Meta-analysis: A 12-step program

Author(s):  
L. Streiner David

Meta-analysis is a technique for combining the results of many studies in a rigorous and systematic manner, to allow us to better assess prevalence rates for different types of gambling and determine which interventions have the best evidence regarding their effectiveness and efficacy. Meta-analysis consists of (a) a comprehensive search for all available evidence; (b) the use of applying explicit criteria for determining which articles to include; (c) determination of an effect size for each study; and (d) the pooling of effect sizes across studies to end up with a global estimate of the prevalence or the effectiveness of a treatment. This paper begins with a discussion of why meta-analyses are useful, followed by a 12-step program for conducting a meta-analysis. This program can be used both by people planning to do such an analysis, as well as by readers of a meta-analysis, to evaluate how well it was carried out.

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Liansheng Larry Tang ◽  
Michael Caudy ◽  
Faye Taxman

Multiple meta-analyses may use similar search criteria and focus on the same topic of interest, but they may yield different or sometimes discordant results. The lack of statistical methods for synthesizing these findings makes it challenging to properly interpret the results from multiple meta-analyses, especially when their results are conflicting. In this paper, we first introduce a method to synthesize the meta-analytic results when multiple meta-analyses use the same type of summary effect estimates. When meta-analyses use different types of effect sizes, the meta-analysis results cannot be directly combined. We propose a two-step frequentist procedure to first convert the effect size estimates to the same metric and then summarize them with a weighted mean estimate. Our proposed method offers several advantages over existing methods by Hemming et al. (2012). First, different types of summary effect sizes are considered. Second, our method provides the same overall effect size as conducting a meta-analysis on all individual studies from multiple meta-analyses. We illustrate the application of the proposed methods in two examples and discuss their implications for the field of meta-analysis.


2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  

‘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.


2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson

Andrews & Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.


2021 ◽  
Vol 5 (1) ◽  
pp. e100135
Author(s):  
Xue Ying Zhang ◽  
Jan Vollert ◽  
Emily S Sena ◽  
Andrew SC Rice ◽  
Nadia Soliman

ObjectiveThigmotaxis is an innate predator avoidance behaviour of rodents and is enhanced when animals are under stress. It is characterised by the preference of a rodent to seek shelter, rather than expose itself to the aversive open area. The behaviour has been proposed to be a measurable construct that can address the impact of pain on rodent behaviour. This systematic review will assess whether thigmotaxis can be influenced by experimental persistent pain and attenuated by pharmacological interventions in rodents.Search strategyWe will conduct search on three electronic databases to identify studies in which thigmotaxis was used as an outcome measure contextualised to a rodent model associated with persistent pain. All studies published until the date of the search will be considered.Screening and annotationTwo independent reviewers will screen studies based on the order of (1) titles and abstracts, and (2) full texts.Data management and reportingFor meta-analysis, we will extract thigmotactic behavioural data and calculate effect sizes. Effect sizes will be combined using a random-effects model. We will assess heterogeneity and identify sources of heterogeneity. A risk-of-bias assessment will be conducted to evaluate study quality. Publication bias will be assessed using funnel plots, Egger’s regression and trim-and-fill analysis. We will also extract stimulus-evoked limb withdrawal data to assess its correlation with thigmotaxis in the same animals. The evidence obtained will provide a comprehensive understanding of the strengths and limitations of using thigmotactic outcome measure in animal pain research so that future experimental designs can be optimised. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines and disseminate the review findings through publication and conference presentation.


2016 ◽  
Vol 26 (4) ◽  
pp. 364-368 ◽  
Author(s):  
P. Cuijpers ◽  
E. Weitz ◽  
I. A. Cristea ◽  
J. Twisk

