Nanotecnologia aplicada ao tratamento da acne

A nanotecnologia é uma ciência multidisciplinar que consiste na optimização das propriedades da matéria permitindo o desenvolvimento de sistemas com um tamanho na escala dos nanómetros. A aplicação da nanotecnologia na medicina e cosmética surge como um campo de pesquisa que está a gerar um crescente interesse. A nanotecnologia aplicada ao tratamento de doenças comuns da pele tem sofrido alguns avanços, principalmente na área do tratamento tópico da acne, que tem beneficiado com o progresso desta tecnologia. A acne surge face a múltiplos factores patogénicos, afectando entre 75% a 95% dos adolescentes provocando-lhes transtornos físicos e psíquicos. No entanto, apesar de ser uma patologia característica da adolescência, a acne é prevalente também numa pequena população de mulheres com idade superior a 40 anos. Nesta dissertação foi feita uma abordagem da patogénese da acne, que foi útil na compressão dos objectivos do tratamento tópico, sistémico e físico instituído ao doente. Foram ainda explorados os conceitos básicos de nanotecnologia, que se enquadraram numa compreensão de como esta pode contribuir para a medicina e cosmética aplicada ao tratamento da acne. Foram também investigadas as diferentes publicações na área e avaliada a sua aplicação ao tratamento tópico da acne.

Synteza analogów nukleozydów i pronukleotydów z zastosowaniem reakcji Huisgena katalizowanej jonami miedzi(I) oraz badania ich aktywności biologicznej

Wydział Chemii: Pracownia Chemii Nukleozydów i Nukleotydów

Is 15 per cent very common? Informing people about the risks of medication side effects

Objectives - To assess the general public's interpretation of the verbal descriptors for side effect frequency recommended for use in medicine information leaflets by a European Union (EU) guideline, and to examine the extent to which differences in interpretation affect people's perception of risk and their judgments of intention to comply with the prescribed treatment. Method - Two studies used a controlled empirical methodology in which people were presented with a hypothetical, but realistic, scenario about visiting their general practitioner and being prescribed medication. They were given an explanation that focused on the side effects of the medicine, together with information about the probability of occurrence using either numerical percentages or the corresponding EU verbal descriptors. Interpretation of the descriptors was assessed. In study 2, participants were also required to make various judgments, including risk to health and intention to comply. Key findings - In both studies, use of the EU recommended descriptors led to significant overestimations of the likelihood of particular side effects occurring. Study 2 further showed that the "overestimation" resulted in significantly increased ratings of perceived severity of side effects and risk to health, as well as significantly reduced ratings of intention to comply, compared with those for people who received the probability information in numerical form. Conclusion - While it is recognised that the current findings require replication in a clinical setting, the European and national authorities should suspend the use of the EU recommended terms until further research is available to allow the use of an evidence-based approach.

Generating recipient-centred explanations about drug prescription

In this paper we describe how we generated written explanations to ‘indirect users’ of a knowledge-based system in the domain of drug prescription. We call ‘indirect users’ the intended recipients of explanations, to distinguish them from the prescriber (the ‘direct’ user) who interacts with the system. The Explanation Generator was designed after several studies about indirect users' information needs and physicians' explanatory attitudes in this domain. It integrates text planning techniques with ATN-based surface generation. A double modeling component enables adapting the information content, order and style to the indirect user to whom explanation is addressed. Several examples of computer-generated texts are provided, and they are contrasted with the physicians' explanations to discuss advantages and limits of the approach adopted.

Bayesian decision procedures for dose-escalation based on evidence of undesirable events and therapeutic benefit.

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.

Stopping clinical trials because of treatment ineffectiveness: a comparison of a futility design with a method of stochastic curtailment

This paper introduces a simple futility design that allows a comparative clinical trial to be stopped due to lack of effect at any of a series of planned interim analyses. Stopping due to apparent benefit is not permitted. The design is for use when any positive claim should be based on the maximum sample size, for example to allow subgroup analyses or the evaluation of safety or secondary efficacy responses. A final frequentist analysis can be performed that is valid for the type of design employed. Here the design is described and its properties are presented. Its advantages and disadvantages relative to the use of stochastic curtailment are discussed. Copyright (C) 2003 John Wiley Sons, Ltd.

Sequential designs for phase III clinical trials incorporating treatment selection

Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power. Copyright © 2003 John Wiley & Sons, Ltd.

The sequential analysis of repeated binary responses: a score test for the case of three time points

In this paper a robust method is developed for the analysis of data consisting of repeated binary observations taken at up to three fixed time points on each subject. The primary objective is to compare outcomes at the last time point, using earlier observations to predict this for subjects with incomplete records. A score test is derived. The method is developed for application to sequential clinical trials, as at interim analyses there will be many incomplete records occurring in non-informative patterns. Motivation for the methodology comes from experience with clinical trials in stroke and head injury, and data from one such trial is used to illustrate the approach. Extensions to more than three time points and to allow for stratification are discussed. Copyright © 2005 John Wiley & Sons, Ltd.

Statistical design and analysis of pharmacogenetic trials

Pharmacogenetic trials investigate the effect of genotype on treatment response. When there are two or more treatment groups and two or more genetic groups, investigation of gene-treatment interactions is of key interest. However, calculation of the power to detect such interactions is complicated because this depends not only on the treatment effect size within each genetic group, but also on the number of genetic groups, the size of each genetic group, and the type of genetic effect that is both present and tested for. The scale chosen to measure the magnitude of an interaction can also be problematic, especially for the binary case. Elston et al. proposed a test for detecting the presence of gene-treatment interactions for binary responses, and gave appropriate power calculations. This paper shows how the same approach can also be used for normally distributed responses. We also propose a method for analysing and performing sample size calculations based on a generalized linear model (GLM) approach. The power of the Elston et al. and GLM approaches are compared for the binary and normal case using several illustrative examples. While more sensitive to errors in model specification than the Elston et al. approach, the GLM approach is much more flexible and in many cases more powerful. Copyright © 2005 John Wiley & Sons, Ltd.

An illustration of the modelling of cost and efficacy data from a clinical trial

Health care providers, purchasers and policy makers need to make informed decisions regarding the provision of cost-effective care. When a new health care intervention is to be compared with the current standard, an economic evaluation alongside an evaluation of health benefits provides useful information for the decision making process. We consider the information on cost-effectiveness which arises from an individual clinical trial comparing the two interventions. Recent methods for conducting a cost-effectiveness analysis for a clinical trial have focused on the net benefit parameter. The net benefit parameter, a function of costs and health benefits, is positive if the new intervention is cost-effective compared with the standard. In this paper we describe frequentist and Bayesian approaches to cost-effectiveness analysis which have been suggested in the literature and apply them to data from a clinical trial comparing laparoscopic surgery with open mesh surgery for the repair of inguinal hernias. We extend the Bayesian model to allow the total cost to be divided into a number of different components. The advantages and disadvantages of the different approaches are discussed. In January 2001, NICE issued guidance on the type of surgery to be used for inguinal hernia repair. We discuss our example in the light of this information. Copyright © 2003 John Wiley & Sons, Ltd.

A score test for binary data with patient non-compliance

A score test is developed for binary clinical trial data, which incorporates patient non-compliance while respecting randomization. It is assumed in this paper that compliance is all-or-nothing, in the sense that a patient either accepts all of the treatment assigned as specified in the protocol, or none of it. Direct analytic comparisons of the adjusted test statistic for both the score test and the likelihood ratio test are made with the corresponding test statistics that adhere to the intention-to-treat principle. It is shown that no gain in power is possible over the intention-to-treat analysis, by adjusting for patient non-compliance. Sample size formulae are derived and simulation studies are used to demonstrate that the sample size approximation holds. Copyright © 2003 John Wiley & Sons, Ltd.