981 resultados para drug dose escalation
Resumo:
This paper reviews Bayesian procedures for phase 1 dose-escalation studies and compares different dose schedules and cohort sizes. The methodology described is motivated by the situation of phase 1 dose-escalation studiesin oncology, that is, a single dose administered to each patient, with a single binary response ("toxicity"' or "no toxicity") observed. It is likely that a wider range of applications of the methodology is possible. In this paper, results from 10000-fold simulation runs conducted using the software package Bayesian ADEPT are presented. Four designs were compared under six scenarios. The simulation results indicate that there are slight advantages of having more dose levels and smaller cohort sizes.
Resumo:
Bayesian decision procedures have already been proposed for and implemented in Phase I dose-escalation studies in healthy volunteers. The procedures have been based on pharmacokinetic responses reflecting the concentration of the drug in blood plasma and are conducted to learn about the dose-response relationship while avoiding excessive concentrations. However, in many dose-escalation studies, pharmacodynamic endpoints such as heart rate or blood pressure are observed, and it is these that should be used to control dose-escalation. These endpoints introduce additional complexity into the modeling of the problem relative to pharmacokinetic responses. Firstly, there are responses available following placebo administrations. Secondly, the pharmacodynamic responses are related directly to measurable plasma concentrations, which in turn are related to dose. Motivated by experience of data from a real study conducted in a conventional manner, this paper presents and evaluates a Bayesian procedure devised for the simultaneous monitoring of pharmacodynamic and pharmacokinetic responses. Account is also taken of the incidence of adverse events. Following logarithmic transformations, a linear model is used to relate dose to the pharmacokinetic endpoint and a quadratic model to relate the latter to the pharmacodynamic endpoint. A logistic model is used to relate the pharmacokinetic endpoint to the risk of an adverse event.
Resumo:
BACKGROUND: EMD 521873 (Selectikine), an immunocytokine comprising a DNA-targeting antibody, aimed at tumour necrosis, fused with a genetically modified interleukin-2 (IL-2) moiety, was investigated in this first-in-human phase I study. METHODS: Patients had metastatic or locally advanced solid tumours failing previous standard therapy. Selectikine was administered as a 1-hour intravenous infusion on 3 consecutive days, every 3weeks. A subgroup of patients also received 300mg/m(2) cyclophosphamide on day 1 of each cycle. Escalating doses of Selectikine were investigated with the primary objective of determining the maximum tolerated dose (MTD). RESULTS: Thirty-nine patients were treated with Selectikine alone at dose levels from 0.075 to 0.9mg/kg, and nine were treated at doses of 0.45 and 0.6mg/kg in combination with cyclophosphamide. A dose-dependent linear increase of peak serum concentrations and area under curve was found. The dose-limiting toxicity was grade 3 skin rash at the 0.9mg/kg dose-level; the MTD was 0.6mg/kg. Rash and flu-like symptoms were the most frequent side-effects. No severe cardiovascular side-effects (hypotension or vascular leak) were observed. At all dose-levels, transient increases in total lymphocyte, eosinophil and monocyte counts were recorded. No objective tumour responses, but long periods of disease stabilisation were observed. Transient and non-neutralising Selectikine antibodies were detected in 69% of patients. CONCLUSIONS: The MTD of Selectikine with or without cyclophosphamide administered under this schedule was 0.6mg/kg. The recommended phase II dose was 0.45-0.6mg/kg. Selectikine had a favourable safety profile and induced biological effects typical for IL-2.
Resumo:
There has recently been increasing demand for better designs to conduct first-into-man dose-escalation studies more efficiently, more accurately and more quickly. The authors look into the Bayesian decision-theoretic approach and use simulation as a tool to investigate the impact of compromises with conventional practice that might make the procedures more acceptable for implementation. Copyright © 2005 John Wiley & Sons, Ltd.
