795 resultados para Trials (Breach of promise)


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Thiocyanate content and lactoperoxidase activity of individual cow's milk of different breeds were determined, and the effects of different lactoperoxidase system (LP-s) activation strategies were compared. Lactoperoxidase activity varied significantly between Friesian and both Ayrshire and Tanzania Short Horn Zebu (TSHZ), but differences between Ayrshire and TSHZ were not significant. There was no significant variation in SCN- content between breeds. The LP-s was activated using three strategies based on SCN-: namely; equal concentrations of SCN- and H2O2 (7:7, 10:10, 15 :15 mg/l), excess SCN- concentrations (15:10, 20:10, 25:10 mg SCN-: H2O2/I), and excess H2O2 concentrations (10:15, 10:20, 10:25 mg SCN-: H2O2/I), plus a fourth strategy based on I- (15 : 15 mg I- : H2O2/I). The keeping quality (KQ) was assessed using pH, titratable acidity, clot on boiling and alcohol stability tests. All activation strategies enhanced the shelf life of milk (typically increasing KQ from around 10 to around 20 h), but it was clear that the effectiveness of the LP-s depends on the type and concentrations of the activators of the system. The LP-s activated using I- as an electron donor was more effective than the LP-s activated using SCN- as an electron donor, increasing the KQ by a further 6-8 h compared with SCN-.

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Objective To assess the efficacy of an intervention designed to improve the mother-infant relationship and security of infant attachment in a South African peri-urban settlement with marked adverse socioeconomic circumstances. Design Randomised controlled trial. Setting Khayelitsha, a peri-urban settlement in South Africa. Participants 449 pregnant women. Interventions The intervention was delivered from late pregnancy and for six months postpartum. Women were visited in their homes by previously untrained lay community workers who provided support and guidance in parenting. The purpose of the intervention was to promote sensitive and responsive parenting and secure infant attachment to the mother. Women in the control group received no therapeutic input from the research team. Main outcome measures Primary outcomes: quality of mother-infant interactions at six and 12 months postpartum; infant attachment security at 18 months. Secondary outcome: maternal depression at six and 12 months. Results The intervention was associated with significant benefit to the mother-infant relationship. At both six and 12 months, compared with control mothers, mothers in the intervention group were significantly more sensitive (6 months: mean difference=0.77 (SD 0.37), t=2.10, P<0.05, d=0.24; 12 months: mean difference=0.42 (0.18), t=-2.04, P<0.05, d=0.26) and less intrusive (6 months: mean difference=0.68 (0.36), t=2.28, P<0.05, d=0.26; 12 months: mean difference=-1.76 (0.86), t=2.28, P<0.05, d=0.24) in their interactions with their infants. The intervention was also associated with a higher rate of secure infant attachments at 18 months (116/156 (74%) v 102/162 (63%); Wald=4.74, odds ratio=1.70, P<0.05). Although the prevalence of maternal depressive disorder was not significantly reduced, the intervention had a benefit in terms of maternal depressed mood at six months (z=2.05, P=0.04) on the Edinburgh postnatal depression scale). Conclusions The intervention, delivered by local lay women, had a significant positive impact on the quality of the mother-infant relationship and on security of infant attachment, factors known to predict favourable child development. If these effects persist, and if they are replicated, this intervention holds considerable promise for use in the developing world. Trial registration Current Controlled Trials ISRCTN25664149.

