Comparative performance of heterogeneity variance estimators in meta-analysis: a review of simulation studies

2016 ◽  
Vol 8 (2) ◽  
pp. 181-198 ◽  
Author(s):  
Dean Langan ◽  
Julian P. T. Higgins ◽  
Mark Simmonds
Keyword(s):  
Meta Analysis ◽  
Simulation Studies ◽  
Comparative Performance ◽  
Variance Estimators ◽  
Heterogeneity Variance

scholarly journals Performance of the ESC 0/3-hour algorithm for rapid triage of myocardial infarction: systematic review and meta-analysis

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
C Chiang ◽  
C.H Chiang ◽  
G.H Lee ◽  
C.C Lee
Keyword(s):  
Myocardial Infarction ◽  
Predictive Value ◽  
Meta Analysis ◽  
Pooled Analysis ◽  
Public Institution ◽  
Systematic Evaluation ◽  
Funding Source ◽  
Cochrane Central Register ◽  
Comparative Performance ◽  
Rule Out

Abstract Objective The European Society of Cardiology (ESC) 0/3-hour algorithm is one of the most widely strategies used for rule-out or rule-in of acute myocardial infarction (AMI). However, a systematic evaluation of its performance has not been conducted. Furthermore, recent studies showed that the 0/3-hour algorithm is non-superior to the 0/1-hour algorithm. Purpose This study aims to summarize the safety and efficacy of the 0/3-hour algorithm and its comparative performance with the 0/1-hour algorithm. Methods We conducted literature search on PubMed, Embase, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials for studies published between 1 January 2008 and 31 May 2019. A bivariate random-effects meta-analysis was used to estimate the primary and secondary outcomes, defined as index myocardial infarction and triage efficacy, major adverse cardiac event (MACE) or mortality at 30 days, respectively. Results A total of 10,832 patients from 9 studies with a pooled AMI prevalence of 16% were analyzed. The 0/3-hour algorithm ruled out 69% of the patients with a pooled sensitivity of 94.2% [95% CI: 87.6%–97.4%] and negative predictive value of 98.6% [95% CI: 97.0%–99.4%]; 17% of the patients were ruled in with a pooled specificity of 94.9% [95% CI: 88.6%–97.8%] and positive predictive value of 72.9% [95% CI: 54.6%–85.7%]. The 30-day mortality and 30-day MACE for patients that were ruled out were 0.0% [95% CI: 0.0%–0.0%] and 1.4% [95% CI: 0.9%–2.0%], respectively. In a pooled analysis of 3 cohorts, the 0/3-hour algorithm had a non-superior sensitivity compared with the 0/1-hour algorithm (94.4% [95% CI: 87.0%–97.7%] vs. 98.4% [95% CI: 95.4%–99.7%]). The 0/3-hour algorithm also had a similar rule-out efficacy compared with the 0/1-hour algorithm (52% [95% CI: 39%–65%] vs. 53% [95% CI: 42%–64%]). Conclusion The widely used 0/3-hour algorithm has sensitivity substantially below the consensus goal of 99% and may not be sufficiently safe for triage of myocardial infarction. Furthermore, the 0/3-hour algorithm is not superior to the 0/1-hour algorithm despite the additional triage time. Performance of ESC 0/3-hour algorithm Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Taiwan National Ministry of Science and Technology Grants

Bias in retrospective analyses of biomarker effect using data from an outcome-adaptive randomized trial

2019 ◽  
Vol 16 (6) ◽  
pp. 599-609 ◽  
Author(s):  
Lingyun Ji ◽  
Lisa M McShane ◽  
Mark Krailo ◽  
Richard Sposto
Keyword(s):  
Simulation Studies ◽  
Adaptive Randomization ◽  
Prognostic Effect ◽  
Variance Estimators ◽  
Oncology Research ◽  
Previously Treated Patients ◽  
Previously Treated ◽  
Effect Of Treatment ◽  
Using Data ◽  
Biased Estimates

Background/Aims Biomarker-stratified outcome-adaptive randomization trials, in which randomization probabilities depend on both biomarker value and outcomes of previously treated patients, are receiving increased attention in oncology research. Data from these trials can also form the basis of investigation of additional biomarkers that may not have been incorporated into the original trial design. In this article, we investigate the validity of a standard analytical method that utilizes data from a biomarker-stratified outcome-adaptive randomization trial to assess the effect of a newly identified biomarker on patient outcomes. Methods In the context of an ancillary biomarker study for a two-arm phase II trial with a response endpoint, we conduct analytic and simulation studies to investigate bias in estimated biomarker effects under outcome-adaptive randomization. Conditions under which bias arises and magnitude of the bias are examined in several settings. We then propose unbiased estimators of biomarker effects with appropriate variance estimators. Results We demonstrate that use of biomarker-stratified outcome-adaptive randomization perturbs the patient population and treatment assignments. Consequently, application of standard analysis methods to data from an outcome-adaptive randomization trial either to estimate prognostic effect of a new biomarker in uniformly treated patients or to estimate effect of treatment in relation to the new biomarker can lead to substantially biased estimates. The proposed adjusted estimators are asymptotically unbiased, and the proposed variance estimators correctly reflect the sample variability in the estimators. Conclusion This article demonstrates existence of bias when standard, naïve statistical methods are utilized to assess biomarker effects using data from a biomarker-stratified outcome-adaptive randomization trial, and hence that results from naïve analyses must be interpreted with great caution. These findings highlight that, in an era where data and specimens are increasingly being shared for biomarker studies, care must be taken to document and understand implications of the study design under which specimens or data have been obtained.

