), treating treatment cycle as a second dimension. By redefining the partial order, the c-CFBD framework can accommodate the reduction in toxicity across cycles. The proposed design adopts a two-stage structure: an initial accelerated titration stage to rapidly explore dose levels, followed by a c-CFBD stage to improve safety and estimate the cycle-specific maximum tolerated dose sequence. Simulation studies across a range of scenarios demonstrate favorable operating characteristics.