• Journal of Korean Academy of Nursing
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• v.43 no.6
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• pp.736-745
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• 2013

Purpose: The purpose of the study was to assess the quality of meta-analyses on nursing published in South Korea. Methods: Relevant meta-analyses were identified through searches of the National Assembly Library, KISS (Korean Studies Information Service System), and the DBpia and RISS4U databases from 1990 to May 2013. Quality assessments were conducted using AMSTAR, a validated tool for assessing the quality of systematic reviews. Results: Forty-two meta-analyses were included in this study. Twenty-nine published between 1990 and 2010, and 13, between 2011 and May 2013. Two high quality studies and 11 moderate quality studies were published in the latter period. The mean score for the reviews was 5.61 (range 3-10); 11 studies were rated as low quality, 29 as moderate quality, and two as high quality. Conclusion: Although an improvement in the quality of meta-analyses conducted by nursing researchers in South Korea was observed across the study period, the study results indicate a need to use of more rigorous research methods when conducting systematic reviews or meta-analyses.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3109-3112
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• 2012

Background: Many studies have focused on possible associations between the glutathione S-transferase M 1 (GSTM1) null genotype and risk of renal cell carcinoma (RCC), but the impact remains unclear owing to obvious inconsistencies among the findings. The present study aimed to quantify the strength of any association in a meta-analysis. Methods: We searched the PubMed, Embase and CBM databases for studies concerning the association between the GSTM1 null genotype and risk of RCC. We estimated the summary odds ratio (OR) with its 95% confidence intervals (95% CI) to assess the association. Results: The meta-analysis showed the GSTM1 null genotype was not associated with risk of RCC overall (OR = 1.04, 95% CI 0.92-1.18, P = 0.501). For Caucasians, the GSTM1 null genotype was also not associated with risk of RCC (OR=1.02, 95% CI 0.90-1.16, P = 0.761). The cumulative meta-analyses showed a trend of no obvious association between GSTM1 null genotype and risk of RCC as information accumulated. Sensitivity analyses by omitting those studies also did not materially alter the overall combined ORs. No evidence of publication bias was observed. Conclusion: Meta-analyses of available data show that the GSTM1 null genotype is not significantly associated with risk of renal cell carcinoma.

• Korean Journal of Applied Biomechanics
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• v.32 no.2
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• pp.56-68
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• 2022

Objective: The purpose of this systematic review and meta-analysis was to investigate potential effects of HRT (hormone replacement therapy) on motor functions in postmenopausal women. Method: In this meta-analysis, 19 studies that examined changes in motor functions between postmenopausal women with and without HRT intervention were qualified. We additionally conducted moderator variable analyses including: (1) motor function type, (2) hormone type, and (3) duration of HRT intervention. Results: The random effects model showed no significant overall effects (SMD = 0.199; SE = 0.115; 95% CI = -0.026~0.425; Z = 1.730; p = 0.084; I² = 93.258%). Additional three moderator variable analyses revealed no significant effect sizes indicating that specific HRT protocols did not improve different motor functions in postmenopausal women. Conclusion: These meta-analytic findings suggest that HRT had no positive effects on motor functions in postmenopausal women.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.355-369
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• 2022

