TRAFIC: statistical design and analysis plan for a pragmatic early phase 1/2 Bayesian adaptive dose escalation trial in rheumatoid arthritis

Cole, M., Yap, C., Buckley, C., Ng, W. F., McInnes, I. , Filer, A., Siebert, S. , Pratt, A., Isaacs, J. D. and Stocken, D. D. (2021) TRAFIC: statistical design and analysis plan for a pragmatic early phase 1/2 Bayesian adaptive dose escalation trial in rheumatoid arthritis. Trials, 22(1), 433. (doi: 10.1186/s13063-021-05384-5) (PMID:34229728) (PMCID:PMC8259060)

Abstract

Background: Adaptive model-based dose-finding designs have demonstrated advantages over traditional rule-based designs but have increased statistical complexity but uptake has been slow especially outside of cancer trials. TRAFIC is a multi-centre, early phase trial in rheumatoid arthritis incorporating a model-based design. Methods: A Bayesian adaptive dose-finding phase I trial rolling into a single-arm, single-stage phase II trial. Model parameters for phase I were chosen via Monte Carlo simulation evaluating objective performance measures under clinically relevant scenarios and incorporated stopping rules for early termination. Potential designs were further calibrated utilising dose transition pathways. Discussion: TRAFIC is an MRC-funded trial of a re-purposed treatment demonstrating that it is possible to design, fund and implement a model-based phase I trial in a non-cancer population within conventional research funding tracks and regulatory constraints. The phase I design allows borrowing of information from previous trials, all accumulated data to be utilised in decision-making, verification of operating characteristics through simulation, improved understanding for management and oversight teams through dose transition pathways. The rolling phase II design brings efficiencies in trial conduct including site and monitoring activities and cost. TRAFIC is the first funded model-based dose-finding trial in inflammatory disease demonstrating that small phase I/II trials can have an underlying statistical basis for decision-making and interpretation.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: McInnes, Professor Iain and Siebert, Professor Stefan
• Authors: Cole, M., Yap, C., Buckley, C., Ng, W. F., McInnes, I., Filer, A., Siebert, S., Pratt, A., Isaacs, J. D., and Stocken, D. D.
• College/School: College of Medical Veterinary and Life Sciences > School of Infection & Immunity
• Research Centre: College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Immunobiology
• Journal Name: Trials
• Publisher: BioMed Central
• ISSN: 1745-6215
• ISSN (Online): 1745-6215
• Published Online: 06 July 2021
• Copyright Holders: Copyright © The Author(s). 2021
• First Published: First published in Trials 22(1):433
• Publisher Policy: Reproduced under a Creative Commons Licence

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
169450		MICA: Targeting the RA synovial fibroblast via cyclin dependent kinase inhibition - a phase IIa study	Stefan Siebert	Medical Research Council (MRC)	MR/L005123/1	Institute of Infection, Immunity & Inflammation