899 resultados para sample size in mirco-clinical trials


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Metabotropic glutamate (mGlu) receptors are G protein-coupled receptors expressed primarily on neurons and glial cells modulating the effects of glutamatergic neurotransmission. The pharmacological manipulation of these receptors has been postulated to be valuable in the management of some neurological disorders. Accordingly, the targeting of mGlu5 receptors as a therapeutic approach for Parkinson's disease (PD) has been proposed, especially to manage the adverse symptoms associated to chronic treatment with classical PD drugs. Thus, the specific pharmacological blocking of mGlu5 receptors constitutes one of the most attractive non-dopaminergic-based strategies for PD management in general and for the L-DOPA-induced diskynesia (LID) in particular. Overall, we provide here an update of the current state of the art of these mGlu5 receptor-based approaches that are under clinical study as agents devoted to alleviate PD symptoms.

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The objectives of this study were to evaluate baby corn yield, green corn yield, and grain yield in corn cultivar BM 3061, with weed control achieved via a combination of hoeing and intercropping with gliricidia, and determine how sample size influences weed growth evaluation accuracy. A randomized block design with ten replicates was used. The cultivar was submitted to the following treatments: A = hoeings at 20 and 40 days after corn sowing (DACS), B = hoeing at 20 DACS + gliricidia sowing after hoeing, C = gliricidia sowing together with corn sowing + hoeing at 40 DACS, D = gliricidia sowing together with corn sowing, and E = no hoeing. Gliricidia was sown at a density of 30 viable seeds m-2. After harvesting the mature ears, the area of each plot was divided into eight sampling units measuring 1.2 m² each to evaluate weed growth (above-ground dry biomass). Treatment A provided the highest baby corn, green corn, and grain yields. Treatment B did not differ from treatment A with respect to the yield values for the three products, and was equivalent to treatment C for green corn yield, but was superior to C with regard to baby corn weight and grain yield. Treatments D and E provided similar yields and were inferior to the other treatments. Therefore, treatment B is a promising one. The relation between coefficient of experimental variation (CV) and sample size (S) to evaluate growth of the above-ground part of the weeds was given by the equation CV = 37.57 S-0.15, i.e., CV decreased as S increased. The optimal sample size indicated by this equation was 4.3 m².

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A 42-year-old male complaining of thoracic spine pain was admitted to the hospital for evaluation. An X-ray and computer tomography of the thoracic spine showed spondylodiscitis of the L3 lumbar and L2-L3 intervertebral disk. The tuberculin skin test (PPD) was strongly positive. A radioscopy-guided fine needle aspirate of the affected area was cultured but did not reveal the cause of the disease. Two biopsy attempts failed to reveal the cause of the disease by culturing or by acid-fast-resistant staining (Ziehl Neelsen) of the specimens. A third biopsy also failed to detect the infectious agent by using microbiological procedures, but revealed the presence of a 245-bp amplicon characteristic of the Mycobacterium tuberculosis complex after PCR of the sample. The result demonstrates the efficacy of PCR for the identification of M. tuberculosis in situations in which conventional diagnosis by culturing techniques or direct microscopy is unable to detect the microorganism. Following this result the patient was treated with the antituberculous cocktail composed by rifampicin, pirazinamide and isoniazid during a six-month period. At the end of the treatment the dorsalgia symptoms had disappeared.

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Recent evidence shows that moxifloxacin could exert an antimicrobial effect against Helicobacter pylori in both in vitroand in vivo models. To systematically evaluate whether moxifloxacin-containing triple therapy could improve eradication rates and reduce side effects in first-line or second-line anti-H. pyloritreatment, eligible articles were identified by searches of electronic databases. We included all randomized trials comparing moxifloxacin-based triple therapy with standard triple or quadruple therapy during H. pylori eradication treatment. Statistical analysis was performed with Review Manager 5.0.10. Subanalysis/sensitivity analysis was also performed. We identified seven randomized trials (n=1263). Pooled H. pylori eradication rates were 79.03% (95%CI: 75.73-82.07) and 68.33% (95%CI: 64.44-72.04) for patients with moxifloxacin-based triple therapy or with standard triple or quadruple therapy, respectively (intention-to-treat analysis). The odds ratio (OR) was 1.82 (95%CI: 1.17-2.81), the occurrence of total side effects was 15.23% (95%CI: 12.58-18.20) and 27.17% (95%CI: 23.64-30.92) for groups with or without moxifloxacin, and the summary OR was 0.45 (95%CI: 0.26-0.77). In subgroup analyses, we noted that the second-line eradication rate in the moxifloxacin group was significantly higher than that in the quadruple therapy group (73.33 vs 60.17%, OR: 1.78, 95%CI: 1.16-2.73, P<0.001). However, there was no difference in first-line eradication treatment. Findings from this meta-analysis suggest that moxifloxacin-based triple therapy is more effective and better tolerated than standard triple or quadruple therapy. Therefore, a moxifloxacin-based triple regimen should be used in the second-line treatment of H. pylori infection.

