Many studies have analyzed the association between peptidylarginine deiminase 4 (PADI4) -104C/T polymorphism and rheumatoid arthritis (RA). However, the results are inconsistent. This meta-analysis, based on different populations, updated and reevaluated the possible associations between PADI4 -104C/T polymorphism and the susceptibility to RA.A literature search was performed on PubMed and related Chinese databases up to April 2017. The association between PADI4 -104C/T polymorphism and RA risk was evaluated by calculating pooled odds ratios (ORs) and 95% confidence intervals (CIs).A total of seventeen studies, including 5,756 RA cases and 4,987 controls, were screened out. In the overall population, PADI -104C/T polymorphism was significantly associated with an increased RA risk. In this meta-analysis stratified by ethnicity, a significant association between PADI -104C/T polymorphism and RA risk was established in China and Japan.Our study indicated a significantly increased association between PADI -104C/T polymorphism and RA in Chinese and Japanese populations. Because most included populations in this meta-analysis were Asian, further studies are needed to elucidate whether the PADI4 -104C/T gene confers RA in other ethnic groups. Rheumatoid arthritis (RA) is the most common disease of joints in adults around the world. In the United States, approximately 2.1 million people suffered from RA, which is expected to double in the next 20 years . GeneticAll studies that investigated the association between PADI4-104C/T polymorphism and RA published before April 2017 were considered for inclusion in the meta-analysis. PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure, and Chinese Biology Medicine databases were used for the literature search. The search keywords were (PADI4 or peptidylarginine deiminase 4 or -104C/T) and rheumatoid arthritis. No restrictions were placed on language, race, ethnicity, or geographic area. All references cited in the studies were also reviewed to identify additional published work not indexed by these databases. The following inclusion criteria were employed: (1) studies describing the association between PADI4 -104C/T polymorphism and RA; (2) sufficient genetypes data to calculate the odds ratio (OR). Exclusion criteria were defined as follows: (1) studies contained incomplete data, (2) case reports, (3) editorial articles, and (4) review articles and metting abstracts.Information was carefully extracted from all eligible publications independently by two authors (Hua J and Huang WJ) according to the inclusion criteria. The titles and abstracts of all potentially relevant articles were initially screened. Full articles were then scrutinized if the title and abstract were ambiguous. Disagreements were resolved through a discussion between the two authors. The following data were extracted from each study: first author’s name, publication year, ethnicity, sample size, and available genotype information with PADI4 -104C/T polymorphism.P-value less than 0.05 was considered statistically significant.The association between PADI4 -104C/T polymorphism and RA risk was evaluated by calculating pooled odds ratios (ORs) and 95% confidence intervals (CIs). The meta-analysis examined the overall association of the T allele with RA risk relative to the C allele; the differences between homozygotes TT and CC, between TT and (TC + CC), and between (TT + TC) and CC were also evaluated. The heterogeneity test and Hardy-Weinberg equilibrium (HWE) expectations in the controls were assessed by Chi-square-based Q-test. In the cases with no obvious heterogeneity between studies, OR was pooled using the fixed-effects model. Otherwise, the random-effects model was used. We compared the consistency between the fixed-effects and random-effects model to assess sensitivity analysis. Funnel plot was used to assess the potential publication bias, and the Egger’s test was applied to evaluate the funnel plot asymmetry. All statistical analyses were conducted using Stata, version 12 . A Fig 1. In total, 5,756 RA cases and 4,987 controls were included in this meta-analysis. All RA patients in each study were diagnosed by the classification criteria proposed by the American College of Rheumatology for RA in 1987. Six ethnic groups, including Chinese, Japanese, British (UK), Spanish, Hungarians, and Iranians, were included in our research. Pooled analysis was not performed for the Spanish, Hungarians, and Iranians due to the presence of only one study for each of them. The characteristics of the included studies are listed in Table 1.Two hundred and sixty-six records were identified through the database search. Based on the inclusion and exclusion criteria, seventeen studies –20 were The primary results of this meta-analysis concerning the association between PADI -104C/T polymorphism and RA risk are presented in Ten studies, including 2,119 cases and 1,962 controls, identified an association between the PADI -104C/T polymorphism and RA risk in China –13,14, aTwo studies determined the relationship between PADI -104C/T polymorphism and RA risk in UK –17. The Table 2). The Begg’s funnel plot and Egger’s test were used to evaluate the publication bias in this meta-analysis. As can be seen in P = 0.984, To evaluate the sensitivity of this meta-analysis, we compared the consistency between the fixed-effects model and the random-effects model. The results were not materially altered, which suggests that the data in this meta-analysis were stable and reliable Click here for additional data file.S2 File(DOC)Click here for additional data file.


