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June 21, 2026Biometrics

A Bayesian phase I/II platform design with data augmentation accounting for delayed outcomes

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Authors

WYWentao YangRMRongji MuZYZhangsheng Yu

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Overview

Randomized trial demonstrates improved dose optimization in drug therapy, suggesting enhanced trial efficiency.

Key Points

  • This research aims to improve dose selection in clinical trials by addressing delayed outcomes.
  • Proposes a Bayesian phase I/II platform design with data augmentation for managing delayed outcomes.
  • Employs hierarchical modeling to borrow information across multiple indications.
  • Conducts simulation studies to assess the robustness and efficiency of the proposed approach.
  • Accurate dose-toxicity and dose-efficacy estimates are achieved, facilitating timely decisions.
  • Significant reduction in trial durations is observed, enhancing overall clinical trial efficiency.
  • The method shows flexibility in managing various indications and outcomes, leading to improved decision-making.

Cite This Study

Yang et al. (2026) studied this question.

synapsesocial.com/papers/6a3781db24f042ddf4c5b7cfhttps://doi.org/10.1093/biomtc/ujag096
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Bayesian phase I/II platform design with survival efficacy endpoint for dose optimization2026
  2. 2A Bayesian design with efficient backfilling and expansion to accelerate phase I/II trials accommodating late-onset competing risk outcomes2026
  3. 3A robust Bayesian dose optimization design with backfill and randomization for phase I/II clinical trials2025
  4. 4BAP: Bayesian Biomarker-Assisted Platform Design for Dose Ranging in Multi-Agent Multi-Dose Trials2026
  5. 5A Bayesian latent-subgroup platform design for dose optimization2024 · 4 citations