An empirical comparison of heterogeneity variance estimators in 12 894 meta-analyses

2015 ◽  
Vol 6 (2) ◽  
pp. 195-205 ◽  
Author(s):  
Dean Langan ◽  
Julian P. T. Higgins ◽  
Mark Simmonds
Keyword(s):  
Empirical Comparison ◽  
Variance Estimators ◽  
Heterogeneity Variance ◽  
Meta Analyses

scholarly journals Impact of Toothbrush Age on Clinical Indicators of Oral Health, a Protocol for a Systematic Review

2021 ◽  
Author(s):  
Sepideh Zayandeh ◽  
Zahra Yaghoubi ◽  
Kosar Hosseini
Keyword(s):  
Systematic Review ◽  
Oral Health ◽  
Dental Caries ◽  
Meta Analysis ◽  
Clinical Indicators ◽  
Plaque Removal ◽  
Study Selection ◽  
Manual Toothbrush ◽  
Heterogeneity Variance ◽  
The Relationship

Abstract Background: Dental caries is the most common chronic untreated disease worldwide. The simplest and most important factor in preventing dental caries is maintaining oral hygiene and removing microbial plaque using a toothbrush. Despite the relationship between toothbrush filament wear and plaque removal effectiveness as a potentially important factor in maintaining oral health, there is little objective standard evidence as to 1) what constitutes a worn-out brush and 2) the degree of loss in plaque removal effectiveness due to brush wear. Contradictions in the results of studies on toothbrushing and the loss of its effectiveness in removing plaque based on the time spent using the toothbrush have led to conflicting recommendations for changing toothbrushes after different periods. While some studies generally question the relationship between toothbrush age and effectiveness. The lack of comprehensive evidence in this area necessitates a structured review study.Methods: We will search the electronic databases ISI, Scopus, and PubMed to find related articles. Our main inclusion criterion is Clinical trial and observational studies investigating manual toothbrush longevity in the natural toothbrush-worn model on each objective indicator of oral health (including plaque removal and gingival indices ...). All funded citations are entered into the Endnote software. the full texts of potentially relevant studies are prepared. study selection and extracting the data will be performed by two reviewers. Also, the studies quality will be assessed. The findings will be displayed using figures, summary tables and narrative summaries. If the similarity of studies and their quality is desirable, meta-analysis will be performed. We will assess the heterogeneity on the bias of the magnitude of heterogeneity variance parameter. We are also going to conduct subgroup analysis and sensitivity analysis if needed.Discussion: The final systematic review highlights the gaps in the available evidence about the effectiveness of toothbrush longevity on each oral indices to provide the best recommendation for toothbrush renewal periods. Registration: The review subject has been submitted in PROSPERO database

The comparative performance of Islamic and conventional banks: a meta-analysis

2021 ◽  
Vol 8 (2/3) ◽  
pp. 199
Author(s):  
Hishamuddin Abdul Wahab ◽  
Mohammed Nur Irfan Mohammed Roslan
Keyword(s):  
Meta Analysis ◽  
Comparative Performance ◽  
Conventional Banks

Variance Estimation by Linearisation for the At Risk of Poverty or Social Exclusion (AROPE) Rate

2020 ◽  
Vol 49 (1) ◽  
pp. 33-44
Author(s):  
Stefan Zins
Keyword(s):  
At Risk ◽  
Social Exclusion ◽  
Variance Estimation ◽  
Simulation Studies ◽  
Important Indicator ◽  
Variance Estimators ◽  
Complex Sampling ◽  
Key Indicator ◽  
Complex Sampling Design ◽  
Data Source

The At Risk of Poverty or Social Exclusion (AROPE) Rate is the key indicator for monitoring the European Commissions 2020 Strategy poverty target. But the variance of the AROPE Rate is not straightforward to estimate. Re-sampling methods can be used, but they are difficult to adapt to complex sampling design, that are often used for the surveys that provide the data source for estimating the AROPER. The presented work fills a methodological gap by providing a linearisation of the AROPE Rate estimator that can be used with well known variance estimators and therefore facilitate the reporting of appropriate inference for this important indicator. The precision of the developed variance estimators based on linearisation is assessed via simulation studies and compared with a bootstrap variance estimator, as an alternative.

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