AimsThe standardised mean difference (SMD) is one of the most used effect sizes to indicate the effects of treatments. It indicates the difference between a treatment and comparison group after treatment has ended, in terms of standard deviations. Some meta-analyses, including several highly cited and influential ones, use the pre-post SMD, indicating the difference between baseline and post-test within one (treatment group).MethodsIn this paper, we argue that these pre-post SMDs should be avoided in meta-analyses and we describe the arguments why pre-post SMDs can result in biased outcomes.ResultsOne important reason why pre-post SMDs should be avoided is that the scores on baseline and post-test are not independent of each other. The value for the correlation should be used in the calculation of the SMD, while this value is typically not known. We used data from an ‘individual patient data’ meta-analysis of trials comparing cognitive behaviour therapy and anti-depressive medication, to show that this problem can lead to considerable errors in the estimation of the SMDs. Another even more important reason why pre-post SMDs should be avoided in meta-analyses is that they are influenced by natural processes and characteristics of the patients and settings, and these cannot be discerned from the effects of the intervention. Between-group SMDs are much better because they control for such variables and these variables only affect the between group SMD when they are related to the effects of the intervention.ConclusionsWe conclude that pre-post SMDs should be avoided in meta-analyses as using them probably results in biased outcomes.


2012 ◽  
Vol 9 (5) ◽  
pp. 610-620 ◽  
Author(s):  
Thomas A Trikalinos ◽  
Ingram Olkin

Background Many comparative studies report results at multiple time points. Such data are correlated because they pertain to the same patients, but are typically meta-analyzed as separate quantitative syntheses at each time point, ignoring the correlations between time points. Purpose To develop a meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects. Methods We present both fixed and random effects methods for multivariate meta-analysis of effect sizes reported at multiple time points. We provide formulas for calculating the covariance (and correlations) of the effect sizes at successive time points for four common metrics (log odds ratio, log risk ratio, risk difference, and arcsine difference) based on data reported in the primary studies. We work through an example of a meta-analysis of 17 randomized trials of radiotherapy and chemotherapy versus radiotherapy alone for the postoperative treatment of patients with malignant gliomas, where in each trial survival is assessed at 6, 12, 18, and 24 months post randomization. We also provide software code for the main analyses described in the article. Results We discuss the estimation of fixed and random effects models and explore five options for the structure of the covariance matrix of the random effects. In the example, we compare separate (univariate) meta-analyses at each of the four time points with joint analyses across all four time points using the proposed methods. Although results of univariate and multivariate analyses are generally similar in the example, there are small differences in the magnitude of the effect sizes and the corresponding standard errors. We also discuss conditional multivariate analyses where one compares treatment effects at later time points given observed data at earlier time points. Limitations Simulation and empirical studies are needed to clarify the gains of multivariate analyses compared with separate meta-analyses under a variety of conditions. Conclusions Data reported at multiple time points are multivariate in nature and are efficiently analyzed using multivariate methods. The latter are an attractive alternative or complement to performing separate meta-analyses.


2021 ◽  
pp. 019459982110350
Author(s):  
Basil Razi ◽  
Adam Perkovic ◽  
Raquel Alvarado ◽  
Anna Stroud ◽  
Jacqueline Ho ◽  
...  

Objective To determine the range of incidental mucosal changes in a general sinonasally asymptomatic population on radiology. Data Sources Medline (1996-present) and Embase (1974-present) were searched on March 14, 2020, to identify articles that reported radiological sinus mucosal findings in asymptomatic population groups. Bibliographic search of included studies was conducted to identify additional articles. Review Methods The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and Cochrane Handbook for Systematic Reviews of Interventions. A comprehensive search strategy was formulated and articles screened to extract data reporting Lund-Mackay (LM) score, presence of mucous retention cysts, and maxillary mucosal thickening. A random-effects model was used in meta-analysis. Results A total of 950 articles were identified, of which 33 manuscripts met the inclusion criteria. The included studies involved 16,966 sinonasally asymptomatic subjects. The mean LM score was 2.24 (95% CI, 1.61-2.87), and an LM score of ≥4 in 14.71% (95% CI, 6.86-24.82%) was present across all general asymptomatic population groups. Mucous retention cysts were noted in 13% (95% CI, 8.33-18.55%) and maxillary mucosal thickening of ≥2 mm in 17.73% (95% CI, 8.67-29.08%). Conclusion The prevalence of incidental mucosal changes in a general asymptomatic population on radiology needs to be considered when making a diagnosis of chronic rhinosinusitis.


