CD34+ CD133+ CD309+ circulating angiogenic cell level is reduced but positively related to hydroxychloroquine use in SLE patients – a case-control study and meta-regression analysis

Rheumatology ◽  
2020 ◽  
Author(s):  
Jinghui Huang ◽  
Nien Yee Kow ◽  
Hui Yin Lee ◽  
Anna-Marie Fairhurst ◽  
Anselm Mak
Keyword(s):  
Regression Analysis ◽  
Lupus Erythematosus ◽  
Statistical Power ◽  
Mixed Model ◽  
Mononuclear Cells ◽  
Case Control ◽  
Case Control Studies ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Meta Analyses

Abstract Objectives To identify and quantify the level of CD34+ CD133+ CD309+ circulating angiogenic cells (CAC) and explore factors associated with the level of CAC in patients with systemic lupus erythematosus (SLE). Methods The peripheral blood mononuclear cells of consecutive SLE patients and demographically matched healthy controls (HC) were extracted and identified, enumerated and compared for CAC levels by multi-colour flow cytometry based on the European League Against Rheumatism Scleroderma Trials and Research (EUSTAR) recommendation. Meta-analyses by combining the current and previous case-control studies were performed, aiming to increase the statistical power to discern the difference in CAC level between SLE patients and HC. Mixed-model meta-regression was conducted to explore potential demographic and clinical factors which were associated with CAC level. Results A lower level of CAC was found in 29 SLE patients compared with 24 HC (10.76 ± 13.9 vs 24.58 ± 25.4 cells/ml, p= 0.015). Random-effects meta-analyses of the current and 6 previously published case-control studies involving 401 SLE patients and 228 HC revealed a lower CAC level compared with HC (SMD= -2.439, p= 0.001). Meta-regression analysis demonstrated that hydroxychloroquine use was associated with a more discrepant CAC level between both groups (p= 0.01115). Conclusion SLE patients had a significantly lower CD34+ CD133+ CD309+ CAC level than HC and hydroxychloroquine use was associated with a more discrepant CAC level between SLE patients and HC. This study triggers further observational, interventional and mechanistic studies to address the beneficial impact of hydroxychloroquine on the functionality of CAC in SLE patients.

scholarly journals Panel Stratification in Meta-Analysis of Economic Studies: An Investigation of Its Effects in the Recreation Valuation Literature

2000 ◽  
Vol 32 (3) ◽  
pp. 459-470 ◽  
Author(s):  
Randall S. Rosenberger ◽  
John B. Loomis
Keyword(s):  
Regression Analysis ◽  
Literature Review ◽  
Outdoor Recreation ◽  
Meta Analysis ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Panel Effects ◽  
Meta Analyses ◽  
Insight Into ◽  
Economic Studies

AbstractStatistical summarizations of literature review databases using meta-regression analysis provide insight into the differences in past estimates of economic variables such as benefits and price elasticities. The panel nature of the data is an issue that has not received adequate attention in past meta-analyses. This paper conceptually and empirically explores the complexity of stratifying data into panels that model the potential correlation and heterogeneity of past outdoor recreation benefit research. Although our tests of three stratifications of the data did not discern panel effects, the inherent complexity of the data maintains a strong presumption of heterogeneous strata.

scholarly journals Therapeutic efficacy of direct oral anticoagulants and vitamin K antagonists for left ventricular thrombus: Systematic review and meta-analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255280
Author(s):  
Tetsuji Kitano ◽  
Yosuke Nabeshima ◽  
Masaharu Kataoka ◽  
Masaaki Takeuchi
Keyword(s):  
Regression Analysis ◽  
Major Bleeding ◽  
Vitamin K Antagonists ◽  
Oral Anticoagulants ◽  
Direct Oral Anticoagulants ◽  
Left Ventricular ◽  
Ventricular Thrombus ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Meta Analyses