Study-specific relative risks (RRs) with corresponding 95% confidence interval (CI) from individual studies were pooled by using random- or fixed- model, and heterogeneity and publication bias analyses were conducted.Epidemiological studies have reported inconsistent findings on the association between dietary nitrate and nitrite intake and cancer risk. We performed a meta-analysis of epidemiological studies to summarize available evidence on the association between dietary nitrate and nitrite intake and cancer risk from published prospective and case-control studies. PubMed database was searched to identify eligible publications through April 302I = 42.3%). In contrast, dietary nitrite intake was positively associated with adult glioma and thyroid cancer risk with pooled RR of 1.21 (95%CI = 1.03-1.42) and 1.52 (95%CI = 1.12-2.05), respectively. No significant associations were found between dietary nitrate/nitrite and cancers of the breast, bladder, colorectal, esophagus, renal cell, non-Hodgkin lymphoma, ovarian, and pancreas. The present meta-analysis provided modest evidence that positive associations of dietary nitrate and negative associations of dietary nitrite with certain cancers.Data from 62 observational studies, 49 studies for nitrates and 51 studies for nitrites, including a total of 60,627 cancer cases were analyzed. Comparing the highest vs. lowest levels, dietary nitrate intake was inversely associated with gastric cancer risk  with moderate heterogeneity ( Nitrate and nitrite from food and water are precursors of endogenously formed N-nitroso compounds (NOCs). Results from animal studies and mechanisms describing DNA damage suggest that these compounds are carcinogenic in humans , 2. Ingeth, 2016 to summarize available evidence on the association between both dietary nitrate and nitrite intake and cancer risk.Literature of dietary nitrate/nitrite and cancer risk has been growing but results have been inconsistent. The discrepancy might be partly due to differences in study populations and design, and partly due to the insufficient statistical power of individual studies. Therefore, we conducted a meta-analysis of all observational studies published between the dates of database inception and April 30Figure Characteristics of the 62 included articles are shown in Table Among the included prospective studies, one article consisted of 3 cohorts. Therefore, a total of 24 prospective studies included 26 cohorts. Of the 24 prospective studies, 17 studies were conducted in the United States, 4 studies in Europe, 2 studies in China, and one study was conducted in United Kingdom. Cohort sizes ranged from 9,985 to 545,770, and the number of cancer cases varied from 45 to 9,305 cases.Of 38 case-control studies, 21 studies were conducted in the United States, 7 studies in Europe, 3 studies were conducted in Asia, 2 studies each were conducted in Canada, Mexico, and Uruguay, and one study was conducted in Australia, The number of cases enrolled in these studies ranged from 79 to 1760 cases, and the number of control subjects varied from 128 to 2481 subjects. Control subjects were drawn from the general population in 27 studies, hospitals in 11 studies.Twenty-two prospective and twenty-eight case-control studies investigated the association between dietary nitrate intake and cancer risk. Among the included studies, 15 studies were on gastric cancer, 6 studies each on colorectal cancer and non-Hodgkin lymphoma, 5 studies each on adult glioma and bladder cancer, 4 studies on esophageal cancer, 3 studies each on breast cancer, pancreatic cancer, renal cell cancer and thyroid cancer and ovarian cancer.Comparing the highest vs. the lowest levels of dietary nitrate intake, statistically significant inverse association was observed for gastric cancer  Figure . No signI2 = 56.0%, Pheterogeneity = 0.103), gastric cancer , ovarian cancer , and renal cell cancer .No statistically significant heterogeneity across studies was detected for dietary nitrate intake in relation to cancers of adult glioma, bladder cancer, colorectal cancer, esophageal cancer, non-Hodgkin lymphoma, pancreatic cancer, and thyroid cancer. We observed some heterogeneity for studies of dietary nitrate intake and breast cancer , thyroid  , esophageal cancer , gastric cancer , non-Hodgkin lymphoma , ovarian cancer  and prostate cancer .No statistically significant heterogeneity across studies was observed for dietary nitrite intake in relation to cancers of adult glioma, bladder, breast, ovarian cancer, pancreatic, renal cell, and thyroid. We observed heterogeneity for studies of dietary nitrite intake and colorectal cancer  suggested publication bias, whereas Begg's rank correlation test (P = 0.208) did not. Adjusting the possible publication bias for nitrates using “trim and fill” method did not influence the pooled RR . We did not evaluate publication bias for other cancer sites due to small numbers of studies for those sites.P = 0.583; Egger's