ArticleClinical cancer research : an official journal of the American Association for Cancer Research2024
Backfilling Patients in Phase I Dose-Escalation Trials Using Bayesian Optimal Interval Design (BOIN).
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A review of seamless phase I/II trial designs towards oncology dose optimization with examples of clinical pharmacology considerations in early drug development.European journal of clinical pharmacology · 2026Review
- BE-BOIN: A Dose Optimization Design Accommodating Backfill and Late-Onset Toxicity.Therapeutic innovation & regulatory science · 2026Article
- The path forward for T cell engagers in patients with prostate cancer.Journal for immunotherapy of cancer · 2026Review
- Model-Informed Drug Development (MIDD) for Analgesics: Review of Applications, Regulatory Integration, and Emerging Directions.Journal of pain research · 2026Review
- Dose Optimization in Oncology Drug Development: Risk Factors for Postmarketing Requirements and Commitments.Clinical pharmacology and therapeutics · 2025Article
- A robust Bayesian dose optimization design with backfill and randomization for phase I/II clinical trials.Statistical methods in medical research · 2025Article
- BARD: A seamless two-stage dose optimization design integrating backfill and adaptive randomization.Clinical trials (London, England) · 2025Article
- Targeted-Agent Continual Reassessment Method: A Novel Bayesian Enrichment Design for Phase I Trials of Molecularly Targeted Therapies.JCO precision oncology · 2024Article
- Determining doses for backfill cohorts based on patient-reported outcome.BMC medical research methodology · 2024Article
- The potential to backfill in phase I trials: the National Cancer Institute's Cancer Therapy Evaluation Program experience.JNCI cancer spectrum · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
In recent years, there has been increased interest in incorporation of backfilling into dose-escalation clinical trials, which involves concurrently assigning patients to doses that have been previously cleared for safety by the dose-escalation design. Backfilling generates additional information on safety, tolerability, and preliminary activity on a range of doses below the maximum tolerated dose (MTD), which is relevant for selection of the recommended phase II dose and dose optimization. However, in practice, backfilling may not be rigorously defined in trial protocols and implemented consistently. Furthermore, backfilling designs require careful planning to minimize the probability of treating additional patients with potentially inactive agents (and/or subtherapeutic doses). In this paper, we propose a simple and principled approach to incorporate backfilling into the Bayesian optimal interval design (BOIN). The design integrates data from the dose-escalation and backfilling components of the design and ensures that the additional patients are treated at doses where some activity has been seen. Simulation studies demonstrated that the proposed backfilling BOIN design (BF-BOIN) generates additional data for future dose optimization, maintains the accuracy of the MTD identification, and improves patient safety without prolonging the trial duration.
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