760 research outputs found
A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.BACKGROUND: The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. METHODS: We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. RESULTS: We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. CONCLUSIONS: Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based.CC is a recipient of a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (funding reference number—CGV 121171) and is a trainee on the Canadian Institutes of Health Research Drug Safety and Effectiveness Network team grant (funding reference number—116573). BH is funded by a New Investigator award from the Canadian Institutes of Health Research and the Drug Safety and Effectiveness Network. This research was partly supported by funding from CADTH as part of a project to develop Excel-based tools to support the conduct of health technology assessments. This research was also supported by Cornerstone Research Group
Telomere disruption results in non-random formation of de novo dicentric chromosomes involving acrocentric human chromosomes
Copyright: © 2010 Stimpson et al.Genome rearrangement often produces chromosomes with two centromeres (dicentrics) that are inherently unstable because of bridge formation and breakage during cell division. However, mammalian dicentrics, and particularly those in humans, can be quite stable, usually because one centromere is functionally silenced. Molecular mechanisms of centromere inactivation are poorly understood since there are few systems to experimentally create dicentric human chromosomes. Here, we describe a human cell culture model that enriches for de novo dicentrics. We demonstrate that transient disruption of human telomere structure non-randomly produces dicentric fusions involving acrocentric chromosomes. The induced dicentrics vary in structure near fusion breakpoints and like naturally-occurring dicentrics, exhibit various inter-centromeric distances. Many functional dicentrics persist for months after formation. Even those with distantly spaced centromeres remain functionally dicentric for 20 cell generations. Other dicentrics within the population reflect centromere inactivation. In some cases, centromere inactivation occurs by an apparently epigenetic mechanism. In other dicentrics, the size of the alpha-satellite DNA array associated with CENP-A is reduced compared to the same array before dicentric formation. Extrachromosomal fragments that contained CENP-A often appear in the same cells as dicentrics. Some of these fragments are derived from the same alpha-satellite DNA array as inactivated centromeres. Our results indicate that dicentric human chromosomes undergo alternative fates after formation. Many retain two active centromeres and are stable through multiple cell divisions. Others undergo centromere inactivation. This event occurs within a broad temporal window and can involve deletion of chromatin that marks the locus as a site for CENP-A maintenance/replenishment.This work was supported by the Tumorzentrum Heidelberg/Mannheim grant (D.10026941)and by March of Dimes Research Foundation grant #1-FY06-377 and NIH R01 GM069514
Death of a tumor: targeting CCN in pancreatic cancer
The matricellular protein CCN2 (connective tissue growth factor, CTGF) has been previously implicated in tumorigenesis. In pancreatic cancer cells, CCN2 expression occurs downstream of ras/MEK/ERK. Direct evidence that CCN2 mediates tumor progression in pancreatic cancer has been lacking. An exciting recent report by Bennewith et al. (Cancer Res 69:775–784, 2009) has used shRNA knockdown of CCN2 to illustrate that CCN2 contributes to growth of pancreatic tumor cells, both in vitro and in vivo. This report briefly summarizes these findings
Stretching the Rules: Monocentric Chromosomes with Multiple Centromere Domains
The centromere is a functional chromosome domain that is essential for faithful chromosome segregation during cell division and that can be reliably identified by the presence of the centromere-specific histone H3 variant CenH3. In monocentric chromosomes, the centromere is characterized by a single CenH3-containing region within a morphologically distinct primary constriction. This region usually spans up to a few Mbp composed mainly of centromere-specific satellite DNA common to all chromosomes of a given species. In holocentric chromosomes, there is no primary constriction; the centromere is composed of many CenH3 loci distributed along the entire length of a chromosome. Using correlative fluorescence light microscopy and high-resolution electron microscopy, we show that pea (Pisum sativum) chromosomes exhibit remarkably long primary constrictions that contain 3-5 explicit CenH3-containing regions, a novelty in centromere organization. In addition, we estimate that the size of the chromosome segment delimited by two outermost domains varies between 69 Mbp and 107 Mbp, several factors larger than any known centromere length. These domains are almost entirely composed of repetitive DNA sequences belonging to 13 distinct families of satellite DNA and one family of centromeric retrotransposons, all of which are unevenly distributed among pea chromosomes. We present the centromeres of Pisum as novel ``meta-polycentric'' functional domains. Our results demonstrate that the organization and DNA composition of functional centromere domains can be far more complex than previously thought, do not require single repetitive elements, and do not require single centromere domains in order to segregate properly. Based on these findings, we propose Pisum as a useful model for investigation of centromere architecture and the still poorly understood role of repetitive DNA in centromere evolution, determination, and function
Estimating required information size by quantifying diversity in random-effects model meta-analyses
