998 resultados para research exemption
Resumo:
BACKGROUND: The aim of this study was to evaluate the efficacy and tolerability of fulvestrant, an estrogen receptor antagonist, in postmenopausal women with hormone-responsive tumors progressing after aromatase inhibitor (AI) treatment. PATIENTS AND METHODS: This is a phase II, open, multicenter, noncomparative study. Two patient groups were prospectively considered: group A (n=70) with AI-responsive disease and group B (n=20) with AI-resistant disease. Fulvestrant 250 mg was administered as intramuscular injection every 28 (+/-3) days. RESULTS: All patients were pretreated with AI and 84% also with tamoxifen or toremifene; 67% had bone metastases and 45% liver metastases. Fulvestrant administration was well tolerated and yielded a clinical benefit (CB; defined as objective response or stable disease [SD] for >or=24 weeks) in 28% (90% confidence interval [CI] 19% to 39%) of patients in group A and 37% (90% CI 19% to 58%) of patients in group B. Median time to progression (TTP) was 3.6 (95% CI 3.0 to 4.8) months in group A and 3.4 (95% CI 2.5 to 6.7) months in group B. CONCLUSIONS: Overall, 30% of patients who had progressed following prior AI treatment gained CB with fulvestrant, thereby delaying indication to start chemotherapy. Prior response to an AI did not appear to be predictive for benefit with fulvestrant.
Resumo:
Q-sort is a research method which allows defining profiles of attitudes toward a set of statements, ordered in relation to each other. Pertaining to the Q Methodology, the qualitative analysis of the Q-sorts is based on quantitative techniques. This method is of particular interest for research in health professions, a field in which attitudes of patients and professionals are very important. The method is presented in this article, along with an example of application in nursing in old age psychiatry.
Resumo:
Expectations about the future are central for determination of current macroeconomic outcomes and the formulation of monetary policy. Recent literature has explored ways for supplementing the benchmark of rational expectations with explicit models of expectations formation that rely on econometric learning. Some apparently natural policy rules turn out to imply expectational instability of private agents’ learning. We use the standard New Keynesian model to illustrate this problem and survey the key results about interest-rate rules that deliver both uniqueness and stability of equilibrium under econometric learning. We then consider some practical concerns such as measurement errors in private expectations, observability of variables and learning of structural parameters required for policy. We also discuss some recent applications including policy design under perpetual learning, estimated models with learning, recurrent hyperinflations, and macroeconomic policy to combat liquidity traps and deflation.
Resumo:
This paper analyzes the early research performance of PhD graduates in labor economics, addressing the following questions: Are there major productivity differences between graduates from American and European institutions? If so, how relevant is the quality of the training received (i.e. ranking of institution and supervisor) and the research environment in the subsequent job placement institution? The population under study consists of labor economics PhD graduates who received their degree in the years 2000 to 2005 in Europe or the USA. Research productivity is evaluated alternatively as the number of publications or the quality-adjusted number of publications of an individual. When restricting the analysis to the number of publications, results suggest a higher productivity by graduates from European universities than from USA universities, but this difference vanishes when accounting for the quality of the publication. The results also indicate that graduates placed at American institutions, in particular top ones, are likely to publish more quality-adjusted articles than their European counterparts. This may be because, when hired, they already have several good acceptances or because of more focused research efforts and clearer career incentives.
Resumo:
The academic activities led by the Unit of Community Pharmacy can be classified as translational. Our group is interested in person-centered pharmaceutical services aimed at a more responsible use of drugs (effectiveness, safety, efficiency) in collaboration with physicians and other health care professionals in a primary care setting. The following domains of education and research are high priorities for our group: medication therapy management, medication adherence, integrated care, individualization of therapies, care management for the elderly and e-health.
Resumo:
A series of studies has been carried out in the field of traditional medicine for searching radio-protective agents. According to the theory of traditional Chinese medicine, may prescriptions were tested with experimental animals. Some of them could raise the survival rate of dogs irradiated with lethal dose of Pi-rays by 30-40%. Some symptoms of radiation sickness could be improved. More than one thousand kinds of Chinese herbs were screened. Some of them have pronounced radioprotectice activities. A series of bioactive components wee isolated from these herbs. The mechanism of radiation protection were studied. Having the capability of hemopoietic system and immune system may be the characteristics of these Chinese herbs.
Resumo:
The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.