scholarly journals BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Audrey Béliveau ◽  
Devon J. Boyne ◽  
Justin Slater ◽  
Darren Brenner ◽  
Paul Arora
Keyword(s):  
Best Practice ◽  
Meta Analysis ◽  
R Package ◽  
Model Fit ◽  
Support Unit ◽  
Best Practice Guidelines ◽  
League Tables ◽  
Regulatory Standards ◽  
Meta Analyses ◽  
Current Guidelines

Abstract Background Several reviews have noted shortcomings regarding the quality and reporting of network meta-analyses (NMAs). We suspect that this issue may be partially attributable to limitations in current NMA software which do not readily produce all of the output needed to satisfy current guidelines. Results To better facilitate the conduct and reporting of NMAs, we have created an R package called “BUGSnet” (Bayesian inference Using Gibbs Sampling to conduct a Network meta-analysis). This R package relies upon Just Another Gibbs Sampler (JAGS) to conduct Bayesian NMA using a generalized linear model. BUGSnet contains a suite of functions that can be used to describe the evidence network, estimate a model and assess the model fit and convergence, assess the presence of heterogeneity and inconsistency, and output the results in a variety of formats including league tables and surface under the cumulative rank curve (SUCRA) plots. We provide a demonstration of the functions contained within BUGSnet by recreating a Bayesian NMA found in the second technical support document composed by the National Institute for Health and Care Excellence Decision Support Unit (NICE-DSU). We have also mapped these functions to checklist items within current reporting and best practice guidelines. Conclusion BUGSnet is a new R package that can be used to conduct a Bayesian NMA and produce all of the necessary output needed to satisfy current scientific and regulatory standards. We hope that this software will help to improve the conduct and reporting of NMAs.

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
R Package ◽  
Effect Sizes ◽  
Forest Plot ◽  
Point Estimates ◽  
Aggregate Effect ◽  
The Individual ◽  
Meta Analyses ◽  
Heterogeneous Effect ◽  
Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

scholarly journals Comparison of the efficacy of hematopoietic stem cell mobilization regimens: a systematic review and network meta-analysis of preclinical studies

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chengxin Luo ◽  
Li Wang ◽  
Guixian Wu ◽  
Xiangtao Huang ◽  
Yali Zhang ◽  
...  
Keyword(s):  
Standard Dose ◽  
Meta Analysis ◽  
Secondary Outcome ◽  
Preclinical Studies ◽  
Mice Model ◽  
Short Term ◽  
Hematopoietic Stem ◽  
Support Unit ◽  
Meta Analyses

Abstract Background Mobilization failure may occur when the conventional hematopoietic stem cells (HSCs) mobilization agent granulocyte colony-stimulating factor (G-CSF) is used alone, new regimens were developed to improve mobilization efficacy. Multiple studies have been performed to investigate the efficacy of these regimens via animal models, but the results are inconsistent. We aim to compare the efficacy of different HSC mobilization regimens and identify new promising regimens with a network meta-analysis of preclinical studies. Methods We searched Medline and Embase databases for the eligible animal studies that compared the efficacy of different HSC mobilization regimens. Primary outcome is the number of total colony-forming cells (CFCs) in per milliliter of peripheral blood (/ml PB), and the secondary outcome is the number of Lin− Sca1+ Kit+ (LSK) cells/ml PB. Bayesian network meta-analyses were performed following the guidelines of the National Institute for Health and Care Excellence Decision Support Unit (NICE DSU) with WinBUGS version 1.4.3. G-CSF-based regimens were classified into the SD (standard dose, 200–250 μg/kg/day) group and the LD (low dose, 100–150 μg/kg/day) group based on doses, and were classified into the short-term (2–3 days) group and the long-term (4–5 days) group based on administration duration. Long-term SD G-CSF was chosen as the reference treatment. Results are presented as the mean differences (MD) with the associated 95% credibility interval (95% CrI) for each regimen. Results We included 95 eligible studies and reviewed the efficacy of 94 mobilization agents. Then 21 studies using the poor mobilizer mice model (C57BL/6 mice) to investigate the efficacy of different mobilization regimens were included for network meta-analysis. Network meta-analyses indicated that compared with long-term SD G-CSF alone, 14 regimens including long-term SD G-CSF + Me6, long-term SD G-CSF + AMD3100 + EP80031, long-term SD G-CSF + AMD3100 + FG-4497, long-term SD G-CSF + ML141, long-term SD G-CSF + desipramine, AMD3100 + meloxicam, long-term SD G-CSF + reboxetine, AMD3100 + VPC01091, long-term SD G-CSF + FG-4497, Me6, long-term SD G-CSF + EP80031, POL5551, long-term SD G-CSF + AMD3100, AMD1300 + EP80031 and long-term LD G-CSF + meloxicam significantly increased the collections of total CFCs. G-CSF + Me6 ranked first among these regimens in consideration of the number of harvested CFCs/ml PB (MD 2168.0, 95% CrI 2062.0−2272.0). In addition, 7 regimens including long-term SD G-CSF + AMD3100, AMD3100 + EP80031, long-term SD G-CSF + EP80031, short-term SD G-CSF + AMD3100 + IL-33, long-term SD G-CSF + ML141, short-term LD G-CSF + ARL67156, and long-term LD G-CSF + meloxicam significantly increased the collections of LSK cells compared with G-CSF alone. Long-term SD G-CSF + AMD3100 ranked first among these regimens in consideration of the number of harvested LSK cells/ml PB (MD 2577.0, 95% CrI 2422.0–2733.0). Conclusions Considering the number of CFC and LSK cells in PB as outcomes, G-CSF plus AMD3100, Me6, EP80031, ML141, FG-4497, IL-33, ARL67156, meloxicam, desipramine, and reboxetine are all promising mobilizing regimens for future investigation.

