CINeMA:Software for semi-automated assessment of the Confidence In the results of Network Meta-Analysis

Network meta‐analysis (NMA) compares several interventions that are linked in a network of comparative studies and estimates the relative treatment effects between all treatments, using both direct and indirect evidence. NMA is increasingly used for decision making in health care, however, a user‐friendly system to evaluate the confidence that can be placed in the results of NMA is currently lacking. This paper is a tutorial describing the Confidence In Network Meta‐Analysis (CINeMA) web application, which is based on the framework developed by Salanti et al (2014, PLOS One, 9, e99682) and refined by Nikolakopoulou et al (2019, bioRxiv). Six domains that affect the level of confidence in the NMA results are considered: (a) within‐study bias, (b) reporting bias, (c) indirectness, (d) imprecision, (e) heterogeneity, and (f) incoherence. CINeMA is freely available and open‐source and no login is required. In the configuration step users upload their data, produce network plots and define the analysis and effect measure. The dataset should include assessments of study‐level risk of bias and judgments on indirectness. CINeMA calls the netmeta routine in R to estimate relative effects and heterogeneity. Users are then guided through a systematic evaluation of the six domains. In this way reviewers assess the level of concerns for each relative treatment effect from NMA as giving rise to “no concerns,” “some concerns,” or “major concerns” in each of the six domains, which are graphically summarized on the report page for all effect estimates. Finally, judgments across the domains are summarized into a single confidence rating (“high,” “moderate,” “low,” or “very low”). In conclusion, the user‐friendly web‐based CINeMA platform provides a transparent framework to evaluate evidence from systematic reviews with multiple interventions

Outcomes of non-invasive diagnostic modalities for the detection of coronary artery disease: network meta-analysis of diagnostic randomised controlled trials

Objective: To evaluate differences in downstream testing, coronary revascularisation, and clinical outcomes following non-invasive diagnostic modalities used to detect coronary artery disease. Design: Systematic review and network meta-analysis. Data sources: Medline, Medline in process, Embase, Cochrane Library for clinical trials, PubMed, Web of Science, SCOPUS, WHO International Clinical Trials Registry Platform, and Clinicaltrials.gov. Eligibility criteria for selecting studies: Diagnostic randomised controlled trials comparing non-invasive diagnostic modalities in patients presenting with symptoms suggestive of low risk acute coronary syndrome or stable coronary artery disease. Data synthesis: A random effects network meta-analysis synthesised available evidence from trials evaluating the effect of non-invasive diagnostic modalities on downstream testing and patient oriented outcomes in patients with suspected coronary artery disease. Modalities included exercise electrocardiograms, stress echocardiography, single photon emission computed tomography-myocardial perfusion imaging, real time myocardial contrast echocardiography, coronary computed tomographic angiography, and cardiovascular magnetic resonance. Unpublished outcome data were obtained from 11 trials. Results: 18 trials of patients with low risk acute coronary syndrome (n=11 329) and 12 trials of those with suspected stable coronary artery disease (n=22 062) were included. Among patients with low risk acute coronary syndrome, stress echocardiography, cardiovascular magnetic resonance, and exercise electrocardiograms resulted in fewer invasive referrals for coronary angiography than coronary computed tomographic angiography (odds ratio 0.28 (95% confidence interval 0.14 to 0.57), 0.32 (0.15 to 0.71), and 0.53 (0.28 to 1.00), respectively). There was no effect on the subsequent risk of myocardial infarction, but estimates were imprecise. Heterogeneity and inconsistency were low. In patients with suspected stable coronary artery disease, an initial diagnostic strategy of stress echocardiography or single photon emission computed tomography-myocardial perfusion imaging resulted in fewer downstream tests than coronary computed tomographic angiography (0.24 (0.08 to 0.74) and 0.57 (0.37 to 0.87), respectively). However, exercise electrocardiograms yielded the highest downstream testing rate. Estimates for death and myocardial infarction were imprecise without clear discrimination between strategies. Conclusions: For patients with low risk acute coronary syndrome, an initial diagnostic strategy of stress echocardiography or cardiovascular magnetic resonance is associated with fewer referrals for invasive coronary angiography and revascularisation procedures than non-invasive anatomical testing, without apparent impact on the future risk of myocardial infarction. For suspected stable coronary artery disease, there was no clear discrimination between diagnostic strategies regarding the subsequent need for invasive coronary angiography, and differences in the risk of myocardial infarction cannot be ruled out. Systematic review registration: PROSPERO registry no CRD42016049442

CINeMA: An approach for assessing confidence in the results of a network meta-analysis.