regression test: P = 0.349). A significantly publication bias was detected in gastric cancer by Egger's regression test (P = 0.024), whereas Begg's rank correlation test did not (P = 0.293). Adjusting the possible publication bias for gastric cancer using “trim and fill” method significantly influenced the conclusion . To explore the possible heterogeneity between dietary nitrite and gastric cancer, we further conducted a meta-regression. We found that geographic area was the main source of heterogeneity for nitrites, which interpreted 73.83%(0.049/0.188) of the estimated between-study variance (τ2). We did not evaluate publication bias for other cancer sites due to small numbers of studies for those sites.No publication bias was evident for the relations of dietary nitrite intake to esophageal cancer , but not many studies considered these factor; not many studies assessed nitrate and nitrite intake by specific food sources or stratified/adjusted for these factors. Concomitant consumption of dietary nitrite/nitrite and vitamin C is likely to be important for inhibition of endogenous nitrosation [In conclusion, findings from this meta-analysis provided modest evidence that dietary nitrate and nitrite intake were potentially associated with certain type of cancer risk. In the field of nutritional epidemiology, diet is a very complex and potentially modifiable exposure. Because of these limitations and confounding factors, we could not absolutely confirm the reliability of these findings. Future well-designed observational studies are warranted to further clarify the potential nitrate/nitrite and cancer association by subtypes and according to molecular classifications.th, 2016 using MEDLINE  for both case-control and cohort studies that evaluated the association between dietary nitrate or nitrite intake and the risk of cancer. The search was limited to published studies in English and studies of humans by using the following keywords and Medical Subject Headings terms: (nitrate OR nitrite OR N-nitroso compounds) AND (cancer OR neoplasm OR carcinoma OR tumor). In addition, we carried out a manual retrieve of reference lists of included studies to identify other possible eligible articles that were not found in our primary search. We followed standard criteria for conducting and reporting meta-analyses. [We identified studies through searching from database initiation until April 30nalyses. , 74Published studies were included in the analysis based on the following criteria: (1) investigated the association between dietary nitrate and/or nitrite intake and cancer risk; (2) had a case-control or cohort study design; (3) provided odds ratio (OR), relative risk (RR), or hazard ratio (HR) estimates with its 95%CI or data necessary to calculate them. When multiple publications from the same study were available, we used the publication with the largest number of cases or the most-applicable information. To be eligible for dose-response analysis, the studies had to further provide quantitative measure of dietary nitrate/nitrite intake for at least three categories with the estimates of RRs, corresponding 95%CI, category-specific or total number of cases and category-specific or total number of either person-years or non-cases.Finally, we identified 62 potentially relevant full-text publications from 3058 articles Figure . In totaTwo investigators (L X and M M) independently performed the eligibility evaluation with the inclusion criteria and data abstraction. Disagreements were discussed and resolved by consensus or by involving a third reviewer (J Z). The following information was extracted from each eligible study by: (1) name of the first author; (2) year of publication; (3) origin of country; (4) study sample size ; (5) gender; (6) duration of follow-up for cohort studies; (7) exposure and outcome assessment including dietary nitrate and/or nitrite intake category; (8) cancer type; (9) study-specific adjusted estimates with their 95%CIs for highest compared with lowest dietary nitrate/nitrite intake; (10) factors matched by or adjusted for in data analysis. If multiple estimates of the association were available, we abstracted the estimate that adjusted for most of confounders. If none were adjusted, we included the crude estimate. If no estimate was given, it was calculated with its corresponding 95%CI using raw data presented in the publication.We did not adopt the Newcastle-Ottawa Scale  to asses2I statistics [p-value less than 0.1 were considered statistically significant of heterogeneity. When substantial heterogeneity was detected, the summary estimate based on the random-effects model (DerSimonian and Laird method) was reported [The study-specific adjusted RRs were used as common measure of association across studies. As absolute risk of cancer is relatively low, we assumed that estimates of ORs from case-control studies and risk, rate, or HRs from cohort studies were all valid estimates of the RR. Thus, we reported all results as the RR for simplicity . The posatistics . In Q streported . Otherwireported . We usedP value of <0.05 for the two aforementioned tests was considered representative of significant statistical publication bias. All data analyses were carried out using Stata software . P values were 2-sided with a significance level of 0.05.In a further analysis, we pooled risk estimates related to nitrate/nitrite and risk of cancer according to 10mg/0.5mg per day of dietary intake. We used generalized least squares for trend estimation as described by Orsini et al . In dose


