Abstract The gene coding interleukin 6 ( IL‐6 ) is a promising candidate in predisposition to type 2 diabetes mellitus (T2DM). This study aimed to meta‐analytically examine the association of IL‐6 gene −174G/C polymorphism with T2DM and circulating IL‐6 changes across −174G/C genotypes. Odds ratio (OR) and standard mean difference (SMD) with 95% confidence interval (CI) were calculated. Twenty‐five articles were meta‐analysed, with 20 articles for T2DM risk and 9 articles for circulating IL‐6 changes. Overall, there was no detectable significance for the association between −174G/C polymorphism and T2DM, and this association was relatively obvious under dominant model (OR: 0.82, 95% CI: 0.56‐1.21). Improved heterogeneity was seen in some subgroups, with statistical significance found in studies involving subjects of mixed races (OR: 0.63, 95% CI: 0.46‐0.86). Begg's and filled funnel plots, along with Egger's tests revealed week evidence of publication bias. In genotype‐phenotype analyses, carriers of −174CC and −174CG genotypes separately had 0.10 and 0.03 lower concentrations (pg/mL) of circulating IL‐6 than −174GG carriers. Albeit no detectable significance for the association of −174G/C with T2DM, our findings provided suggestive evidence on a dose‐dependent relation between −174G/C mutant alleles and circulating IL‐6 concentrations, indicating possible implication of this polymorphism in the pathogenesis of T2DM.
We did a systematic review and meta-analysis, aiming to examine the association of available polymorphisms in the receptor for advanced glycation end products (AGER) gene with the risk of type 2 diabetes. Literature search, eligibility assessment, and data extraction were independently performed by two authors. Risk was expressed as by odds ratio (OR) and 95% confidence interval (CI) under the random-effects model. A total of 26 publications, involving 29 independent studies (8,318 patients with type 2 diabetes and 5,589 healthy or orthoglycemic controls) were included in this meta-analysis. Six polymorphisms in AGER gene, rs2070600, rs1800624, rs1800625, rs184003, rs3134940, and rs55640627, were eligible for inclusion. Overall analyses indicated that the mutations of rs1800624 (–374A) and rs55640627 (2245A) were associated with a significantly increased risk of type 2 diabetes (OR = 1.17 and 1.55, 95% CI: 1.00 to 1.38 and 1.21 to 1.98, respectively). Subsidiary analyses revealed that the mutation of rs2070600 was associated with 2.13-folded increased risk of type 2 diabetes in Caucasians (95% CI: 1.28 to 3.55), and the mutation of rs1800624 was associated with 1.57-folded increased risk in South Asians (95% CI: 1.09 to 2.25), with no evidence of heterogeneity (I2: 42.5% and 44.5%). There were low probabilities of publication bias for all studied polymorphisms. Taken together, our findings indicate an ethnicity-dependent contribution of AGER gene in the pathogenesis of type 2 diabetes, that is, rs2070600 was a susceptibility locus in Caucasians, yet rs1800624 in South Asians.
Axillary lymph node metastasis (ALNM) is commonly the earliest detectable clinical manifestation of breast cancer when distant metastasis emerges. This study aimed to explore the influencing factors of ALNM and develop models that can predict its occurrence preoperatively.Cases of sonographically visible clinical stage T1-2N0M0 breast cancers treated with breast and axillary surgery at West China Hospital were retrospectively reviewed. Univariate and multivariate logistic regression analyses were performed to evaluate associations between ALNM and variables. Decision tree analyses were performed to construct predictive models using the C5.0 packages.Of the 1671 tumors, 541 (32.9%) showed axillary lymph node positivity on final surgical histopathologic analysis. In multivariate logistic regression analysis, tumor size (P < .001), infiltration of subcutaneous adipose tissue (P < .001), infiltration of the interstitial adipose tissue (P = .031), and tumor quadrant locations (P < .001) were significantly correlated with ALNM. Furthermore, the accuracy in the decision tree model was 69.52%, and the false-negative rate (FNR) was 74.18%. By using the error-cost matrix algorithm, the FNR significantly decreased to 14.75%, particularly for nodes 5, 8, and 13 (FNR: 11.4%, 9.09%, and 14.29% in the training set and 18.1%,14.71%, and 20% in the test set, respectively).In summary, our study demonstrated that tumor lesion boundary, tumor size, and tumor quadrant locations were the most important factors affecting ALNM in cT1-2N0M0 stage breast cancer. The decision tree built using these variables reached a slightly higher FNR than sentinel lymph node dissection in predicting ALNM in some selected patients.
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