Comment on “Early Prognostic Utility of Gp210 Antibody-Positive Rate in Primary Biliary Cholangitis: A Meta-Analysis”

Background. The prevalence of primary biliary cholangitis (PBC), which is an autoimmune liver disease, has increased over time. PBC often leads to severe consequences, such as liver failure and death. Stratification tools using biochemical liver tests are needed to assess and predict the progression of this disease at the time of PBC diagnosis. Methods. We searched PubMed, Cochrane Library, Web of Science, and Embase for studies focused on the relationship between positive rates of Gp210 antibodies and poor prognosis of PBC. The primary end point was the number of PBC patients with poor outcome in the Gp210 antibody (+) and Gp210 antibody (−) groups. The secondary end point was the basic serum level of alanine aminotransferase (ALT), alkaline phosphatase (ALP), total bilirubin (TBIL), and IgM in the two groups. The age and number of female patients were also measured. Results. A total of 5 studies, comprising 737 patients, were included in this analysis. A positive rate of Gp210 antibodies was positively correlated with poor outcomes and with many types of progression in PBC, especially liver failure. Mortality was also higher in the Gp210 antibody (+) group. Furthermore, the serum levels of ALP and IgM were associated with the positive rate of Gp210 antibodies, while the serum levels of ALT and TBIL were not. The age and number of female patients were also not associated with the positive rate of Gp210 antibodies. Conclusion. PBC-specific Gp120 antibodies are optimal predictors of PBC prognosis at the time of diagnosis. Some other liver function indicators, such as ALP and IgM, can be used as predictors to complement Gp210 antibodies to establish a stratification tool to predict the prognosis of PBC at the time of diagnosis.

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Identification of and Correction for Publication Bias: Comment

10.31222/osf.io/dh87m ◽

2019 ◽

Author(s):

Amanda Kvarven ◽

Eirik Strømland ◽

Magnus Johannesson

Keyword(s):

Publication Bias ◽

False Positive ◽

Large Scale ◽

Meta Analysis ◽

False Positive Rate ◽

Effect Sizes ◽

Replication Studies ◽

Moderate Reduction ◽

Positive Rate ◽

Meta Analyses

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%.

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Replication study and meta-analysis indicate a suggestive association of RUNX3 locus with primary biliary cholangitis

Immunogenetics ◽

10.1007/s00251-020-01192-4 ◽

2020 ◽

Author(s):

Rohil Jawed ◽

Mingming Zhang ◽

Chan Wang ◽

Shu-Han Yang ◽

Peng Jiang ◽

...

Keyword(s):

Meta Analysis ◽

Replication Study ◽

Primary Biliary Cholangitis ◽

Suggestive Association

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Detection of three pandemic causing coronaviruses from non-respiratory samples: systematic review and meta-analysis

Scientific Reports ◽

10.1038/s41598-021-95329-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Chandan Mishra ◽

Suneeta Meena ◽

Jitendra Kumar Meena ◽

Suman Tiwari ◽

Purva Mathur

Keyword(s):

Systematic Review ◽

Detection Rate ◽

Meta Analysis ◽

Total Sample ◽

Urine Samples ◽

Pathogenic Potential ◽

Clinical Specimens ◽

Qrt Pcr ◽

Corona Virus ◽

Positive Rate

AbstractSARS-CoV-2 has posed an unprecedented challenge to the world. Pandemics have been caused previously by viruses of this family like Middle East Respiratory Corona Virus (MERS CoV), Severe Acute Respiratory Syndrome Corona Virus (SARS CoV). Although these viruses are primarily respiratory viruses, but they have been isolated from non-respiratory samples as well. Presently, the detection rate of SARS‐CoV‐2 RNA from different clinical specimens using Real Time Reverse Transcriptase Polymerized Chain Reaction (qRT‐PCR) after onset of symptoms is not yet well established. Therefore, the aim of this systematic review was to establish the profile of detecting SARS‐CoV‐2, MERS CoV, SARS CoV from different types of clinical specimens other than the respiratory using a standard diagnostic test (qRT‐PCR). A total of 3429 non-respiratory specimens were recorded: SARS CoV (total sample—802), MERS CoV (total sample—155), SARS CoV-2 (total sample—2347). Out of all the samples studied high positive rate was seen for saliva with 96.7% (14/14; 95% CI 87.6–100.0%) for SARS CoV and 57.5% (58/250; 95% CI − 1.2 to 116.2%) for SARS CoV-2, while low detection rate in urine samples for SARS CoV-2 with 2.2% (8/318; 95% CI 0.6–3.7%) and 9.6% (12/61; 95% CI − 0.9 to 20.1%) for SARS CoV but there was relatively higher positivity in urine samples for MERS CoV with detection rate of 32.4% (2/38; 95% CI − 37.3 to 102.1%). In Stool sample positivity was 54.9% (396/779; 95% CI 41.0–68.8%), 45.2% (180/430; 95% CI 28.1–62.3%) and 34.7% (4/38; 95% CI − 29.5 to 98.9%) for SARS CoV-2, MERS CoV, and SARS CoV, respectively. In blood sample the positivity was 33.3% (7/21; 95% CI 13.2–53.5%), 23.7% (42/277; 95% CI 10.5–36.9%) and 2.5% (2/81; 95% CI 0.00–5.8%) for MERS CoV, SARS CoV-2 and SARS CoV respectively. SARS‐CoV‐2 along with previous two pandemic causing viruses from this family, were highly detected stool and saliva. A low positive rate was recorded in blood samples. Viruses were also detected in fluids along with unusual samples like semen and vaginal secretions thus highlighting unique pathogenic potential of SARS‐CoV‐2.