BACKGROUND The evaluation of the credibility of results from a meta-analysis has become an important part of the evidence synthesis process. We present a methodological framework to evaluate confidence in the results from network meta-analyses, Confidence in Network Meta-Analysis (CINeMA), when multiple interventions are compared. METHODOLOGY CINeMA considers 6 domains: (i) within-study bias, (ii) reporting bias, (iii) indirectness, (iv) imprecision, (v) heterogeneity, and (vi) incoherence. Key to judgments about within-study bias and indirectness is the percentage contribution matrix, which shows how much information each study contributes to the results from network meta-analysis. The contribution matrix can easily be computed using a freely available web application. In evaluating imprecision, heterogeneity, and incoherence, we consider the impact of these components of variability in forming clinical decisions. CONCLUSIONS Via 3 examples, we show that CINeMA improves transparency and avoids the selective use of evidence when forming judgments, thus limiting subjectivity in the process. CINeMA is easy to apply even in large and complicated networks

PCR-based detection of mobile genetic elements in total community DNA

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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

Endothelial LRP1 protects against neurodegeneration by blocking cyclophilin A

The low-density lipoprotein receptor-related protein 1 (LRP1) is an endocytic and cell signaling transmembrane protein. Endothelial LRP1 clears proteinaceous toxins at the blood-brain barrier (BBB), regulates angiogenesis, and is increasingly reduced in Alzheimer\u27s disease associated with BBB breakdown and neurodegeneration. Whether loss of endothelial LRP1 plays a direct causative role in BBB breakdown and neurodegenerative changes remains elusive. Here, we show that LRP1 inactivation from the mouse endothelium results in progressive BBB breakdown, followed by neuron loss and cognitive deficits, which is reversible by endothelial-specific LRP1 gene therapy. LRP1 endothelial knockout led to a self-autonomous activation of the cyclophilin A-matrix metalloproteinase-9 pathway in the endothelium, causing loss of tight junctions underlying structural BBB impairment. Cyclophilin A inhibition in mice with endothelial-specific LRP1 knockout restored BBB integrity and reversed and prevented neuronal loss and behavioral deficits. Thus, endothelial LRP1 protects against neurodegeneration by inhibiting cyclophilin A, which has implications for the pathophysiology and treatment of neurodegeneration linked to vascular dysfunction

Use of bioengineering techniques in river restoration from a functional perspective: understanding drivers of nitrogen removal

Many bioengineering techniques involve the use of helophytes to reduce soil erosion and increase landscape stabilization. However, helophytes can influence carbon (C) quality, water residence time and biogeochemical rates, and thus they can also play a relevant role on in-stream nitrogen (N) removal (Peipoch et al., 2013). Therefore, these bioengineering techniques could be successfully applied in stream reaches downstream of wastewater treatment plant (WWTP) effluents which usually exhibit a high capacity to nitrify ammonium but a low capacity to permanently remove N via denitrification (Ribot et al. 2012). In this study, we tested the effect of helophytes on net N removal by using flumes receiving treated water from a WWTP. Furthermore, we added a labile C source to the flumes to test whether the low C quality of the treated waste water can limit N removal, and in particular denitrification.Instituto de Limnología "Dr. Raúl A. Ringuelet

ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis

Background Selective outcome reporting and publication bias threaten the validity of systematic reviews and meta-analyses and can affect clinical decision-making. A rigorous method to evaluate the impact of this bias on the results of network meta-analyses of interventions is lacking. We present a tool to assess the Risk Of Bias due to Missing Evidence in Network meta-analysis (ROB-MEN). Methods ROB-MEN first evaluates the risk of bias due to missing evidence for each of the possible pairwise comparison that can be made between the interventions in the network. This step considers possible bias due to the presence of studies with unavailable results (within-study assessment of bias) and the potential for unpublished studies (across-study assessment of bias). The second step combines the judgements about the risk of bias due to missing evidence in pairwise comparisons with (i) the contribution of direct comparisons to the network meta-analysis estimates, (ii) possible small-study effects evaluated by network meta-regression, and (iii) any bias from unobserved comparisons. Then, a level of “low risk”, “some concerns”, or “high risk” for the bias due to missing evidence is assigned to each estimate, which is our tool’s final output. Results We describe the methodology of ROB-MEN step-by-step using an illustrative example from a published NMA of non-diagnostic modalities for the detection of coronary artery disease in patients with low risk acute coronary syndrome. We also report a full application of the tool on a larger and more complex published network of 18 drugs from head-to-head studies for the acute treatment of adults with major depressive disorder. Conclusions ROB-MEN is the first tool for evaluating the risk of bias due to missing evidence in network meta-analysis and applies to networks of all sizes and geometry. The use of ROB-MEN is facilitated by an R Shiny web application that produces the Pairwise Comparisons and ROB-MEN Table and is incorporated in the reporting bias domain of the CINeMA framework and software