Showing papers by "Sarah Zohar published in 2013"

Dose-finding designs using a novel quasi-continuous endpoint for multiple toxicities.

Abstract: The aim of a phase I oncology trial is to identify a dose with an acceptable safety profile. Most phase I designs use the dose-limiting toxicity, a binary endpoint, to assess the unacceptable level of toxicity. The dose-limiting toxicity might be incomplete for investigating molecularly targeted therapies as much useful toxicity information is discarded. In this work, we propose a quasi-continuous toxicity score, the total toxicity profile (TTP), to measure quantitatively and comprehensively the overall severity of multiple toxicities. We define the TTP as the Euclidean norm of the weights of toxicities experienced by a patient, where the weights reflect the relative clinical importance of each grade and toxicity type. We propose a dose-finding design, the quasi-likelihood continual reassessment method (CRM), incorporating the TTP score into the CRM, with a logistic model for the dose–toxicity relationship in a frequentist framework. Using simulations, we compared our design with three existing designs for quasi-continuous toxicity score (the Bayesian quasi-CRM with an empiric model and two nonparametric designs), all using the TTP score, under eight different scenarios. All designs using the TTP score to identify the recommended dose had good performance characteristics for most scenarios, with good overdosing control. For a sample size of 36, the percentage of correct selection for the quasi-likelihood CRM ranged from 80% to 90%, with similar results for the quasi-CRM design. These designs with TTP score present an appealing alternative to the conventional dose-finding designs, especially in the context of molecularly targeted agents.

Using the continual reassessment method to estimate the minimum effective dose in phase II dose-finding studies: a case study.

Abstract: BackgroundThe Continual Reassessment Method typically is presented as the method of choice for the purpose of dose-finding based on a toxicity scale in phase I clinical trials. However, this adaptive statistical approach also can be applied easily to dose-finding experiments in phase II trials.PurposeTo provide a case study from a real clinical trial to illustrate the use of the Continual Reassessment Method in the context of phase II dose finding.MethodsThe Continual Reassessment Method was used to model the dose-failure relationship in order to estimate the minimal effective dose. This approach was retrospectively used to determine the minimal effective dose of granulocyte colony-stimulating factor for peripheral blood stem cell collection in allografted patients following chemotherapy.ResultsAfter the inclusion of 25 patients, the minimal effective dose was estimated to be the third dose level tested in the study.LimitationsThe main limitation of the Continual Reassessment Method, which is not specific...

Application of the continual reassessment method to dose-finding studies in regional anesthesia: an estimate of the ED95 dose for 0.5% bupivacaine for ultrasound-guided supraclavicular block.

Abstract: Background:Previously reported estimates of the ED95 doses for local anesthetics used in brachial plexus blocks vary. The authors used the continual reassessment method, already established in oncology trials, to determine the ED95 dose for 0.5% bupivacaine for the ultrasound-guided supraclavicular

An adaptive model switching approach for phase I dose-finding trials.

Abstract: Model-based phase I dose-finding designs rely on a single model throughout the study for estimating the maximum tolerated dose (MTD). Thus, one major concern is about the choice of the most suitable model to be used. This is important because the dose allocation process and the MTD estimation depend on whether or not the model is reliable, or whether or not it gives a better fit to toxicity data. The aim of our work was to propose a method that would remove the need for a model choice prior to the trial onset and then allow it sequentially at each patient's inclusion. In this paper, we described model checking approach based on the posterior predictive check and model comparison approach based on the deviance information criterion, in order to identify a more reliable or better model during the course of a trial and to support clinical decision making. Further, we presented two model switching designs for a phase I cancer trial that were based on the aforementioned approaches, and performed a comparison between designs with or without model switching, through a simulation study. The results showed that the proposed designs had the advantage of decreasing certain risks, such as those of poor dose allocation and failure to find the MTD, which could occur if the model is misspecified. Copyright © 2013 John Wiley & Sons, Ltd.