<p>Abstract</p> <p>Background</p> <p>There is increasing awareness that meta-analyses require a sufficiently large information size to detect or reject an anticipated intervention effect. The required information size in a meta-analysis may be calculated from an anticipated <it>a priori </it>intervention effect or from an intervention effect suggested by trials with low-risk of bias.</p> <p>Methods</p> <p>Information size calculations need to consider the total model variance in a meta-analysis to control type I and type II errors. Here, we derive an adjusting factor for the required information size under any random-effects model meta-analysis.</p> <p>Results</p> <p>We devise a measure of diversity (<it>D</it><sup>2</sup>) in a meta-analysis, which is the relative variance reduction when the meta-analysis model is changed from a random-effects into a fixed-effect model. <it>D</it><sup>2 </sup>is the percentage that the between-trial variability constitutes of the sum of the between-trial variability and a sampling error estimate considering the required information size. <it>D</it><sup>2 </sup>is different from the intuitively obvious adjusting factor based on the common quantification of heterogeneity, the inconsistency (<it>I</it><sup>2</sup>), which may underestimate the required information size. Thus, <it>D</it><sup>2 </sup>and <it>I</it><sup>2 </sup>are compared and interpreted using several simulations and clinical examples. In addition we show mathematically that diversity is equal to or greater than inconsistency, that is <it>D</it><sup>2 </sup>≥ <it>I</it><sup>2</sup>, for all meta-analyses.</p> <p>Conclusion</p> <p>We conclude that <it>D</it><sup>2 </sup>seems a better alternative than <it>I</it><sup>2 </sup>to consider model variation in any random-effects meta-analysis despite the choice of the between trial variance estimator that constitutes the model. Furthermore, <it>D</it><sup>2 </sup>can readily adjust the required information size in any random-effects model meta-analysis.</p
Applying the Risk of Bias Tool in a Systematic Review of Combination Long-Acting Beta-Agonists and Inhaled Corticosteroids for Persistent Asthma
Background: The Risk of Bias (RoB) tool is used to assess internal validity of randomized controlled trials (RCTs). Our objectives were to: 1) evaluate inter-rater agreement of the RoB tool; 2) determine the time to access supplemental study information; 3) compare the RoB tool with the Jadad scale and Schulz allocation concealment (AC); and 4) examine the relationship between RoB and effect estimates. Methods: We conducted a systematic review of long-acting beta agonists (LABA) combined with inhaled corticosteroids (ICS) for adults with persistent asthma. Two reviewers independently assessed 107 trials using RoB, Jadad, and AC. One reviewer searched for study protocols. We assessed inter-rater agreement using weighted Kappa (k) and the correlation between tools using Kendall’s Tau (t). Mean differences in effect sizes for RCTs with different RoB were calculated using inverse variance method and random effects model. Results: Trials had good Jadad scores (median 4, IQR 3-4); however, 85 % had unclear AC and 87 % high RoB. The factor that most influenced RoB was the potential inappropriate influence of study sponsors (95 % industry funded). Agreement on RoB domains was fair (k = 0.40) to almost perfect (k = 0.86), and moderate for overall RoB (k = 0.41). Median time to complete RoB assessments was 21 minutes (IQR 14-27) and 12 minutes (IQR 9-16) to search for protocols. Protocols were identified for 5/42 studies (12%); in 3 cases the assessment of selective outcome reporting changed. There was low correlation between overall RoB vs. Jadad (t =0.04
Redox-Induced Src Kinase and Caveolin-1 Signaling in TGF-β1-Initiated SMAD2/3 Activation and PAI-1 Expression
Plasminogen activator inhibitor-1 (PAI-1), a major regulator of the plasmin-based pericellular proteolytic cascade, is significantly increased in human arterial plaques contributing to vessel fibrosis, arteriosclerosis and thrombosis, particularly in the context of elevated tissue TGF-β1. Identification of molecular events underlying to PAI-1 induction in response to TGF-β1 may yield novel targets for the therapy of cardiovascular disease.Reactive oxygen species are generated within 5 minutes after addition of TGF-β1 to quiescent vascular smooth muscle cells (VSMCs) resulting in pp60(c-src) activation and PAI-1 expression. TGF-β1-stimulated Src kinase signaling sustained the duration (but not the initiation) of SMAD3 phosphorylation in VSMC by reducing the levels of PPM1A, a recently identified C-terminal SMAD2/3 phosphatase, thereby maintaining SMAD2/3 in an active state with retention of PAI-1 transcription. The markedly increased PPM1A levels in triple Src kinase (c-Src, Yes, Fyn)-null fibroblasts are consistent with reductions in both SMAD3 phosphorylation and PAI-1 expression in response to TGF-β1 compared to wild-type cells. Activation of the Rho-ROCK pathway was mediated by Src kinases and required for PAI-1 induction in TGF-β1-stimulated VSMCs. Inhibition of Rho-ROCK signaling blocked the TGF-β1-mediated decrease in nuclear PPM1A content and effectively attenuated PAI-1 expression. TGF-β1-induced PAI-1 expression was undetectable in caveolin-1-null cells, correlating with the reduced Rho-GTP loading and SMAD2/3 phosphorylation evident in TGF-β1-treated caveolin-1-deficient cells relative to their wild-type counterparts. Src kinases, moreover, were critical upstream effectors of caveolin-1(Y14) phosphoryation and initiation of downstream signaling.TGF-β1-initiated Src-dependent caveolin-1(Y14) phosphorylation is a critical event in Rho-ROCK-mediated suppression of nuclear PPM1A levels maintaining, thereby, SMAD2/3-dependent transcription of the PAI-1 gene
Prevalence of Borderline Personality Disorder in University Samples: Systematic Review, Meta-Analysis and Meta-Regression.
