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      Genetic association between interluekin-4 rs2243250 polymorphism and gastric cancer susceptibility: evidence based on a meta-analysis

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          Abstract

          Purpose

          Numerous studies have suggested that the interleukin-4 ( IL-4) rs2243250 polymorphism is associated with gastric cancer susceptibility. However, the results were inconsistent. Hence, we carried out a meta-analysis to confirm the conclusion.

          Methods

          We searched PubMed, Embase, CBM, CNKI, and Wanfang Data to identify relevant studies up to August 20, 2015. Odds ratio (OR) and 95% confidence interval (CI) were used to estimate the association between IL-4 rs2243250 polymorphism and gastric cancer susceptibility. All the statistical analyses were performed with Stata 12.0 software.

          Results

          A total of eleven published case–control studies were identified, including 2,247 gastric cancer patients and 3,370 controls. Overall, no significant association between IL-4 rs2243250 polymorphism and gastric cancer susceptibility was observed in this meta-analysis (T vs C: OR =1.05, 95% CI =0.95–1.17; TT vs CC: OR =1.20, 95% CI =0.89–1.63; CT vs CC: OR =1.14, 95% CI =0.87–1.48; TT + CT vs CC: OR =1.13, 95% CI =0.89–1.44; TT vs CT + CC: OR =1.02, 95% CI =0.88–1.20). Similar results were found in subgroup analyses according to ethnicity and Hardy–Weinberg equilibrium in controls.

          Conclusion

          This meta-analysis suggests that IL-4 rs2243250 polymorphism may not be associated with gastric cancer susceptibility. Further studies are needed to validate this conclusion.

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          Most cited references 33

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          Estimates of the worldwide incidence and mortality from 27 major cancers and for all cancers combined for 2012 are now available in the GLOBOCAN series of the International Agency for Research on Cancer. We review the sources and methods used in compiling the national cancer incidence and mortality estimates, and briefly describe the key results by cancer site and in 20 large "areas" of the world. Overall, there were 14.1 million new cases and 8.2 million deaths in 2012. The most commonly diagnosed cancers were lung (1.82 million), breast (1.67 million), and colorectal (1.36 million); the most common causes of cancer death were lung cancer (1.6 million deaths), liver cancer (745,000 deaths), and stomach cancer (723,000 deaths). © 2014 UICC.
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            The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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              Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews. Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution.
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                Author and article information

                Journal
                Onco Targets Ther
                Onco Targets Ther
                OncoTargets and Therapy
                OncoTargets and therapy
                Dove Medical Press
                1178-6930
                2016
                20 April 2016
                : 9
                : 2403-2408
                ott-9-2403
                10.2147/OTT.S104181
                4844435
                27143935
                © 2016 Zhang et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Oncology & Radiotherapy

                stomach neoplasms, genetic, polymorphism, meta-analysis, interleukin-4

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