scholarly journals The ultrasound unit and infection control – Are we on the right track?

Ultrasound ◽  
2017 ◽  
Vol 25 (1) ◽  
pp. 53-57 ◽  
Author(s):  
Susan C Westerway ◽  
Jocelyne M Basseal
Keyword(s):  
Infection Control ◽  
Best Practice ◽  
Infection Prevention ◽  
Ultrasound Transducers ◽  
Awareness Campaign ◽  
Best Practice Guidelines ◽  
Hygiene Practices ◽  
Cleaning Methods ◽  
The Right ◽  
Current Guidelines

Best practice guidelines for the disinfection of ultrasound transducers and infection prevention in ultrasound departments are generally recommended by either government health groups or the ultrasound societies of individual countries. The literature shows a wide variance in not only transducer cleaning methods but basic hygiene practices in the ultrasound workplace. This paper describes results from a UK survey of disinfection of ultrasound transducers and hygiene practice in the workplace. The survey revealed that some ultrasound practitioners did not follow current guidelines with regard to the correct disinfection method of transducers, cords or ultrasound machine keyboards. Furthermore, the survey exposed the lack of training from the product manufacturers on how to use the disinfection product appropriately. These inconsistencies may be responsible for compliance issues and highlight the need for an awareness campaign and a unified approach to infection control by ultrasound practitioners.

scholarly journals Best practice guidelines for abstract screening large‐evidence systematic reviews and meta‐analyses

2019 ◽  
Vol 10 (3) ◽  
pp. 330-342 ◽  
Author(s):  
Joshua R. Polanin ◽  
Terri D. Pigott ◽  
Dorothy L. Espelage ◽  
Jennifer K. Grotpeter
Keyword(s):  
Systematic Reviews ◽  
Practice Guidelines ◽  
Best Practice ◽  
Best Practice Guidelines ◽  
Meta Analyses ◽  
Abstract Screening

scholarly journals metamicrobiomeR: an R package for analysis of microbiome relative abundance data using zero-inflated beta GAMLSS and meta-analysis across studies using random effect models

2018 ◽  
Author(s):  
Nhan Thi Ho ◽  
Fan Li
Keyword(s):  
Random Effects ◽  
High Throughput ◽  
Relative Abundance ◽  
High Throughput Sequencing ◽  
Meta Analysis ◽  
R Package ◽  
Standard Errors ◽  
Relative Abundances ◽  
Meta Analyses ◽  
Analysis Models

