A Bayesian Phase I/II basket design with robust information borrowing to identify subtrial-specific optimal biological doses

2026-06-22

AI Summary

This study addresses the challenge of heterogeneous dose–toxicity and dose–efficacy relationships across sub-studies in basket early-phase oncology trials, where conventional unified dose-finding approaches often fail to identify sub-study-specific optimal biological doses (OBDs). The authors propose a Bayesian phase I/II design based on an extended exchangeability–nonexchangeability (EXNEX) framework that adaptively modulates the degree of information borrowing across sub-studies. The OBD is determined by maximizing a utility function incorporating monotonic logistic regression for toxicity and a quadratic model for continuous efficacy, both scaled to a common metric. Simulation studies across four sub-studies, five dose levels, and 70 OBD configurations demonstrate that the proposed method substantially improves OBD selection accuracy and reduces the risk of overdosing compared to non-borrowing strategies, with particularly pronounced advantages when sub-studies exhibit high similarity.

Abstract

The objective of modern early oncology dose-finding is to identify an optimal biological dose (OBD), rather than simply the maximum tolerated dose. In basket trials, the dose-toxicity and dose-efficacy relationships may differ across biomarker or disease-defined subtrials, so a single common dose from pooled analysis may be suboptimal. We propose a flexible exchangeability-non-exchangeability (EXNEX) dose finding design (DF-EXNEX design) for subtrial-specific OBD selection in basket phase I/II trials with binary toxicity and continuous efficacy endpoints. Patient toxicity is modelled by a monotone logistic regression and efficacy by a quadratic dose-response curve. Robust borrowing is introduced through extended EXNEX mixture priors on the subtrial-specific curve parameters, allowing the strength of borrowing to adapt to the similarity of subtrials. Dose recommendation is based on an admissible set defined by posterior safety and futility rules, and an OBD-oriented utility function combining toxicity and efficacy on comparable scales. The operating characteristics were evaluated in a large-scale simulation study for the basket trial with four subtrials and five dose levels, and 70 scenarios covering all non-redundant combinations of true subtrial-specific OBD locations. Results showed that, compared with a no-borrowing NEX design, the DF-EXNEX design can increase the correct OBD selection for most scenarios while reducing overly toxic recommendation as final OBD. The improvement increased with subtrial similarity due to robust information borrowing, but a small number of mixed low/high OBD scenarios showed negative or near-zero gains, consistent with occasional over-borrowing towards intermediate doses. These results support robust borrowing for subtrial-specific OBD finding while highlighting the need to monitor borrowing behaviour when true OBDs are widely separated.

Problem

• optimal biological dose
• basket trial
• subtrial-specific
• dose-finding
• information borrowing

Innovation

• Bayesian basket trial
• optimal biological dose
• robust information borrowing
• EXNEX prior
• dose-finding design