Quantitative analyses of circulating cell-free DNA (cfDNA) are suggested to be a promising method for the detection of colorectal cancer, validated clinical relevance of cfDNA has not been published so far. Though some of the inconsistent results were published. This study is the first meta-analysis to systematically evaluate the diagnostic accuracy of circulating cfDNA as non-invasive biomarkers for colorectal cancer.p = 0.197).Fourteen studies concerning a quantitative analysis of circulating cfDNA for the diagnosis of colorectal cancer met the inclusion criteria. Data includes 1,258 patients with colorectal cancer and 803 healthy individuals as control was analyzed. The summary estimates were as follow: sensitivity, 0.735 (95% CI 0.713–0.757); specificity, 0.918 ; positive likelihood ratio, 8.295 ; negative likelihood ratio, 0.300 ; diagnostic odds ratio, 30.783 ; and area under the curve, 0.8818 , respectively. Publication bias was not evident with Deeks’ funnel plot asymmetry test  is better than absolute DNA concentration in diagnostic accuracy of colorectal cancer. Colorectal cancer is the third most common cancer worldwide, with 945,000 new cases diagnosed and 492,000 deaths each year. This cancer has vague or nonspecific symptoms, so it is generally diagnosed in the advanced stage. Furthermore, mortality of colorectal cancer is strongly related to disease stage: the 5-year survival rate decreases from 95% in stage I to 6% in patients with stage IV . TherefoCurrently, the major available strategies for diagnosis of colorectal cancer include colonoscopy and fecal occult blood testing. Histopathology examination via colonoscopy is considered as the golden standard. However, people always reject screening of colonoscopy because of its uncomfortable invasive process and complex bowel preparation in China. In addition, fecal occult blood testing, even colonoscopy, may fail to detect carcinomas at early stage. Blood-based tests are the most promising method, as getting a patient's blood is a easy and convenient way of early examination.Carcinoembryonic antigen (CEA) and carbohydrate antigen-19-9 (CA 19-9) etc are clinically used as routine tumor markers to monitor disease progression of colorectal cancer. Nevertheless, these markers have limited use in early diagnosis and cancer screening due to their low sensitivity and specificity . AbnormaCirculating Cell Free DNA (cfDNA) is a type of cell-free nucleic acids that is released from normal and deceased cells from apoptosing and necrotizing processes . MoreoveValidated clinical relevance of cfDNA has not been published so far. Though some of the inconsistent results were published. The present study aimed to carry out the first meta-analysis to quantitatively analyze the diagnostic accuracy of circulating cfDNA and to systematically evaluate the potential of circulating cfDNA as non-invasive biomarkers for colorectal cancer. We also sought to compare the integrity index and the concentration of cfDNA in the diagnosis of colorectal cancer.The process used to select studies is summarized in Figure Based on the QUADAS-2, the quality assessment results of the eligible fourteen studies are shown in Table 2 for sensitivity was 88.6%, p = 0.000 and I2 for specificity was 82.8%, p = 0.000). The threshold effect was the major cause of heterogeneity. When it existed, the logit of sensitivity were positively correlated with the logit of 1-specificity, and there would be shoulder-like ROC plane curve. In this meta-analyses, the Spearman correction coefficient was 0.096 and the p value was 0.705, confirming that the threshold effect was not significant and the heterogeneity must be caused by other reasons. Therefore, we could combine most evaluation index directly. The overall pooled sensitivity and specificity were 0.735 (95% CI 0.713–0.757) and 0.918 , respectively. Forest plots are shown in Figure p = 0.0000 and the distribution of DORs does not along a straight line, which means heterogeneity exist due to non-threshold effect. The SROC curve for the included studies is shown in Figure Eighteen sets of data were included in the analysis, significant heterogeneity existed among the overall pooled results , participants , specimen types (plasma or serum) and sample size (number of cases ≥ 100 or number of cases < 100). We found that integrity index: ALU247/ALU115 group had a better