ABSTRACTBackgroundThe rapid growth of high-throughput sequencing-based microbiome profiling has yielded tremendous insights into human health and physiology. Data generated from high-throughput sequencing of 16S rRNA gene amplicons are often preprocessed into composition or relative abundance. However, reproducibility has been lacking due to the myriad of different experimental and computational approaches taken in these studies. Microbiome studies may report varying results on the same topic, therefore, meta-analyses examining different microbiome studies to provide robust results are important. So far, there is still a lack of implemented methods to properly examine differential relative abundances of microbial taxonomies and to perform meta-analysis examining the heterogeneity and overall effects across microbiome studies.ResultsWe developed an R package ‘metamicrobiomeR’ that applies Generalized Additive Models for Location, Scale and Shape (GAMLSS) with a zero-inflated beta (BEZI) family (GAMLSS-BEZI) for analysis of microbiome relative abundance datasets. Both simulation studies and application to real microbiome data demonstrate that GAMLSS-BEZI well performs in testing differential relative abundances of microbial taxonomies. Importantly, the estimates from GAMLSS-BEZI are log(odds ratio) of relative abundances between groups and thus are comparable between microbiome studies. As such, we also apply random effects meta-analysis models to pool estimates and their standard errors across microbiome studies. We demonstrate the meta-analysis workflow and highlight the utility of our package on four studies comparing gut microbiomes between male and female infants in the first six months of life.ConclusionsGAMLSS-BEZI allows proper examination of microbiome relative abundance data. Random effects meta-analysis models can be directly applied to pool comparable estimates and their standard errors to evaluate the heterogeneity and overall effects across microbiome studies. The examples and workflow using our metamicrobiomeR package are reproducible and applicable for the analyses and meta-analyses of other microbiome studies.

Influence of vitamin D on fracture reduction among older adults: a discussion of recent meta-analysis findings

2019 ◽  
Vol 28 (02) ◽  
pp. 136-139
Author(s):  
Heike A. Bischoff-Ferrari
Keyword(s):  
Older Adults ◽  
Vitamin D ◽  
Vitamin D Deficiency ◽  
Meta Analysis ◽  
Target Group ◽  
Fracture Reduction ◽  
Increased Risk ◽  
Health Target ◽  
Meta Analyses ◽  
Current Guidelines

AbstractRecent meta-analyses on vitamin D and fracture reduction have led physicians and patients to question current guidelines on vitamin D. In this review of four recent meta-analyses, we summarize these meta-analyses with regard to target group and relevance to current guidelines. Importantly, two of the recent meta-analyses target adults age 50 years and older without osteoporosis and vitamin D deficiency where trial data is still very limited and does not reflect the target group of older adults age 65 and older vulnerable to both osteoporosis and vitamin D deficiency. One other meta-analysis has a focus on vitamin D plus calcium with significant benefits for both total and hip fractures, and one excludes these trials and shows no benefit plus has been questioned for several limitations with regard to study design. In summary, for older adults at increased risk for fractures and/or vitamin D deficiency, it is still reasonable to take 800 to 1000 IU vitamin D per day, following current recommendations. Reducing the risk of fractures among vulnerable older adults age 65 and older, at risk of vitamin D deficiency and fractures, remains a major public health target.

scholarly journals 131 Meta-analysis of Primary Care Interventions to Address Frailty Among Adults Aged 65+

2019 ◽  
Vol 48 (Supplement_3) ◽  
pp. iii17-iii65
Author(s):  
Steve Macdonald ◽  
John Travers ◽  
Éidín Ní Shé ◽  
Jade Bailey ◽  
Roman Romero-Ortuno ◽  
...  
Keyword(s):  
Older Adults ◽  
Primary Care ◽  
Best Practice ◽  
Meta Analysis ◽  
Relative Effectiveness ◽  
Or Education ◽  
Frailty Status ◽  
Nutrition Supplementation ◽  
Quantitative Synthesis ◽  
Meta Analyses

