Dataset Information

Evaluation of utility of pharmacokinetic studies in phase I trials of two oncology drugs.

ABSTRACT: There are many phase I trials of oncology drug combinations, very few of which report clinically significant pharmacokinetic interactions. We hypothesized that the utility of such pharmacokinetic drug-drug interaction (DDI) studies is low in the absence of a mechanistic hypothesis.We retrospectively reviewed 152 phase I (two drug) combination studies published between 2007 and 2011.Only 28 (18%) studies had an implicit or explicit rationale, either inhibition/induction of a drug-metabolizing enzyme or transporter, cosubstrates for the same enzyme or transporter, potential for end-organ toxicity, or protein binding. Only 12 (8%) studies demonstrated a statistically significant DDI, on the basis of change in clearance (or area under the curve) of parent drug and/or active metabolite. There was a strong association between a rationale and a demonstrable drug interaction, as only 2% of studies without a rationale demonstrated a DDI, compared with 32% of studies with a rationale (Fisher exact test; P < 10(-6)).DDI studies should not be routinely performed as part of phase I trials of oncology combinations.

SUBMITTER: Wu K

PROVIDER: S-EPMC3832109 | biostudies-other | 2013 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Evaluation of utility of pharmacokinetic studies in phase I trials of two oncology drugs.

Wu Kehua K House Larry L Ramírez Jacqueline J Seminerio Michael J MJ Ratain Mark J MJ

Clinical cancer research : an official journal of the American Association for Cancer Research 20130920 21

<h4>Purpose</h4>There are many phase I trials of oncology drug combinations, very few of which report clinically significant pharmacokinetic interactions. We hypothesized that the utility of such pharmacokinetic drug-drug interaction (DDI) studies is low in the absence of a mechanistic hypothesis.<h4>Experimental design</h4>We retrospectively reviewed 152 phase I (two drug) combination studies published between 2007 and 2011.<h4>Results</h4>Only 28 (18%) studies had an implicit or explicit ratio ...[more]

PMID: 24056785

Similar Datasets

Project description:BackgroundGiven the inherent challenges of conducting randomized phase III trials in older cancer patients, single-arm phase II trials which assess the feasibility of a treatment that has already been shown to be effective in a younger population may provide a compelling alternative. Such an approach would need to evaluate treatment feasibility based on a composite endpoint that combines multiple clinical dimensions and to stratify older patients as fit or frail to account for the heterogeneity of the study population to recommend an appropriate treatment approach. In this context, stratified adaptive two-stage designs for binary or composite endpoints, initially developed for biomarker studies, allow to include two subgroups whilst maintaining competitive statistical performances. In practice, heterogeneity may indeed affect more than one dimension and incorporating co-primary endpoints, which independently assess each individual clinical dimension, would therefore appear quite pertinent. The current paper presents a novel phase II design for co-primary endpoints which takes into account the heterogeneity of a population. METHODS: We developed a stratified adaptive Bryant & Day design based on the Jones et al. and Parashar et al. algorithm. This two-stage design allows to jointly assess two dimensions (e.g. activity and toxicity) in two different subgroups. The operating characteristics of this new design were evaluated using examples and simulation comparisons with the Bryant & Day design in the context where the study population is stratified according to a pre-defined criterion.ResultsSimulation results demonstrated that the new design minimized the expected and maximum sample sizes as compared to parallel Bryant & Day designs (one in each subgroup), whilst controlling type I error rates and maintaining a competitive statistical power as well as a high probability of detecting heterogeneity.ConclusionsIn a heterogeneous population, this two-stage stratified adaptive phase II design provides a useful alternative to classical one and allows to identify a subgroup of interest without dramatically increasing sample size. As heterogeneity is not limited to older populations, this new design may also be relevant to other study populations such as children or adolescents and young adults or the development of targeted therapies based on a biomarker.

Dataset Information

Evaluation of utility of pharmacokinetic studies in phase I trials of two oncology drugs.

Publications

Evaluation of utility of pharmacokinetic studies in phase I trials of two oncology drugs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets