scholarly journals Powerful p-value combination methods to detect incomplete association

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sora Yoon ◽  
Bukyung Baik ◽  
Taesung Park ◽  
Dougu Nam
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Null Distribution ◽  
R Package ◽  
P Value ◽  
Experimental Conditions ◽  
Combination Methods ◽  
Analysis Methods ◽  
Meta Analyses ◽  
Microarray Datasets

AbstractMeta-analyses increase statistical power by combining statistics from multiple studies. Meta-analysis methods have mostly been evaluated under the condition that all the data in each study have an association with the given phenotype. However, specific experimental conditions in each study or genetic heterogeneity can result in “unassociated statistics” that are derived from the null distribution. Here, we show that power of conventional meta-analysis methods rapidly decreases as an increasing number of unassociated statistics are included, whereas the classical Fisher’s method and its weighted variant (wFisher) exhibit relatively high power that is robust to addition of unassociated statistics. We also propose another robust method based on joint distribution of ordered p-values (ordmeta). Simulation analyses for t-test, RNA-seq, and microarray data demonstrated that wFisher and ordmeta, when only a small number of studies have an association, outperformed existing meta-analysis methods. We performed meta-analyses of nine microarray datasets (prostate cancer) and four association summary datasets (body mass index), where our methods exhibited high biological relevance and were able to detect genes that the-state-of-the-art methods missed. The metapro R package that implements the proposed methods is available from both CRAN and GitHub (http://github.com/unistbig/metapro).

Power-Enhanced Funnel Plots for Meta-Analysis

2020 ◽  
Vol 228 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Relevant Information ◽  
Selective Reporting ◽  
Graphical Display ◽  
Funnel Plot ◽  
Evidential Value ◽  
Graphical Displays ◽  
Funnel Plots ◽  
Meta Analyses

Abstract. Currently, dedicated graphical displays to depict study-level statistical power in the context of meta-analysis are unavailable. Here, we introduce the sunset (power-enhanced) funnel plot to visualize this relevant information for assessing the credibility, or evidential value, of a set of studies. The sunset funnel plot highlights the statistical power of primary studies to detect an underlying true effect of interest in the well-known funnel display with color-coded power regions and a second power axis. This graphical display allows meta-analysts to incorporate power considerations into classic funnel plot assessments of small-study effects. Nominally significant, but low-powered, studies might be seen as less credible and as more likely being affected by selective reporting. We exemplify the application of the sunset funnel plot with two published meta-analyses from medicine and psychology. Software to create this variation of the funnel plot is provided via a tailored R function. In conclusion, the sunset (power-enhanced) funnel plot is a novel and useful graphical display to critically examine and to present study-level power in the context of meta-analysis.

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 Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 110
Author(s):  
Elizabeth Korevaar ◽  
Amalia Karahalios ◽  
Andrew B. Forbes ◽  
Simon L. Turner ◽  
Steve McDonald ◽  
...  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Systematic Reviews ◽  
Data Extraction ◽  
Meta Analysis ◽  
Interrupted Time Series ◽  
Analysis Methods ◽  
Study Selection ◽  
The Individual ◽  
Meta Analyses

Background: Systematic reviews are used to inform healthcare decision making. In reviews that aim to examine the effects of organisational, policy change or public health interventions, or exposures, evidence from interrupted time series (ITS) studies may be included. A core component of many systematic reviews is meta-analysis, which is the statistical synthesis of results across studies. There is currently a lack of guidance informing the choice of meta-analysis methods for combining results from ITS studies, and there have been no studies examining the meta-analysis methods used in practice. This study therefore aims to describe current meta-analysis methods used in a cohort of reviews of ITS studies. Methods: We will identify the 100 most recent reviews (published between 1 January 2000 and 11 October 2019) that include meta-analyses of ITS studies from a search of eight electronic databases covering several disciplines (public health, psychology, education, economics). Study selection will be undertaken independently by two authors. Data extraction will be undertaken by one author, and for a random sample of the reviews, two authors. From eligible reviews we will extract details at the review level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies. Descriptive statistics will be used to summarise the data. Conclusions: This review will describe the methods used to meta-analyse results from ITS studies. Results from this review will inform future methods research examining how different meta-analysis methods perform, and ultimately, the development of guidance.

scholarly journals A Systematic Review and Meta-Analysis on the Significance of TIGIT in Solid Cancers: Dual TIGIT/PD-1 Blockade to Overcome Immune-Resistance in Solid Cancers

2021 ◽  
Vol 22 (19) ◽  
pp. 10389
Author(s):  
Negar Hosseinkhani ◽  
Mahdi Abdoli Shadbad ◽  
Mohammad Asghari Jafarabadi ◽  
Noora Karim Ahangar ◽  
Zahra Asadzadeh ◽  
...  
Keyword(s):  
Systematic Review ◽  
T Cells ◽  
Cd8 T Cells ◽  
Meta Analysis ◽  
Strong Association ◽  
Positive Association ◽  
P Value ◽  
Immune Resistance ◽  
Current Systematic Review ◽  
Meta Analyses