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Research Question: What are the psychosocial factors that affect causality assessment in early phase oncology clinical trials? Methods: Thirty-two qualitative interviews were explicated with the aid of “Naturalistic Decision Making”. Data explication consisted of phenomenological reduction, delineating and clustering meaning units, forming themes, and creating a composite summary. Participants were members of the National Cancer Institute of Canada’s Clinical Trial Group Investigative New Drug committee. Results: The process of assigning causality is extremely subjective and full of uncertainty. Physicians had no formal training, nor a tool to assist them with this process. Physicians were apprehensive about their decisions and felt pressure from their patients, as well as the pharmaceutical companies sponsoring the trial. Conclusions: There are many problem areas when attributing causality, all of which have serious consequences, but clinicians used a variety of methods to cope with these problem areas.

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Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data. Many of the issues that are discussed with reference to the statistical analysis of compositional data have a natural counterpart in the construction of a Bayesian statistical model for categorical data. This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986) in his seminal book on compositional data. Particular emphasis is put on the problem of what parameterization to use

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In the last few years, many researchers have studied the presence of common dimensions of temperament in subjects with symptoms of anxiety. The aim of this study is to examine the association between temperamental dimensions (high negative affect and activity level) and anxiety problems in clinical preschool children. A total of 38 children, ages 3 to 6 years, from the Infant and Adolescent Mental Health Center of Girona and the Center of Diagnosis and Early Attention of Sabadell and Olot were evaluated by parents and psychologists. Their parents completed several screening scales and, subsequently, clinical child psychopathology professionals carried out diagnostic interviews with children from the sample who presented signs of anxiety. Findings showed that children with high levels of negative affect and low activity level have pronounced symptoms of anxiety. However, children with anxiety disorders do not present different temperament styles from their peers without these pathologies

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The aim of phase II single-arm clinical trials of a new drug is to determine whether it has sufficient promising activity to warrant its further development. For the last several years Bayesian statistical methods have been proposed and used. Bayesian approaches are ideal for earlier phase trials as they take into account information that accrues during a trial. Predictive probabilities are then updated and so become more accurate as the trial progresses. Suitable priors can act as pseudo samples, which make small sample clinical trials more informative. Thus patients have better chances to receive better treatments. The goal of this paper is to provide a tutorial for statisticians who use Bayesian methods for the first time or investigators who have some statistical background. In addition, real data from three clinical trials are presented as examples to illustrate how to conduct a Bayesian approach for phase II single-arm clinical trials with binary outcomes.

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We focus on the comparison of three statistical models used to estimate the treatment effect in metaanalysis when individually pooled data are available. The models are two conventional models, namely a multi-level and a model based upon an approximate likelihood, and a newly developed model, the profile likelihood model which might be viewed as an extension of the Mantel-Haenszel approach. To exemplify these methods, we use results from a meta-analysis of 22 trials to prevent respiratory tract infections. We show that by using the multi-level approach, in the case of baseline heterogeneity, the number of clusters or components is considerably over-estimated. The approximate and profile likelihood method showed nearly the same pattern for the treatment effect distribution. To provide more evidence two simulation studies are accomplished. The profile likelihood can be considered as a clear alternative to the approximate likelihood model. In the case of strong baseline heterogeneity, the profile likelihood method shows superior behaviour when compared with the multi-level model. Copyright (C) 2006 John Wiley & Sons, Ltd.

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In this paper we set out what we consider to be a set of best practices for statisticians in the reporting of pharmaceutical industry-sponsored clinical trials. We make eight recommendations covering: author responsibilities and recognition; publication timing; conflicts of interest; freedom to act; full author access to data; trial registration and independent review. These recommendations are made in the context of the prominent role played by statisticians in the design, conduct, analysis and reporting of pharmaceutical sponsored trials and the perception of the reporting of these trials in the wider community.