Resumo:
In this paper, Bayesian decision procedures are developed for dose-escalation studies based on bivariate observations of undesirable events and signs of therapeutic benefit. The methods generalize earlier approaches taking into account only the undesirable outcomes. Logistic regression models are used to model the two responses, which are both assumed to take a binary form. A prior distribution for the unknown model parameters is suggested and an optional safety constraint can be included. Gain functions to be maximized are formulated in terms of accurate estimation of the limits of a therapeutic window or optimal treatment of the next cohort of subjects, although the approach could be applied to achieve any of a wide variety of objectives. The designs introduced are illustrated through simulation and retrospective implementation to a completed dose-escalation study. Copyright © 2006 John Wiley & Sons, Ltd.
Resumo:
Recently, various approaches have been suggested for dose escalation studies based on observations of both undesirable events and evidence of therapeutic benefit. This article concerns a Bayesian approach to dose escalation that requires the user to make numerous design decisions relating to the number of doses to make available, the choice of the prior distribution, the imposition of safety constraints and stopping rules, and the criteria by which the design is to be optimized. Results are presented of a substantial simulation study conducted to investigate the influence of some of these factors on the safety and the accuracy of the procedure with a view toward providing general guidance for investigators conducting such studies. The Bayesian procedures evaluated use logistic regression to model the two responses, which are both assumed to be binary. The simulation study is based on features of a recently completed study of a compound with potential benefit to patients suffering from inflammatory diseases of the lung.
Resumo:
In this paper, Bayesian decision procedures previously proposed for dose-escalation studies in healthy volunteers are reviewed and evaluated. Modifications are made to the expression of the prior distribution in order to make the procedure simpler to implement and a more relevant criterion for optimality is introduced. The results of an extensive simulation exercise to establish the proper-ties of the procedure and to aid choice between designs are summarized, and the way in which readers can use simulation to choose a design for their own trials is described. The influence of the value of the within-subject correlation on the procedure is investigated and the use of a simple prior to reflect uncertainty about the correlation is explored. Copyright (c) 2005 John Wiley & Sons, Ltd.
Resumo:
Bayesian decision procedures have recently been developed for dose escalation in phase I clinical trials concerning pharmacokinetic responses observed in healthy volunteers. This article describes how that general methodology was extended and evaluated for implementation in a specific phase I trial of a novel compound. At the time of writing, the study is ongoing, and it will be some time before the sponsor will wish to put the results into the public domain. This article is an account of how the study was designed in a way that should prove to be safe, accurate, and efficient whatever the true nature of the compound. The study involves the observation of two pharmacokinetic endpoints relating to the plasma concentration of the compound itself and of a metabolite as well as a safety endpoint relating to the occurrence of adverse events. Construction of the design and its evaluation via simulation are presented.
Resumo:
In this paper, Bayesian decision procedures are developed for dose-escalation studies based on binary measures of undesirable events and continuous measures of therapeutic benefit. The methods generalize earlier approaches where undesirable events and therapeutic benefit are both binary. A logistic regression model is used to model the binary responses, while a linear regression model is used to model the continuous responses. Prior distributions for the unknown model parameters are suggested. A gain function is discussed and an optional safety constraint is included. Copyright (C) 2006 John Wiley & Sons, Ltd.
Resumo:
We describe 17 children with nocturnal or early-morning seizures who were switched to a proportionally higher evening dose of antiepileptic drugs and were retrospectively reviewed for seizure outcome and side effects. Of 10 children with unknown etiology, clinical presentation was consistent with nocturnal frontal lobe epilepsy (NFLE) in 5 and benign epilepsy with centrotemporal spikes (BECTS) in 3. After a mean follow-up of 5.3 months, 15 patients were classified as responders: 11 of these became seizure free (5 NFLE, 1 BECTS, 5 with structural lesions) and 4 (2 BECTS, 2 with structural lesions) experienced 75-90% reductions in seizures. Among two nonresponders, seizures in one had failed to resolve with epilepsy surgery. Nine subjects (53%) received monotherapy after dose modification, and none presented with worsening of seizures. Two complained of transient side effects (fatigue/somnolence). Differential dosing led to seizure freedom in 64.7% (11/17) of patients, and 88.2% (15/17) experienced >= 50% reductions in seizures. (C) 2010 Elsevier Inc. All rights reserved.