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Background: Preventing childhood overweight and obesity has become a major public health issue in developed and developing countries. Systematic reviews of this topic have not provided practice-relevant guidance because of the generally low quality of research and the heterogeneity of reported effectiveness. Aim: To present practice-relevant guidance on interventions to reduce at least one measure of adiposity in child populations that do or do not contain overweight or obese children. Design: Systematic review of eligible randomized, controlled trials or controlled trials using a novel approach to synthesizing the trial results through application of descriptive epidemiological and realistic evaluation concepts. Eligible trials involved at least 30 participants, lasted at least 12 weeks and involved non-clinical child populations. Results: Twenty-eight eligible trials were identified to 30 April 2006. Eleven trials were effective and 17 were ineffective in reducing adiposity. Blind to outcome, the main factor distinguishing effective from ineffective trials was the provision of moderate to vigorous aerobic physical activity in the former on a relatively 'compulsory' rather than 'voluntary' basis. Conclusions: By using a novel approach to synthesizing trials, a decisive role for the 'compulsory' provision of aerobic physical activity has been demonstrated. Further research is required to identify how such activity can be sustained and transformed into a personally chosen behaviour by children and over the life course. (C) 2007 The Royal Institute of Public Health. Published by Elsevier Ltd. All rights reserved.

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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.

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Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.

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This paper presents practical approaches to the problem of sample size re-estimation in the case of clinical trials with survival data when proportional hazards can be assumed. When data are readily available at the time of the review, on a full range of survival experiences across the recruited patients, it is shown that, as expected, performing a blinded re-estimation procedure is straightforward and can help to maintain the trial's pre-specified error rates. Two alternative methods for dealing with the situation where limited survival experiences are available at the time of the sample size review are then presented and compared. In this instance, extrapolation is required in order to undertake the sample size re-estimation. Worked examples, together with results from a simulation study are described. It is concluded that, as in the standard case, use of either extrapolation approach successfully protects the trial error rates. Copyright © 2012 John Wiley & Sons, Ltd.

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Recently, in order to accelerate drug development, trials that use adaptive seamless designs such as phase II/III clinical trials have been proposed. Phase II/III clinical trials combine traditional phases II and III into a single trial that is conducted in two stages. Using stage 1 data, an interim analysis is performed to answer phase II objectives and after collection of stage 2 data, a final confirmatory analysis is performed to answer phase III objectives. In this paper we consider phase II/III clinical trials in which, at stage 1, several experimental treatments are compared to a control and the apparently most effective experimental treatment is selected to continue to stage 2. Although these trials are attractive because the confirmatory analysis includes phase II data from stage 1, the inference methods used for trials that compare a single experimental treatment to a control and do not have an interim analysis are no longer appropriate. Several methods for analysing phase II/III clinical trials have been developed. These methods are recent and so there is little literature on extensive comparisons of their characteristics. In this paper we review and compare the various methods available for constructing confidence intervals after phase II/III clinical trials.

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Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

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In an adaptive seamless phase II/III clinical trial interim analysis, data are used for treatment selection, enabling resources to be focused on comparison of more effective treatment(s) with a control. In this paper, we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focuses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short- and long-term endpoints.

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There is an urgent need to treat individuals with high blood pressure (BP) with effective dietary strategies. Previous studies suggest a small, but significant decrease in BP after lactotripeptides (LTP) ingestion, although the data are inconsistent. The study aim was to perform a comprehensive meta-analysis of data from all relevant randomised controlled trials (RCT). Medline, Cochrane library, EMBASE and Web of Science were searched until May 2014. Eligibility criteria were RCT that examined the effects of LTP on BP in adults, with systolic BP (SBP) and diastolic BP (DBP) as outcome measures. Thirty RCT met the inclusion criteria, which resulted in 33 sets of data. The pooled treatment effect for SBP was −2.95 mmHg (95% CI: −4.17, −1.73; p < 0.001), and for DBP was −1.51 mmHg (95% CI: −2.21, −0.80; p < 0.001). Sub-group analyses revealed that reduction of BP in Japanese studies was significantly greater, compared with European studies (p = 0.002 for SBP and p < 0.001 for DBP). The 24-h ambulatory BP (AMBP) response to LTP supplementation was statistically non-significant (p = 0.101 for SBP and p = 0.166 for DBP). Both publication bias and “small-study effect” were identified, which shifted the treatment effect towards less significant SBP and non-significant DBP reduction after LTP consumption. LTP may be effective in BP reduction, especially in Japanese individuals; however sub-group, meta-regression analyses and statistically significant publication biases suggest inconsistencies.