diagnostic accuracy compared with ALU115&cfDNA levels group, even overall data, with sensitivity of 0.747 versus 0.717 (ALU115&cfDNA levels) and 0.735 , specificity of 0.939 versus 0.917 (ALU115&cfDNA levels) and 0.918 , PLR of 9.398 versus 8.235 (ALU115&cfDNA levels) and 8.295 , NLR of 0.277 versus 0.334 (ALU115&cfDNA levels) and 0.300 , DOR of 37.767 versus 27.825 (ALU115&cfDNA levels) and 30.783  and AUC of 0.9275 versus 0.8652 (ALU115&cfDNA levels) and 0.8818 , respectively. We also found that China has the best overall accuracy in detecting colorectal cancer than Italy or other country group by current evidence. with sensitivity , specificity , PLR , NLR , DOR  and AUC . Furthermore, We cannot determine which is more accurate in serum-based assays or plasma -based assays, sensitivity of 0.750 versus 0.707, specificity of 0.924 versus 0.900, PLR of 8.858 versus 6.868, NLR of 0.324 versus 0.214, DOR of 29.789 versus 31.501 and AUC of 0.8581 versus 0.9365. In addition, the subgroup with larger sample size own a higher potential diagnostic value of cfDNA than smaller sample size group, with sensitivity (0.739 versus 0.726), specificity (0.939 versus 0.898), PLR (11.397 versus 6.390), NLR (0.273 versus 0.319), DOR (43.554 versus 23.910) and AUC (0.8932 versus 0.8772). The pooled data such as sensitivity, specificity, PLR, NLR, DOR, and AUC for each subgroup are shown in Table We performed a meta-regression analysis to explore possible sources of the heterogeneity from the articles.p value from high to low. It was noticed that quality cause statistically significant differences among studies, indicating that quality substantially affect the diagnostic accuracy. The diagnostic accuracy of studies which are defined as high risk of bias is 0.25 times lower than studies had low and unclear risk of bias . Other factors did not show any definite influence on heterogeneity , “Study location” (Country: China or Other countries), “type of specimens” (Sample: plasma or serum), “Methods of detection”(Assay methods: qPCR or non qPCR), measuring objects (Object: integrity index or others), number of cases (Size: ≥ 100 or < 100) and “four key domains in QUADAS-2”. Then, we carry out new regression analyses respectively after dropping the variables one by one, according to the ty Table .The Fagan nomogram is a graphical tool for estimating how much the result on a diagnostic test changes the probability that a patient has a disease. To use this tool, you need to provide the probability of disease before testing and the likelihood ratio for the diagnostic test. From our Fagan's Nomogram Figure , we founp = 0.197)  in the funnel plot. The angle should close to 90 degree when publication bias is absent. In this meta-analysis, publication bias was not evident with Deeks’ funnel plot asymmetry test  Figure .In 1948, Mandel and Metais firstly described the presence of cfDNA in human blood. Several years later, Leon, et al.  demonstrLater studies , 23 haveSeveral previous meta-analyses have published the diagnostic accuracy of quantitative analysis of cfDNA including ovarian cancer  and lungIn this exploratory meta-analysis of 14 studies, including 18 sets of data, the pooled sensitivity and specificity of the circulating cfDNA assay were 0.735 (95% CI 0.713–0.757) and 0.918 , respectively, indicating quantitative analysis of cfDNA has poor sensitivity but acceptable specificity for diagnosis of colorectal cancer. Likelihood ratios are used for assessing the value of performing a diagnostic test and the verity of sensitivity and specificity. LRs of greater than 10 may make a definite diagnosis for a disease, LRs of less than 0.1 may eliminate the possibility of a disease to some extent. LRs are more clinically meaningful than SROC curve and DOR. In our study, the pooled PLR and NLR of the circulating cfDNA assay was 8.295  and 0.300 , respectively. This result suggested that colorectal cancer patients via circulating cfDNA assay have approximately 8.295 times higher chance have a positive result compared with healthy controls, and the probability of the individuals with colorectal cancer was approximately 30.0% when circulating cfDNA test was negative. These results indicated that the unsatisfactory likelihood ratios obtained in meta-analysis may reflect poor robustness and accuracy. DOR is commonly used to assess diagnostic efficiency because it combines sensitivity, specificity, PLR and NLR data. DOR indicates the multiples on the probability of a positive result versus a negative result in diagnostic test. The pooled DOR in our study was 30.783 , indicating a relatively high level of overall accuracy. Moreover, ROC is normally used to describe overall test performance and AUC serves as a measurement indicator, the AUC of SROC for cfDNA was 0.8818, indicating a relatively high accuracy of circulating cfDNA for colorectal cancer diagnosis.We were able to separately evaluate four different subtypes. The studies on integrity index: ALU247/ALU115 group had a better overall accuracy compared with ALU115&cfDNA levels group, even overall data, with higher level of sensitivity, specificity, PLR, DOR and AUC. CfDNA reported by China has more accurate than cfDNA reported by Italy or other country group in diagnosis of colorectal cancer. Meanwhile, our subgroup analysis suggested that larger sample size groups were more accurate in detecting colorectal cancer than smaller sample size groups. We also found that serum-based assays showed a higher level of sensitivity, specificity and PLR but lower DOR and AUC compared with plasma-based assays. The Fagan nomogram reveal that incremental values of cfDNA could raise the probability of colorectal cancer from 50% to 91%, which means cfDNA is excellent in the clinical utility assessment.2 test. The threshold effect is usually a primary cause of heterogeneity in diagnostic meta-analysis. However, the spearman correction coefficient of our study  indicated that the heterogeneity must be caused by other reasons rather than threshold effect. In order to explore the potential source of heterogeneity, we investigated the characteristics of included studies such as publication year, study location, type of specimens, methods of detection, measuring objects, number of cases and four key domains in QUADAS-2 using meta-regression. Finally, our analysis revealed that study quality largely contributed to the substantial heterogeneity, indicating that the study design with high risk biases of “Patient selection”, “Index Test”, “Golden Standard” and “Process and Progress” could be easier than other characteristics to affect the diagnostic accuracy. Heterogeneity may also have risen due to other reasons, such as age, tumor type, metastasis, TNM staging, operation method and treatment protocol, which could not be analyzed in the present study due to the related data are so insufficient.Heterogeneity is an critical issue in meta-analysis. In our study, Significant heterogeneity was detected among the trials by the IAlthough publication bias can be another problem in meta-analyses, Deeks’ funnel plot asymmetry test did not identify such bias, indicating that the results of our meta-analysis are reliable.Many different hypotheses concerning the origin of the circulating cfDNA have been proposed, including liberation from the tumor itself by rupture or necrosis, a derivative from abnormal apoptotic pathways, autophagia, mitotic catastrophe and micrometastases .However, injury, acute inflammation, or infarctions may also lead to cells rupture and cfDNA release . In addiCEA and CA19-9 are widely used markers in clinical medicine for the diagnosis of CRC. In fact, increased CEA concentrations occur in only 5%–40% of CRC patients, and positive result are often observed in cancer-free patients who suffer from benign diseases such as liver damage or inflammatory diseases ; CA19-9 Similar to all meta-analyses, our study was subject to several limitations. First, for the sources of substantial heterogeneity in our study, we could not identify its by subgroup analyses and meta-regression. Second, our study is limited because of the small sample size. Only 14 studies met our criteria to examine the quantitative analysis of circulating cfDNA for the diagnosis of colorectal cancer. Moreover, some included studies lacked information and data, especially with respect to cfDNA integrity index: ALU247/ALU115. Third, only full-text studies published in English and Chinese were included in this meta-analysis. Because the authors could not easily understand other languages. Therefore, a potential selection bias may exist.A prospective protocol was registered on PROSPERO International prospective register of systematic reviews (identification number CRD42016047066). According to the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) , we condWe performed a systematic literature search in several electronic databases, including PubMed, EMBASE, Cochrane Library and Chinese National Knowledge Infrastructure (CNKI) from inception to August 07, 2017The search terms were as follows:  AND )) AND (cell free DNA OR circulating DNA OR cfDNA) AND (blood OR serum OR plasma OR circulation) AND (diagnoses OR sensitivity and specificity OR ROC curve).In order to assess completeness, we also reviewed the reference lists from all included articles to identify additional relevant studies. No attempt was made to recover unpublished studies.Eligible studies had to meet the following inclusion criteria:(1) the outcome of interest was quantitatively analysis to the diagnostic accuracy of circulating cfDNA for colorectal cancer; (2) sensitivity and specificity were reported or could be calculated; (3) absolute numbers of true-positive (TP), false-positive (FP), true-negative (TN), and false-negative (FN) were provided;Two reviewers (X Wang and XQ Shi) independently determined the eligibility of the studies, and disagreements in decisions were resolved by