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Pretherapeutic Imaging for Axillary Staging in Breast Cancer: A Systematic Review and Meta-Analysis of Ultrasound, MRI and FDG PET

Journal of Clinical Medicine ◽

10.3390/jcm10071543 ◽

2021 ◽

Vol 10 (7) ◽

pp. 1543

Author(s):

Morwenn Le Boulc’h ◽

Julia Gilhodes ◽

Zara Steinmeyer ◽

Sébastien Molière ◽

Carole Mathelin

Keyword(s):

Systematic Review ◽

Sensitivity And Specificity ◽

Meta Analysis ◽

False Negative ◽

Significant Proportion ◽

False Negative Rate ◽

True Positive Rate ◽

Axillary Staging ◽

Positron Emission ◽

Positive Rate

Background: This systematic review aimed at comparing performances of ultrasonography (US), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography (PET) for axillary staging, with a focus on micro- or micrometastases. Methods: A search for relevant studies published between January 2002 and March 2018 was conducted in MEDLINE database. Study quality was assessed using the QUality Assessment of Diagnostic Accuracy Studies checklist. Sensitivity and specificity were meta-analyzed using a bivariate random effects approach; Results: Across 62 studies (n = 10,374 patients), sensitivity and specificity to detect metastatic ALN were, respectively, 51% (95% CI: 43–59%) and 100% (95% CI: 99–100%) for US, 83% (95% CI: 72–91%) and 85% (95% CI: 72–92%) for MRI, and 49% (95% CI: 39–59%) and 94% (95% CI: 91–96%) for PET. Interestingly, US detects a significant proportion of macrometastases (false negative rate was 0.28 (0.22, 0.34) for more than 2 metastatic ALN and 0.96 (0.86, 0.99) for micrometastases). In contrast, PET tends to detect a significant proportion of micrometastases (true positive rate = 0.41 (0.29, 0.54)). Data are not available for MRI. Conclusions: In comparison with MRI and PET Fluorodeoxyglucose (FDG), US is an effective technique for axillary triage, especially to detect high metastatic burden without upstaging majority of micrometastases.

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Estimating the statistical performance of different approaches to meta-analysis of data from animal studies in identifying the impact of aspects of study design

10.1101/256776 ◽

2018 ◽

Cited By ~ 4

Author(s):

Qianying Wang ◽

Jing Liao ◽

Kaitlyn Hair ◽

Alexandra Bannach-Brown ◽

Zsanett Bahor ◽

...

Keyword(s):

Effect Size ◽

False Positive ◽

Latent Variable ◽

Statistical Power ◽

Animal Studies ◽

Meta Analysis ◽

False Positive Rate ◽

Mean Difference ◽

Positive Rate ◽

Meta Regression

AbstractBackgroundMeta-analysis is increasingly used to summarise the findings identified in systematic reviews of animal studies modelling human disease. Such reviews typically identify a large number of individually small studies, testing efficacy under a variety of conditions. This leads to substantial heterogeneity, and identifying potential sources of this heterogeneity is an important function of such analyses. However, the statistical performance of different approaches (normalised compared with standardised mean difference estimates of effect size; stratified meta-analysis compared with meta-regression) is not known.MethodsUsing data from 3116 experiments in focal cerebral ischaemia to construct a linear model predicting observed improvement in outcome contingent on 25 independent variables. We used stochastic simulation to attribute these variables to simulated studies according to their prevalence. To ascertain the ability to detect an effect of a given variable we introduced in addition this “variable of interest” of given prevalence and effect. To establish any impact of a latent variable on the apparent influence of the variable of interest we also introduced a “latent confounding variable” with given prevalence and effect, and allowed the prevalence of the variable of interest to be different in the presence and absence of the latent variable.ResultsGenerally, the normalised mean difference (NMD) approach had higher statistical power than the standardised mean difference (SMD) approach. Even when the effect size and the number of studies contributing to the meta-analysis was small, there was good statistical power to detect the overall effect, with a low false positive rate. For detecting an effect of the variable of interest, stratified meta-analysis was associated with a substantial false positive rate with NMD estimates of effect size, while using an SMD estimate of effect size had very low statistical power. Univariate and multivariable meta-regression performed substantially better, with low false positive rate for both NMD and SMD approaches; power was higher for NMD than for SMD. The presence or absence of a latent confounding variables only introduced an apparent effect of the variable of interest when there was substantial asymmetry in the prevalence of the variable of interest in the presence or absence of the confounding variable.ConclusionsIn meta-analysis of data from animal studies, NMD estimates of effect size should be used in preference to SMD estimates, and meta-regression should, where possible, be chosen over stratified meta-analysis. The power to detect the influence of the variable of interest depends on the effect of the variable of interest and its prevalence, but unless effects are very large adequate power is only achieved once at least 100 experiments are included in the meta-analysis.

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