We propose to develop designs for phase I trials conducted in heterogeneous groups of patients. Phase I trials in oncology are meant to establish the 'maximally tolerated dose'(MTD), the highest dose that can be administered without excessive side effects. In many studies, the group structure is not used in the design. The resulting recommended dose is weighted in favor of the dose for the most frequently occurring group, effectively moving away from 'personalized'dosing for patients. At present, the most common way to include the group structure as part of the design is to conduct a separate phase I trial within each group. This can be inefficient, requiring a large number of patients, and can lead to dose recommendations that run counter to what is known clinically about the groups. In this proposal, we will develop efficient designs for phase I trials in groups that build from our previous work in designs for combinations of agent. Our goal is to develop efficient and more accurate designs for phase I trials in groups of patients that can lead to improved care across the entire range of cancers and cancer therapies.

Public Health Relevance

Dose-finding trials of new agents in oncology are often done in groups of patients, where the safe dose varies by group. In many of these studies, it is known before the start of the study that the groups are ordered, meaning that for any fixed dose of the agent, the groups can be ordered in terms of the probability that a patient will experience a severe side effect. In some cases, the grouping is ignored in the design of the trial, and a single dose is recommended for all the patients. The effect of this is to weigh the recommended dose in favor of the most frequent group, and potentially expose patients in other groups to overly toxic doses or sub-optimal therapies. In studies that use the group information, the most common design is to run separate studies in each group. This can be inefficient and can lead to recommended doses that run counter to what is known about the ordering of the groups. In this proposal, we will develop methods that allow us to use the information from all the patients in all the groups to estimate the safe dose within each group. The goal is to have efficient designs that 'personalize'doses within groups.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Cancer Biomarkers Study Section (CBSS)
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Witherspoon, Kim
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University of Virginia
Public Health & Prev Medicine
Schools of Medicine
United States
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Iasonos, Alexia; O'Quigley, John (2014) Adaptive dose-finding studies: a review of model-guided phase I clinical trials. J Clin Oncol 32:2505-11
Wages, Nolan A; Conaway, Mark R (2014) Phase I/II adaptive design for drug combination oncology trials. Stat Med 33:1990-2003
O'Quigley, John; Iasonos, Alexia (2014) Bridging Solutions in Dose Finding Problems. Stat Biopharm Res 6:185-197
Wages, Nolan A; Conaway, Mark R; O'Quigley, John (2014) Comments on 'A dose-finding approach based on shrunken predictive probability for combinations of two agents in phase I trials' by Akihiro Hirakawa, Chikuma Hamada, and Shigeyuki Matsui. Stat Med 33:2156-8
Wages, Nolan A; O'Quigley, John; Conaway, Mark R (2014) Phase I design for completely or partially ordered treatment schedules. Stat Med 33:569-79
Wages, Nolan A; Conaway, Mark R (2013) Specifications of a continual reassessment method design for phase I trials of combined drugs. Pharm Stat 12:217-24
Wages, Nolan A; Conaway, Mark R; O'Quigley, John (2013) Using the time-to-event continual reassessment method in the presence of partial orders. Stat Med 32:131-41
Wages, Nolan A; Varhegyi, Nikole (2013) pocrm: an R-package for phase I trials of combinations of agents. Comput Methods Programs Biomed 112:211-8
Wages, Nolan A; Conaway, Mark R; O'Quigley, John (2011) Dose-finding design for multi-drug combinations. Clin Trials 8:380-9
Iasonos, Alexia; Zohar, Sarah; O'Quigley, John (2011) Incorporating lower grade toxicity information into dose finding designs. Clin Trials 8:370-9

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