Abstract Background Frailty can contribute to poor clinical outcomes including disability, illness, and death. Intervention against frailty may help older adults maintain overall health and independence, and a growing body of recent literature describes interventions specifically targeting frailty. The diversity of measurement constructs and intervention types raises a challenge for those seeking to identify best-practice strategies to manage frailty in the primary care setting, therefore this study aimed to quantify the relative effectiveness of reported interventions. Methods PubMed, CINAHL, Cochrane Register of Controlled Trials, and PEDr databases were interrogated, and reference lists of retrieved studies were also examined. For comparisons, articles were grouped by intervention and meta-analysis using the random effects model was performed wherever two or more studies examined the same outcome measure using similar interventions. Results 29 studies with a total of 4430 participants were included in this series of meta-analyses. Interventions included exercise (alone or plus nutrition supplementation or education), nutrition supplementation alone, comprehensive geriatric assessment (CGA), and hormone supplementation. Outcome measures included frailty (Fried criteria), physical performance, leg strength, and grip strength, among others. Interventions varied in relative effectiveness. When comparing studies that assessed frailty status using Fried’s criteria, exercise alone (n=3, RR=0.63 (CI 0.47–0.85), I2=0%) appeared effective versus control in improving status, as did exercise plus nutritional supplementation (n=2, RR=0.62 (CI 0.48–0.79), I2=0%), and exercise plus nutritional education (n=3, RR=0.69 (CI 0.58–0.82), I2=0%). CGA also appeared effective in improving frailty status (n=3, RR=0.77 (CI 0.64–0.93), I2=0%). Conclusion This series of meta-analyses indicates that several intervention types are associated with positive improvements in frailty status, and frailty-associated indicators. These results agree with previous findings, and represent an up-to-date quantitative synthesis of available literature on primary care interventions addressing frailty among older adults.

662 Clinical Outcomes from Prospective Randomized Trials on the Proportion of Carbohydrates versus Fat in Enteral Nutrition for Burn Patients

2020 ◽  
Vol 41 (Supplement_1) ◽  
pp. S176-S176
Author(s):  
Beth A Shields ◽  
Kaitlin A Pruskowski ◽  
James K Aden ◽  
Anthony Basel ◽  
Garrett W Britton ◽  
...  
Keyword(s):  
Enteral Nutrition ◽  
Clinical Outcomes ◽  
Burn Injury ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Burn Patients ◽  
Levels Of Evidence ◽  
American Society ◽  
Meta Analyses ◽  
Current Guidelines

Abstract Introduction Multiple organizations have developed guidelines for nutritional support following burn trauma. These guidelines are based on low levels of evidence and largely on expert opinion. We sought to compile randomized controlled trials (RCTs) evaluating clinical outcomes from carbohydrate versus fat in enteral nutrition (EN) for burn patients and then analyze outcomes via meta-analysis and compare these outcomes to current available guidelines. Methods We performed a literature search to identify RCTs evaluating outcomes of burn patients with different proportions of carbohydrate versus fat interventions. Meta-analyses were conducted on outcomes reported by more than one RCT with the DerSimonian and Laird random effects model. Statistical significance was established at α less than 0.05. Meta-analysis results were then evaluated alongside the available guidelines from American Society for Parenteral and Enteral Nutrition (ASPEN) and Society of Critical Care Medicine (SCCM), the European Society for Parenteral and Enteral Nutrition (ESPEN), and the International Society for Burn Injury (ISBI). Results We identified 3 studies meeting our inclusion criteria for RCTs. Meta-analysis showed lower fat, higher carbohydrate EN to be associated with lower incidence of pneumonia (p=0.0005) as well as a reduction in mortality (p=0.04). The ASPEN/SCCM and ISBI guidelines do not specifically address this topic. ESPEN recommends less than 60% carbohydrates and less than 35% fat. However, this is not in accordance with the 46–65% carbohydrate and 12–27% fat with favorable outcomes studied in the 3 identified RCTs. Conclusions As current guidelines are often not based on high levels of evidence, it was important to collect and evaluate all of the available RCTs. Our meta-analysis results of these RCTs demonstrated mortality benefits with lower fat, higher carbohydrate EN in burn patients. Additionally, we found lower rates of pneumonia with lower fat, higher carbohydrate EN. Applicability of Research to Practice Consideration should be made for 12–27% fat, 46–65% carbohydrate EN in burn patients; however, multicentered trials are required before strong recommendations can be made.

scholarly journals How to perform a meta-analysis with R: a practical tutorial

2019 ◽  
Vol 22 (4) ◽  
pp. 153-160 ◽  
Author(s):  
Sara Balduzzi ◽  
Gerta Rücker ◽  
Guido Schwarzer
Keyword(s):  
Mental Health ◽  
Meta Analysis ◽  
R Package ◽  
Outcome Data ◽  
Sensitivity Analyses ◽  
Binary Outcome ◽  
Software Environment ◽  
Flexible Tool ◽  
Funnel Plot ◽  
Meta Analyses

ObjectiveMeta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health.MethodsR package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses.ResultsThe working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types.ConclusionsR represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.

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