Objective: To evaluate the completeness of the reporting of systematic reviews and meta-analyses published in a general radiology journal using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Materials and Methods: Twenty-four articles (systematic review and meta-analysis, n = 18; systematic review only, n = 6) published between August 2009 and September 2021 in the Korean Journal of Radiology were analyzed. Completeness of the reporting of main texts and abstracts were evaluated using the PRISMA 2020 statement. For each item in the statement, the proportion of studies that met the guidelines' recommendation was calculated and items that were satisfied by fewer than 80% of the studies were identified. The review process was conducted by two independent reviewers. Results: Of the 42 items (including sub-items) in the PRISMA 2020 statement for main text, 24 were satisfied by fewer than 80% of the included articles. The 24 items were grouped into eight domains: 1) assessment of the eligibility of potential articles, 2) assessment of the risk of bias, 3) synthesis of results, 4) additional analysis of study heterogeneity, 5) assessment of non-reporting bias, 6) assessment of the certainty of evidence, 7) provision of limitations of the study, and 8) additional information, such as protocol registration. Of the 12 items in the abstract checklists, eight were incorporated in fewer than 80% of the included publications. Conclusion: Several items included in the PRISMA 2020 checklist were overlooked in systematic review and meta-analysis articles published in the Korean Journal of Radiology. Based on these results, we suggest a double-check list for improving the quality of systematic reviews and meta-analyses. Authors and reviewers should familiarize themselves with the PRISMA 2020 statement and check whether the recommended items are fully satisfied prior to publication.

• Clinical and Experimental Pediatrics
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• v.64 no.5
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• pp.208-222
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• 2021

The publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, since most claimed candidate gene associations were false-positives, correctly interpreting the published results is important. In this review, we emphasize the importance of interpreting the results of genetic epidemiology meta-analyses using Bayesian statistics and gene network analysis, which could be applied in other diseases.

• Journal of Ginseng Research
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• v.40 no.3
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• pp.269-277
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• 2016

Background: The findings of currently available studies are not consistent with regard to the association between the risk of cancer and ginseng consumption. Therefore, we aimed to evaluate this association by conducting a meta-analysis of different studies. Methods: To systematically evaluate the effect of ginseng consumption on cancer incidence, six databases were searched, including PubMed, Ovid Technologies, Embase, The Cochrane Library, China National Knowledge Infrastructure, and Chinese VIP Information, from 1990 to 2014. Statistical analyses based on the protocol employed for a systematic review were conducted to calculate the summary relative risks (RRs) and 95% confidence intervals (CIs). Results: We identified nine studies, including five cohort studies, three case-control studies, and one randomized controlled trial, evaluating the association between ginseng consumption and cancer risk; these studies involved 7,436 cases and 334,544 participants. The data from the meta-analysis indicated a significant 16% lower risk of developing cancer in patients who consumed ginseng (RR = 0.84, 95% CI = 0.76-0.92), with evidence of heterogeneity (p = 0.0007, $I^2$ = 70%). Stratified analyses suggested that the significant heterogeneity may result from the incidence data for gastric cancer that were included in this study. Publication bias also showed the same result as the stratified analyses. In addition, subgroup analyses for four specific types of cancer (colorectal cancer, lung cancer, gastric cancer, and liver cancer) were also performed. The summary RRs for ginseng intake versus no ginseng consumption were 0.77 for lung cancer, 0.83 for gastric cancer, 0.81 for liver cancer, and 0.77 for colorectal cancer. Conclusion: The findings of this meta-analysis indicated that ginseng consumption is associated with a significantly decreased risk of cancer and that the effect is not organ specific.

• Genomics & Informatics
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• v.20 no.4
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• pp.49.1-49.7
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• 2022

Many packages for a meta-analysis of genome-wide association studies (GWAS) have been developed to discover genetic variants. Although variations across studies must be considered, there are not many currently-accessible packages that estimate between-study heterogeneity. Thus, we propose a python based application called Beta-Meta which can easily process a meta-analysis by automatically selecting between a fixed effects and a random effects model based on heterogeneity. Beta-Meta implements flexible input data manipulation to allow multiple meta-analyses of different genotype-phenotype associations in a single process. It provides a step-by-step meta-analysis of GWAS for each association in the following order: heterogeneity test, two different calculations of an effect size and a p-value based on heterogeneity, and the Benjamini-Hochberg p-value adjustment. These methods enable users to validate the results of individual studies with greater statistical power and better estimation precision. We elaborate on these and illustrate them with examples from several studies of infertility-related disorders.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.111-115
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• 2012