Preclinical studies have indicated that T-cell immunoglobulin and ITIM domain (TIGIT) can substantially attenuate anti-tumoral immune responses. Although multiple clinical studies have evaluated the significance of TIGIT in patients with solid cancers, their results remain inconclusive. Thus, we conducted the current systematic review and meta-analysis based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) to determine its significance in patients with solid cancers. We systematically searched the Web of Science, Embase, PubMed, and Scopus databases to obtain peer-reviewed studies published before September 20, 2020. Our results have shown that increased TIGIT expression has been significantly associated with inferior overall survival (OS) (HR = 1.42, 95% CI: 1.11–1.82, and p-value = 0.01). Besides, the level of tumor-infiltrating TIGIT+CD8+ T-cells have been remarkably associated inferior OS and relapse-free survival (RFS) of affected patients (HR = 2.17, 95% CI: 1.43–3.29, and p-value < 0.001, and HR = 1.89, 95% CI: 1.36–2.63, and p-value < 0.001, respectively). Also, there is a strong positive association between TIGIT expression with programmed cell death-1 (PD-1) expression in these patients (OR = 1.71, 95% CI: 1.10–2.68, and p-value = 0.02). In summary, increased TIGIT expression and increased infiltration of TIGIT+CD8+ T-cells can substantially worsen the prognosis of patients with solid cancers. Besides, concerning the observed strong association between TIGIT and PD-1, ongoing clinical trials, and promising preclinical results, PD-1/TIGIT dual blockade can potentially help overcome the immune-resistance state seen following monotherapy with a single immune checkpoint inhibitor in patients with solid cancers.

scholarly journals Junk Food Consumption and Symptoms of Mental Health Problems: A Meta-Analysis for Public Health Awareness

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Muhammad Hafizurrachman ◽  
Risky Kusuma Hartono
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Food Consumption ◽  
Mental Health Problems ◽  
Meta Analysis ◽  
Health Problems ◽  
P Value ◽  
Junk Food ◽  
Frequent Consumption ◽  
Meta Analyses

Junk food consumption increases the risk of having symptoms of mental health problems. This study aimed to conduct a meta-analysis to assess the association between junk food and symptoms of mental health problems. Six researchers, two primary researchers, and four assistant researchers, from October to December 2020 conducted a systematic literature review. The data sources were selected from Pubmed and Science Direct articles published from 2010 to 2020. Those websites were check-marked for text availability for original articles, using keywords for junk foods and mental health. This study had inclusion criteria for selecting and organizing articles using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. The full-text articles were selected for conducting a meta-analysis using R Studio Software. The 5,079 article titles were obtained, seven of which met the relevant requirements for meta-analysis. The range of respondents who experienced symptoms of mental illness was 1.38%–79.8%. There was no heterogeneity based on the Tau-square test. The correlation coefficient was 0.11 (95% CI 0.09–0.14), with no publication bias based on Egger’s Regression test (0.6023 or p-value>0.05). The frequent consumption of junk food can contribute to mental illness symptoms, even with minimal effects.

scholarly journals Anticariogenic action and safety profile of a cacao bean husk extract: A systematic review and meta-analysis

2021 ◽  
Vol 8 (1) ◽  
pp. 118-127
Author(s):  
Flavio Martinez-Morales ◽  
Saray Aranda Romo ◽  
Othoniel Hugo Aragon-Martinez
Keyword(s):  
Systematic Review ◽  
Safety Profile ◽  
Meta Analysis ◽  
P Value ◽  
Mouth Rinse ◽  
P Values ◽  
Scientific Databases ◽  
Z Value ◽  
Cariogenic Bacterium ◽  
Meta Analyses

Nowadays, there is not a meta-analytic synthesis of the clinical reports that used a cacao bean husk extract (CBHE) solution as an anticariogenic mouth rinse. Thus, the aim of this study was to evaluate that information through a systematic review and meta-analysis methodology, conducted in accordance with PRISMA guidelines. Scientific databases were searched for studies published up to June 2021. Inclusion and exclusion criteria were applied to studies found and then, their data was analyzed. The five selected studies were categorized with a 36.6, 58.5, and 4.9 % of a low, unclear, and high risk of bias, respectively. Under appropriate heterogeneities (I2 values from 0 to 65 %, p values > 0.09) and absent reporting bias (symmetrical funnels), the meta-analyses show that the use of a CBHE mouth rinse reduced the salivary count of Streptococcus mutans (Z values from 2.45 to 10.61, p values < 0.01), similar to the chlorhexidine rinse performance (Z value= 0.55, p value= 0.58), and produced an insignificant presence of adverse events (Z value= 0.92, p value= 0.36) in children and adults, all these effects compared with those volunteers under an ethanol rinse or their pretest conditions. In conclusion, the CBHE mouth rinse reduced a cariogenic bacterium under an acceptable safety profile, but more clinical studies with high quality and more parameters are needed.