Background Although several meta-analyses have compared efficacies of vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs) for treatment of left ventricular thrombus (LVT), those meta-analyses included no single-arm studies. Methods and results PubMed, Scopus, and the Cochrane Library databases were searched for articles investigating thrombus resolution, stroke, any thromboembolism, major bleeding, any bleeding, or all-cause death in LVT treated with VKAs or DOACs, and single-class meta-analyses were also included (PROSPERO database, CRD42021230849). Event rates were pooled using a random effects model. Meta-regression analysis was performed to explore factors that may influence outcomes. 2,612 patients from 23 articles were included (VKAs: 2,004, DOACs: 608). There were no significant differences between VKAs and DOACs in the frequency of thrombus resolution (VKAs: 0.75 [95% confidence interval; 0.67 to 0.81], DOACs: 0.75 [0.67 to 0.82]), stroke (VKAs: 0.06 [0.04 to 0.10], DOACs: 0.02 [0.01 to 0.01]), any thromboembolism (VKAs: 0.08 [0.05 to 0.13], DOACs: 0.03 [0.01 to 0.10]), major bleeding (VKAs: 0.06 [0.04 to 0.09], DOACs: 0.03 [0.01 to 0.06]), any bleeding (VKAs: 0.08 [0.05 to 0.12], DOACs: 0.08 [0.06 to 0.10]), and all-cause death (VKAs: 0.07 [0.04 to 0.13], DOACs: 0.09 [0.05 to 0.16]). Meta-regression analysis revealed that increased duration of follow-up was associated with lower-rates of stroke (estimate: -0.040, p = 0.0495) with VKAs, but not with DOACs. There was significant publication bias for thrombus resolution, stroke, any thromboembolism, any bleeding, and all-cause death. Conclusions Efficacy and adverse outcomes of therapy with DOACs and VKAs do not differ. Randomized controlled trials are needed to determine the optimal anticoagulant strategy.

scholarly journals Most published meta-regression analyses based on aggregate data suffer from methodological pitfalls: a meta-epidemiological study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Michael Geissbühler ◽  
Cesar A. Hincapié ◽  
Soheila Aghlmandi ◽  
Marcel Zwahlen ◽  
Peter Jüni ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Epidemiological Study ◽  
Treatment Effects ◽  
Aggregate Data ◽  
Ecological Fallacy ◽  
Regression Analyses ◽  
Aggregated Data ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Meta Analyses

Abstract Background Due to clinical and methodological diversity, clinical studies included in meta-analyses often differ in ways that lead to differences in treatment effects across studies. Meta-regression analysis is generally recommended to explore associations between study-level characteristics and treatment effect, however, three key pitfalls of meta-regression may lead to invalid conclusions. Our aims were to determine the frequency of these three pitfalls of meta-regression analyses, examine characteristics associated with the occurrence of these pitfalls, and explore changes between 2002 and 2012. Methods A meta-epidemiological study of studies including aggregate data meta-regression analysis in the years 2002 and 2012. We assessed the prevalence of meta-regression analyses with at least 1 of 3 pitfalls: ecological fallacy, overfitting, and inappropriate methods to regress treatment effects against the risk of the analysed outcome. We used logistic regression to investigate study characteristics associated with pitfalls and examined differences between 2002 and 2012. Results Our search yielded 580 studies with meta-analyses, of which 81 included meta-regression analyses with aggregated data. 57 meta-regression analyses were found to contain at least one pitfall (70%): 53 were susceptible to ecological fallacy (65%), 14 had a risk of overfitting (17%), and 5 inappropriately regressed treatment effects against the risk of the analysed outcome (6%). We found no difference in the prevalence of meta-regression analyses with methodological pitfalls between 2002 and 2012, nor any study-level characteristic that was clearly associated with the occurrence of any of the pitfalls. Conclusion The majority of meta-regression analyses based on aggregate data contain methodological pitfalls that may result in misleading findings.

scholarly journals Mixed Models for Meta-Analysis and Sequencing

2015 ◽  
Author(s):  
Brendan Bulik-Sullivan
Keyword(s):  
Mixed Models ◽  
Mixed Model ◽  
Association Studies ◽  
Meta Analysis ◽  
Computational Cost ◽  
Case Control ◽  
Effective Sample Size ◽  
Case Control Studies ◽  
Individual Level ◽  
Meta Analyses

Mixed models are an effective statistical method for increasing power and avoiding confounding in genetic association studies. Existing mixed model methods have been designed for ``pooled'' studies where all individual-level genotype and phenotype data are simultaneously visible to a single analyst. Many studies follow a ``meta-analysis'' design, wherein a large number of independent cohorts share only summary statistics with a central meta-analysis group, and no one person can view individual-level data for more than a small fraction of the total sample. When using linear regression for GWAS, there is no difference in power between pooled studies and meta-analyses \cite{lin2010meta}; however, we show that when using mixed models, standard meta-analysis is much less powerful than mixed model association on a pooled study of equal size. We describe a method that allows meta-analyses to capture almost all of the power available to mixed model association on a pooled study without sharing individual-level genotype data. The added computational cost and analytical complexity of this method is minimal, but the increase in power can be large: based on the predictive performance of polygenic scoring reported in \cite{wood2014defining} and \cite{locke2015genetic}, we estimate that the next height and BMI studies could see increases in effective sample size of $\approx$15\% and $\approx$8\%, respectively. Last, we describe how a related technique can be used to increase power in sequencing, targeted sequencing and exome array studies. Note that these techniques are presently only applicable to randomly ascertained studies and will sometimes result in loss of power in ascertained case/control studies. We are developing similar methods for case/control studies, but this is more complicated.

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