consensus.The following data were extracted from each identified study by two reviewers (X Wang and XQ Shi): last name of the first author; study location; publication year; number of cases and controls; methods of detection; type of specimens; measuring objects; cut off values; diagnostic performance, including sensitivity, specificity, TP, FP, TN, and FN.We used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2)  to assesReferring to the standard methods of previous diagnostic meta-analysis , we calc2 statistics were also used to assess the heterogeneity between studies. A random-effects model was applied when significant heterogeneity was detected. We considered a value of p less than 0.1 or an I2 value > 50% to indicate substantial heterogeneity [p < 0.10) [The Higgins Iogeneity . Subgrou < 0.10) . Clinicap < 0·05 was considered statistically significant except where otherwise specified.All statistical analyses were performed by Meta-DiSc 1.4  and STATA 12·0 statistical software package . A threshold of Our meta-analysis suggested that the diagnostic accuracy of circulating cfDNA has unsatisfactory sensitivity but acceptable specificity for diagnosis of colorectal cancer. Furthermore, the integrity index (ALU247/ALU115) is better than absolute DNA concentration in diagnostic accuracy of colorectal cancer. We hold the opinion that the cfDNA may be valuable in early complementary diagnosis, but still need to be combined with conventional examination for colorectal cancer detection. Additional highquality rigorous studies, especially, comparing multiple time points in different tumor stage group and employing reasonable measurement techniques, should be performed to confirm our results or explore the clinical utility of cfDNA in the diagnosis of colorectal cancer.


Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related mortality worldwide. Host gene variants may influence hepatitis B virus- (HBV-) related HCC. Human leukocyte antigens (HLA) play an important role in presenting virus antigens to immune cells that are responsible for the clearance of virus-infected cells and tumor cells. Previous studies have investigated the HLA-DQ (rs2856718 and rs9275572) polymorphisms that may be associated with the development of HBV-related HCC. However, the results are controversial or inconclusive. Hence, we conducted a meta-analysis to derive a more precise estimation of the associations. A total of 6 articles were used to evaluate the effect of the two polymorphisms on the risk of HBV-related HCC. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. We found that rs2856718 and rs9275572 in HLA-DQ significantly decreased HBV-related HCC in total population, especially in Chinese, but not in Saudi Arabian. Further validation of our results in larger populations and different ethnicities are required. Primary liver cancer is one of the six most common cancers and the second largest cause of cancer deaths worldwide , especially in undeveloped countries . ApproxiHuman leukocyte antigen (HLA) has been identified to be associated with regulating the immune response to HBV infection and clinical outcomes . HLA-DQsPrevious studies have assessed the association between HLA-DQ (rs2856718 and rs9275572) polymorphisms and HBV-related HCC susceptibility, but the results of previous studies are inconsistent and inconclusive , 15–19. To identify relevant studies, we systematically searched PubMed, EMBASE, Google Scholar and China National Knowledge Infrastructure (CNKI) databases. The search strategy was based on a combination of “HLA-DQ,” “hepatitis B virus,” or “HBV”; “Hepatocellular carcinoma,” “HCC,” or “liver cancer”; “polymorphism” or “SNP”; and “rs2856718” or “rs9275572” . The languages of the reviewed articles were limited to English and Chinese. In addition, references of retrieved articles were also screened.The following criteria were necessary for inclusion in the meta-analysis: (1) a case-control study that had investigated the genetic risk of HBV-related HCC in relation to HLA-DQ rs2856718 or rs9275572, (2) original papers containing independent data, (3) the study that provided the available genotype frequencies, (4) the study that provided sufficient information for calculating the pooled odds ratios (ORs) with 95% confidence intervals (CIs), and (5) the genotype distribution of a control group that are consistent with the Hardy-Weinberg equilibrium (HWE).Exclusion criteria were as follows: (1) case-only studies, (2) review articles, (3) repetitive reports, and (4) lack of genotype frequency data. In addition, if multiple studies had overlapping data, only the most recent version was used.The following data were independently extracted from each study by two authors (Jingzhu Lv and Tao Xu): the first author's name, year of publication, country, genotyping method, number of cases and controls, genotype, and allele frequency. After extraction, data were reviewed and compared by the two independent investigators. Any disagreements were resolved by discussion with the third investigator.