scholarly journals Mortality rates in matched cohort, pseudo-randomised and randomised trials of convalescent plasma given to COVID-19 patients

2020 ◽  
Author(s):  
Amar Ahmad ◽  
Marwa Salsabil ◽  
Tim Oliver
Keyword(s):  
Vitamin D ◽  
Meta Analysis ◽  
P Value ◽  
Matched Cohort ◽  
Randomised Trials ◽  
Published Evidence ◽  
Increased Risk ◽  
Life Threatening ◽  
Number Of Publications ◽  
Meta Analyses

AbstractIntroductionFor more than 80 years convalescent or immune sera has been used in severe life threatening infections. Since March of this year a rapidly increasing number of publications have reported series of Convalescent plasma (CP) investigations in severely ill COVID-19 patients.Objectivea brief CP scoping review focusing on early mortalityMethodsWe searched available data bases. Three randomised trials, two pseudo-randomised observations and twelve matched cohort studies were identified. Random-effects meta-analyses were performed on extracted dataResultsA total of 2,378 CP treated and 5188 “controls” in 17 studies. Individually only two studies were significant for reduction of deaths to 30 days, but all showed a similar percentage reduction. When pooled, meta-analysis was undertaken. It showed that the overall reduction of death was significant for all series RR 0.710 (p=0.00001), all matched cohort series RR = 0.610 (p-value = 0.001) and the two pseudo-randomised series RR 0.747 (p=0.005) but not the three technically inadequate randomised trials, RR 0.825 (p=0.397). In two of these randomised trials, there was faster clearance of Viral DNA at 72 hours after CP than placeboConclusionIt is hoped the significance of this less than perfect data will increase interest in completing the delayed randomised trials as the results suggest they could be better than currently licenced drugs. Given increasing published evidence of increased risk of both diagnosis and death from COVID-19 in patients with severe Vitamin-D deficiency, future studies should also study influence of Vitamin-D status of donor and recipient on outcome.

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.

scholarly journals Quantifying the advantages of conducting a prospective meta-analysis (PMA): a case study of early childhood obesity prevention

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
A. L. Seidler ◽  
◽  
K. E. Hunter ◽  
D. Espinoza ◽  
S. Mihrshahi ◽  
...  
Keyword(s):  
Early Childhood ◽  
Childhood Obesity ◽  
External Validity ◽  
Statistical Power ◽  
Meta Analysis ◽  
Intervention Design ◽  
Intervention Effects ◽  
Early Childhood Obesity ◽  
Limited Power ◽  
Meta Analyses

Abstract Background For prospective meta-analyses (PMAs), eligible studies are identified, and the PMA hypotheses, selection criteria, and analysis methods are pre-specified before the results of any of the studies are known. This reduces publication bias and selective outcome reporting and provides a unique opportunity for outcome standardisation/harmonisation. We conducted a world-first PMA of four trials investigating interventions to prevent early childhood obesity. The aims of this study were to quantitatively analyse the effects of prospective planning on variations across trials, outcome harmonisation, and the power to detect intervention effects, and to derive recommendations for future PMA. Methods We examined intervention design, participant characteristics, and outcomes collected across the four trials included in the EPOCH PMA using their registration records, protocol publications, and variable lists. The outcomes that trials planned to collect prior to inclusion in the PMA were compared to the outcomes that trials collected after PMA inclusion. We analysed the proportion of matching outcome definitions across trials, the number of outcomes per trial, and how collaboration increased the statistical power to detect intervention effects. Results The included trials varied in intervention design and participants, this improved external validity and the ability to perform subgroup analyses for the meta-analysis. While individual trials had limited power to detect the main intervention effect (BMI z-score), synthesising data substantially increased statistical power. Prospective planning led to an increase in the number of collected outcome categories (e.g. weight, child’s diet, sleep), and greater outcome harmonisation. Prior to PMA inclusion, only 18% of outcome categories were included in all trials. After PMA inclusion, this increased to 91% of outcome categories. However, while trials mostly collected the same outcome categories after PMA inclusion, some inconsistencies in how the outcomes were measured remained (such as measuring physical activity by hours of outside play versus using an activity monitor). Conclusion Prospective planning led to greater outcome harmonisation and greater power to detect intervention effects, while maintaining acceptable variation in trial designs and populations, which improved external validity. Recommendations for future PMA include more detailed harmonisation of outcome measures and careful pre-specification of analyses to avoid research waste by unnecessary over-collection of data.

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