OBJECTIVE: To determine pooled prevalence of clinically significant traits or features of Borderline Personality Disorder among college students, and explore the influence of methodological factors on reported prevalence figures, and temporal trends. DATA SOURCES: Electronic databases (1994-2014: AMED; Biological Abstracts; Embase; MEDLINE; PsycARTICLES; CINAHL Plus; Current Contents Connect; EBM Reviews; Google Scholar; Ovid Medline; Proquest central; PsychINFO; PubMed; Scopus; Taylor & Francis; Web of Science (1998-2014), and hand searches. STUDY SELECTION: Forty-three college-based studies reporting estimates of clinically significant BPD symptoms were identified (5.7% of original search). DATA EXTRACTION: One author (RM) extracted clinically relevant BPD prevalence estimates, year of publication, demographic variables, and method from each publication or through correspondence with the authors. RESULTS: The prevalence of BPD in college samples ranged from 0.5% to 32.1%, with lifetime prevalence of 9.7% (95% CI, 7.7-12.0; p < .005). Methodological factors contributing considerable between-study heterogeneity in univariate meta-analyses were participant anonymity, incentive type, research focus and participant type. Study and sample characteristics related to between study heterogeneity were sample size, and self-identifying as Asian or "other" race. The prevalence of BPD varied over time: 7.8% (95% CI 4.2-13.9) between 1994 and 2000; 6.5% (95% CI 4.0-10.5) during 2001 to 2007; and 11.6% (95% CI 8.8-15.1) from 2008 to 2014, yet was not a source of heterogeneity (p = .09). CONCLUSIONS: BPD prevalence estimates are influenced by the methodological or study sample factors measured. There is a need for consistency in measurement across studies to increase reliability in establishing the scope and characteristics of those with BPD engaged in tertiary study
Recommendations by Cochrane Review Groups for assessment of the risk of bias in studies
<p>Abstract</p> <p>Background</p> <p>Assessing the risk of bias in individual studies in a systematic review can be done using individual components or by summarizing the study quality in an overall score.</p> <p>Methods</p> <p>We examined the instructions to authors of the 50 Cochrane Review Groups that focus on clinical interventions for recommendations on methodological quality assessment of studies.</p> <p>Results</p> <p>Forty-one of the review groups (82%) recommended quality assessment using components and nine using a scale. All groups recommending components recommended to assess concealment of allocation, compared to only two of the groups recommending scales (P < 0.0001). Thirty-five groups (70%) recommended assessment of sequence generation and 21 groups (42%) recommended assessment of intention-to-treat analysis. Only 28 groups (56%) had specific recommendations for using the quality assessment of studies analytically in reviews, with sensitivity analysis, quality as an inclusion threshold and subgroup analysis being the most commonly recommended methods. The scales recommended had problems in the individual items and some of the groups recommending components recommended items not related to bias in their quality assessment.</p> <p>Conclusion</p> <p>We found that recommendations by some groups were not based on empirical evidence and many groups had no recommendations on how to use the quality assessment in reviews. We suggest that all Cochrane Review Groups refer to the Cochrane Handbook for Systematic Reviews of Interventions, which is evidence-based, in their instructions to authors and that their own guidelines are kept to a minimum and describe only how methodological topics that are specific to their fields should be handled.</p
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