60 research outputs found

    Choosing sensitivity analyses for randomised trials: principles

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    Background Sensitivity analyses are an important tool for understanding the extent to which the results of randomised trials depend upon the assumptions of the analysis. There is currently no guidance governing the choice of sensitivity analyses. Discussion We provide a principled approach to choosing sensitivity analyses through the consideration of the following questions: 1) Does the proposed sensitivity analysis address the same question as the primary analysis? 2) Is it possible for the proposed sensitivity analysis to return a different result to the primary analysis? 3) If the results do differ, is there any uncertainty as to which will be believed? Answering all of these questions in the affirmative will help researchers to identify relevant sensitivity analyses. Treating analyses as sensitivity analyses when one or more of the answers are negative can be misleading and confuse the interpretation of studies. The value of these questions is illustrated with several examples. Summary By removing unreasonable analyses that might have been performed, these questions will lead to relevant sensitivity analyses, which help to assess the robustness of trial results

    Intestinal Damage Determines the Inflammatory Response and Early Complications in Patients Receiving Conditioning for a Stem Cell Transplantation

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    Contains fulltext : 87954.pdf (publisher's version ) (Open Access)BACKGROUND: Stem cell transplantation (SCT) is still complicated by the occurrence of fever and inflammatory complications attributed to neutropenia and subsequent infectious complications. The role of mucosal barrier injury (MBI) of the intestinal tract therein has received little attention. METHODS: We performed a retrospective analysis in 163 SCT recipients of which data had been collected prospectively on intestinal damage (citrulline), inflammation (C-reactive protein), and neutrophil count. Six different conditioning regimens were studied; 5 myeloablative (MA) and 1 non-myeloablative (NMA). Linear mixed model multivariate and AUC analyses were used to define the role of intestinal damage in post-SCT inflammation. We also studied the relationship between the degree of intestinal damage and the occurrence of early post-SCT complications. RESULTS: In the 5 MA regimen there was a striking pattern of inflammatory response that coincided with the occurrence of severe intestinal damage. This contrasted with a modest inflammatory response seen in the NMA regimen in which intestinal damage was limited. With linear mixed model analysis the degree of intestinal damage was shown the most important determinant of the inflammatory response, and both neutropenia and bacteremia had only a minor impact. AUC analysis revealed a strong correlation between citrulline and CRP (Pearson correlation r = 0.96). Intestinal damage was associated with the occurrence of bacteremia and acute lung injury, and influenced the kinetics of acute graft-versus-host disease. CONCLUSION: The degree of intestinal damage after myeloablative conditioning appeared to be the most important determined the inflammatory response following SCT, and was associated with inflammatory complications. Studies should explore ways to ameliorate cytotoxic therapy-induced intestinal damage in order to reduce complications associated with myeloablative conditioning therapy

    Economic evaluation of posaconazole versus fluconazole prophylaxis in patients with graft-versus-host disease (GVHD) in the Netherlands

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    The objective of this study was to evaluate the cost-effectiveness of posaconazole versus fluconazole for the prevention of invasive fungal infections (IFI) in graft-versus-host disease (GVHD) patients in the Netherlands. A decision analytic model was developed based on a double-blind randomized trial that compared posaconazole with fluconazole antifungal prophylaxis in recipients of allogeneic HSCT with GVHD who were receiving immunosuppressive therapy (Ullmann et al., N Engl J Med 356:335–347, 2007). Clinical events were modeled with chance nodes reflecting probabilities of IFIs, IFI-related death, and death from other causes. Data on life expectancy, quality-of-life, medical resource consumption, and costs were obtained from the literature. The total cost with posaconazole amounted to €9,428 (95% uncertainty interval €7,743–11,388), which is €4,566 (€2,460–6,854) more than those with fluconazole. Posaconazole prophylaxis resulted in 0.17 (0.02–0.36) quality adjusted life year (QALY) gained compared to fluconazole prophylaxis, corresponding to an incremental cost effectiveness ratio (ICER) of €26,225 per QALY gained. A scenario analysis demonstrated that at an increased background IFI risk (from 9% to 15%) the ICER was €13,462 per QALY. Given the underlying data and assumptions, posaconazole prophylaxis is expected to be cost-effective relative to fluconazole in recipients of allogeneic HSCT developing GVHD in the Netherlands. The cost-effectiveness of posaconazole depends on the IFI risk, which can vary by hospital

    Methods for visual mining of genomic and proteomic data atlases

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    <p>Abstract</p> <p>Background</p> <p>As the volume, complexity and diversity of the information that scientists work with on a daily basis continues to rise, so too does the requirement for new analytic software. The analytic software must solve the dichotomy that exists between the need to allow for a high level of scientific reasoning, and the requirement to have an intuitive and easy to use tool which does not require specialist, and often arduous, training to use. Information visualization provides a solution to this problem, as it allows for direct manipulation and interaction with diverse and complex data. The challenge addressing bioinformatics researches is how to apply this knowledge to data sets that are continually growing in a field that is rapidly changing.</p> <p>Results</p> <p>This paper discusses an approach to the development of visual mining tools capable of supporting the mining of massive data collections used in systems biology research, and also discusses lessons that have been learned providing tools for both local researchers and the wider community. Example tools were developed which are designed to enable the exploration and analyses of both proteomics and genomics based atlases. These atlases represent large repositories of raw and processed experiment data generated to support the identification of biomarkers through mass spectrometry (the PeptideAtlas) and the genomic characterization of cancer (The Cancer Genome Atlas). Specifically the tools are designed to allow for: the visual mining of thousands of mass spectrometry experiments, to assist in designing informed targeted protein assays; and the interactive analysis of hundreds of genomes, to explore the variations across different cancer genomes and cancer types.</p> <p>Conclusions</p> <p>The mining of massive repositories of biological data requires the development of new tools and techniques. Visual exploration of the large-scale atlas data sets allows researchers to mine data to find new meaning and make sense at scales from single samples to entire populations. Providing linked task specific views that allow a user to start from points of interest (from diseases to single genes) enables targeted exploration of thousands of spectra and genomes. As the composition of the atlases changes, and our understanding of the biology increase, new tasks will continually arise. It is therefore important to provide the means to make the data available in a suitable manner in as short a time as possible. We have done this through the use of common visualization workflows, into which we rapidly deploy visual tools. These visualizations follow common metaphors where possible to assist users in understanding the displayed data. Rapid development of tools and task specific views allows researchers to mine large-scale data almost as quickly as it is produced. Ultimately these visual tools enable new inferences, new analyses and further refinement of the large scale data being provided in atlases such as PeptideAtlas and The Cancer Genome Atlas.</p

    The value of randomized clinical trials for daily clinical practice.

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    Contains fulltext : 52751.pdf (publisher's version ) (Closed access
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