Dose Transition Pathways: The missing link between complex dose-finding designs and simple decision-making

Christina Yap, Lucinda J Billingham, Ying Kuen Cheung, Charles Craddock, John O'Quigley

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
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The ever increasing pace of development of novel therapies mandates efficient methodologies for assessment of their tolerability and activity. Evidence increasingly support the merits of model-based dose-finding designs in identifying the recommended Phase II dose compared to conventional rule-based designs such as the 3+3 but despite this, their use remains limited. Here, we propose a useful tool, Dose Transition Pathways (DTP), which helps overcome several commonly-faced practical and methodological challenges in the implementation of model-based designs. DTP projects in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, de-escalate or stop early), using all the accumulated information. After specifying a model with favourable statistical properties, we utilise the DTP to fine-tune the model to tailor it to the trial's specific requirements that reflect important clinical judgements. In particular, it can help to determine how stringent the stopping rules should be if the investigated therapy is too toxic. Its use to design and implement a modified Continual Reassessment Method is illustrated in an Acute Myeloid Leukaemia trial. DTP removes the fears of model-based designs as unknown, complex systems and can serve as a handbook, guiding decision-making for each dose-update. In the illustrated trial, the seamless, clear transition for each dose-recommendation aided the investigators' understanding of the design and facilitated decision-making to enable finer calibration of a tailored model. We advocate the use of the DTP as an integral procedure in the co-development and successful implementation of practical model-based designs by statisticians and investigators.

Original languageEnglish
Pages (from-to)7440-7447
JournalClinical Cancer Research
Issue number24
Early online date21 Jul 2017
Publication statusPublished - Dec 2017


  • model-based designs
  • rule-based designs
  • continual reassessment method
  • 3+3


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