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Embracing model-based designs for dose-finding trials.
Love, Sharon B; Brown, Sarah; Weir, Christopher J; Harbron, Chris; Yap, Christina; Gaschler-Markefski, Birgit; Matcham, James; Caffrey, Louise; McKevitt, Christopher; Clive, Sally; Craddock, Charlie; Spicer, James; Cornelius, Victoria.
Affiliation
  • Love SB; Oxford Clinical Trials Research Unit, Centre for Statistics in Medicine, NDORMS, University of Oxford, Botnar Research Centre, Windmill Road, Oxford OX3 7LD, UK.
  • Brown S; Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds LS2 9JT, UK.
  • Weir CJ; Edinburgh Clinical Trials Unit, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh Medical School, Teviot Place, Edinburgh EH8 9AG, UK.
  • Harbron C; Roche Pharmaceuticals, 6 Falcon Way, Shire Park, Welwyn Garden City AL7 1TW, UK.
  • Yap C; Cancer Research UK Clinical Trials Unit, Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK.
  • Gaschler-Markefski B; Boehringer Ingelheim Pharma GmbH &Co. KG, Biostatistics and Data Sciences, Birkendorfer Strasse 65, Biberach an der Riss 88400, Germany.
  • Matcham J; AstraZeneca, DaVinci Building, Melbourn Science Park, Royston SG8 6HB, UK.
  • Caffrey L; School of Social Work and Social Policy, Trinity College Dublin, College Green, Dublin 2, Ireland.
  • McKevitt C; Division of Health and Social Care Research, Faculty of Life Sciences and Medicine, King's College London, London, UK.
  • Clive S; Edinburgh Cancer Centre, Western General Hospital, Edinburgh EX4 2XU, UK.
  • Craddock C; Centre for Clinical Haematology, Haematology - University Hospitals Birmingham NHS Foundation Trust, Queen Elizabeth Hospital, Queen Elizabeth Medical Centre, Birmingham B15 2TH, UK.
  • Spicer J; Division of Cancer Studies, Bermondsey Wing, Guy's Hospital, Great Maze Pond, London SE1 9RT, UK.
  • Cornelius V; Imperial Clinical Trials Unit, Imperial College London, Stadium House, 68 Wood Lane, London W12 7RH, UK.
Br J Cancer ; 117(3): 332-339, 2017 Jul 25.
Article in En | MEDLINE | ID: mdl-28664918
BACKGROUND: Dose-finding trials are essential to drug development as they establish recommended doses for later-phase testing. We aim to motivate wider use of model-based designs for dose finding, such as the continual reassessment method (CRM). METHODS: We carried out a literature review of dose-finding designs and conducted a survey to identify perceived barriers to their implementation. RESULTS: We describe the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources. The most prominent barriers to implementation of a model-based design were lack of suitable training, chief investigators' preference for algorithm-based designs (e.g., 3+3), and limited resources for study design before funding. We use a real-world example to illustrate how these barriers can be overcome. CONCLUSIONS: There is overwhelming evidence for the benefits of CRM. Many leading pharmaceutical companies routinely implement model-based designs. Our analysis identified barriers for academic statisticians and clinical academics in mirroring the progress industry has made in trial design. Unified support from funders, regulators, and journal editors could result in more accurate doses for later-phase testing, and increase the efficiency and success of clinical drug development. We give recommendations for increasing the uptake of model-based designs for dose-finding trials in academia.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Research Personnel / Models, Statistical / Clinical Trials, Phase I as Topic / Maximum Tolerated Dose Type of study: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Year: 2017 Type: Article

Full text: 1 Database: MEDLINE Main subject: Research Personnel / Models, Statistical / Clinical Trials, Phase I as Topic / Maximum Tolerated Dose Type of study: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Year: 2017 Type: Article