Variants of X-ray repair cross-complementing group 1 (XRCC1) are involved in the development of cancer, but studies investigating the association of XRCC1-77T>C polymorphism with cancer risk have reported conflicting results. To clarify the effect of the XRCC1 -77T>C polymorphism on cancer risk, we performed a meta-analysis by conducting searches of the published literature in PubMed, Embase and CBM databases. Finally, 13 studies were included into our meta-analysis, involving a total of 11, 678 individuals. Subgroup analyses were performed by ethnicity and cancer type. The results of this meta-analysis showed that there was significant association between the C variant of XRCC1-77T>C polymorphism and cancer risk in all four genetic comparison models (ORC vs. T =1.19, 95%CI 1.07-1.31, P = 0.001; OR homozygote model =1.28, 95%CI 1.07-1.52, P = 0.007; OR recessive genetic model =1.22, 95%CI 1.04-1.44, P = 0.015; OR dominant model =1.21, 95% CI 1.07-1.35, P = 0.001). In the subgroup analyses based on ethnicity, the association was still significant in the Asian population (all p values<0.001), but not in the Caucasian population (all p values > 0.05). Thus, the XRCC1 -77T>C polymorphism is associated with cancer risk, and individuals with XRCC1 -77C variant have a significantly higher cancer risk, particularly in the Asian population.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.3
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• pp.915-921
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• 2012

Background: Previous studies investigating the association between TP53 Arg72Pro polymorphism and gastric cancer (GC) risk in Asian population have reported controversial results. Thus, a meta-analysis was performed. Methods: A comprehensive literature search was conducted and 17 case-control studies were finally included, involving a total of 5,990 GC cases and 6,812 controls. Subgroup analyses were performed by the sample size. Results: Meta-analysis of all 17 studies showed variant genotypes of TP53 Arg72Pro to be associated with an elevated GC risk in three genetic comparison models ($OR_{Pro\;vs.\;Arg}$=1.13, 95%CI 1.03-1.25, $P_{OR}$=0.01; $OR_{Homozygote\;comparison\;model}$=1.33, 95%CI 1.07-1.64, $P_{OR}$=0.009; $OR_{Dominant\;genetic\;model}$=1.13, 95%CI 1.05-1.22, $P_{OR}$=0.002). Besides, a more obvious association was observed after the heterogeneity was decreased (all P values less than 0.001). This association was further identified by both subgroup and sensitivity analyses. Conclusions: This meta-analysis suggests the Pro variant of TP53 Arg72Pro contributes to gastric cancer risk in Asians.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.23
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• pp.10175-10179
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• 2015

Background: The association between the RTEL1 rs6010620 single nucleotide polymorphism (SNP) and glioma risk has been extensively studied. However, the results remain inconclusive. To further examine this association, we performed a meta-analysis. Materials and Methods: A computerized search of the PubMed and Embase databases for publications regarding the RTEL1 rs6010620 polymorphism and glioma cancer risk was performed. Genotype data were analyzed in a meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analyses, tests of heterogeneity, cumulative meta-analyses, and assessments of bias were performed in our meta-analysis. Results: Our meta-analysis confirmed that risk with allele A is lower than with allele G for glioma. The A allele of rs6010620 in RTEL1 decreased the risk of developing glioma in the 12 case-control studies for all genetic models: the allele model (OR=0.752, 95%CI: 0.715-0.792), the dominant model (OR=0.729, 95%CI: 0.685-0.776), the recessive model (OR=0.647, 95%CI: 0.569-0.734), the homozygote comparison (OR=0.528, 95%CI: 0.456-0.612), and the heterozygote comparison (OR=0.761, 95%CI: 0.713-0.812). Conclusions: In all genetic models, the association between the RTEL1 rs6010620 polymorphism and glioma risk was significant. This meta-analysis suggests that the RTEL1 rs6010620 polymorphism may be a risk factor for glioma. Further functional studies evaluating this polymorphism and glioma risk are warranted.