2018 ◽  
Vol 64 (10) ◽  
pp. 942-951 ◽  
Author(s):  
Mohammad Zare ◽  
Jamal Jafari-Nedooshan ◽  
Mohammadali Jafari ◽  
Hossein Neamatzadeh ◽  
Seyed Mojtaba Abolbaghaei ◽  
...  

SUMMARY OBJECTIVE: There has been increasing interest in the study of the association between human mutL homolog 1 (hMLH1) gene polymorphisms and risk of colorectal cancer (CRC). However, results from previous studies are inconclusive. Thus, a meta-analysis was conducted to derive a more precise estimation of the effects of this gene. METHODS: A comprehensive search was conducted in the PubMed, EMBASE, Chinese Biomedical Literature databases until January 1, 2018. Odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of the association. RESULTS: Finally, 38 case-control studies in 32 publications were identified met our inclusion criteria. There were 14 studies with 20668 cases and 19533 controls on hMLH1 −93G>A, 11 studies with 5,786 cases and 8,867 controls on 655A>G and 5 studies with 1409 cases and 1637 controls on 1151T>A polymorphism. The combined results showed that 655A>G and 1151T>A polymorphisms were significantly associated with CRC risk, whereas −93G>A polymorphism was not significantly associated with CRC risk. As for ethnicity, −93G>A and 655A>G polymorphisms were associated with increased risk of CRC among Asians, but not among Caucasians. More interestingly, subgroup analysis indicated that 655A>G might raise CRC risk in PCR-RFLP and HB subgroups. CONCLUSION: Inconsistent with previous meta-analyses, this meta-analysis shows that the hMLH1 655A>G and 1151T>A polymorphisms might be risk factors for CRC. Moreover, the −93G>A polymorphism is associated with the susceptibility of CRC in Asian population.


Author(s):  
Timothy T. Adeliyi ◽  
Ropo E. Ogunsakin ◽  
Marion O. Adebiyi ◽  
Oludayo O. Olugbara

Channel zapping delays are inconveniences that are often experienced by the subscribers of Internet protocol television (IPTV). It is a major bottleneck in the IPTV channels switching system that affect the quality of experience of users. Consequently, numerous channels switching approaches to minimize zapping delay in IPTV have been suggested. However, there is little knowledge reported in the literature on the determination of the strength of the evidence presented on the approaches of reducing zapping delay in IPTV, which is the prime purpose of this study. The extraction of the relevant articles was designed following the technique of preferred reporting items for systematic reviews and meta-analyses (PRISMA). All the included research articles were searched from the widely used databases of Google Scholar, and Web of Science. All statistical analyses were performed with the aid of the random-effects model implementation in Stata version 15. The overall pooled estimated delay component was presented in forest plots. Overall, thirteen studies were included in the meta-analysis and the overall pooled estimate was 10% (95% CI: 7%, 30%)). Experimental studies have shown that virtual elimination of IPTV zapping delay is possible for a relevant chunk of channel switching requests.


2019 ◽  
Author(s):  
◽  
Sharon Ann Van Wicklin

Background. Patients undergoing surgery in the Trendelenburg and prone positions may be at risk for postoperative vision loss associated with increased intraocular pressure. The purpose of this dissertation research is to estimate the magnitude of the increase in intraocular pressure at specific perioperative time points in adult patients undergoing surgery in the Trendelenburg and prone positions. Methods. Comprehensive search strategies were used to identify eligible studies for two meta-analyses and to address the research questions. For each meta-analysis, standardized mean difference effect sizes were calculated for selected perioperative time points. Results. Using a random effects model, the meta-analysis examining the effect of Trendelenburg position, showed that intraocular pressure decreased significantly after induction and before arousal. Intraocular pressure increased significantly after abdominal insufflation and during Trendelenburg position. The meta-analysis examining the effect of prone position, showed that intraocular pressure increased significantly between induction of anesthesia and up to 10 minutes of prone position and continued to increase significantly until the end of the prone position. Conclusions. Intraocular pressure increases of the magnitude found in this research demonstrate the need for implementing interventions to reduce the risk for postoperative vision loss in patients undergoing surgery in the Trendelenburg and prone positions.


Sign in / Sign up

Export Citation Format

Share Document