χP < 0.05 was considered as significant disequilibrium in the control group). Odds ratios (ORs) with 95% confidence intervals (95% CIs) were used to estimate the strength of the association between HLA-DQ (rs2856718 and rs9275572) polymorphisms and HBV-related HCC. The pooled ORs were obtained from combination of single studies by homozygote comparison, heterozygote comparison, dominant and recessive models, and allele comparison, respectively. The significance of pooled ORs was assessed by the Z test, and PZ < 0.05 was considered as the significance threshold. Based on the heterogeneity test, the pooled OR was calculated using the fixed  or random  effect models. Sensitivity analysis was carried out to identify the effect of data from each study on the pooled ORs. Finally, publication bias was assessed using Egger's test, and PE < 0.05 was considered statistically significant.All statistical analyses were performed using Stata software version 12.0 . The Hardy-Weinberg equilibrium test in the control group was undertaken using the A total of 47 potentially relevant articles published up to March 27, 2017 were systematically identified in PubMed, EMBASE, Google Scholar, and CNKI. The flow chart that summarized the literature review process and the specific reasons for any exclusion from the meta-analysis are shown in PZ < 0.001), recessive contrast , homozygous contrast , heterozygous contrast , and allele contrast  was significantly associated with HBV-related HCC (PZ = 0.019)  .PZ < 0.001; AA versus AG + GG: OR = 0.37, 95% CI: 0.24–0.56, PZ < 0.001; AA versus GG: OR = 0.29, 95% CI: 0.19–0.45, PZ < 0.001; AG versus GG: OR = 0.56, 95% CI: 0.45–0.69, PZ < 0.001; and A versus G: OR = 0.52, 95% CI: 0.44–0.62, PZ < 0.001), particularly in Chinese population, but not among Saudi Arabian population  . pulation . Similar< 0.001) .The sensitivity analysis was performed to assess the influence of an individual study on the overall OR, and the corresponding pooled ORs were not materially altered Figures  and 5.Publication bias of the included articles was assessed using Egger's test. The results of Egger's test indicated that no evidence of publication bias was observed in HLA-DQ (rs2856718 and rs9275572) polymorphisms Tables .+ T cells resulting in generating immunity against infection [+ T cells were significantly increased in tumor, ascites, and peripheral blood of patients with HCC and showed that HBV-specific and HLA class II-restricted CD4+ T cell responses may be related to HBV-related HCC development [HLA-DQs belong to HLA class II molecules, which are expressed as cell-surface glycoproteins that present viral peptides to CD4nfection . A studyelopment . Recentlelopment –25. Accuelopment . Chen etelopment , while Kelopment . Gao et elopment . Other'selopment . Howeverelopment . Meanwhielopment .In order to resolve this conflict, we conducted a meta-analysis on the association between HLA-DQ (rs2856718 and rs9275572) polymorphisms and HBV-related HCC. Meta-analysis has been recognized as an important tool to more precisely define the effect of selected genetic polymorphisms on the risk for disease and to identify potentially important sources of between-study heterogeneity. There are variations between human populations, so a SNP allele that is common in one geographical or ethnic group may be much rarer in another. So we also analyzed the distribution of HLA-DQ (rs2856718 and rs9275572) polymorphisms in different ethnic groups. Our results indicated that HLA-DQ (rs2856718 and rs9275572) polymorphisms were associated with the decreased risk of HBV-related HCC in Chinese population, but not in Saudi Arabian population. However, the sample size in Saudi Arabian population is too small to conclude a negative association. The comparison between Chinese population and Saudi Arabian population may be imbalanced as a result of the sample size. Therefore, the findings of this study should be validated in the future through a population-based study.As a meta-analysis of observational studies, there are some limitations. Firstly, we did not have original data for all studies to adjust estimates and perform a more precise analysis, including gender, age, drinking, smoking, lifestyle, body mass index, and so on. Secondly, the number of published studies was not sufficiently large for a comprehensive analysis. Thirdly, the interaction of gene-gene and of gene-environment has not been evaluated owing to the absence of original data. Therefore, more studies are needed to get more reliable results.In conclusion, the current meta-analysis suggested that HLA-DQ (rs2856718 and rs9275572) polymorphisms were associated with HBV-related HCC risk among Chinese population. Taken together, our study suggested that HLA-DQ loci are candidate susceptibility regions that have some marker SNPs (rs2856718 and rs9275572) for HBV-related HCC in Chinese population.


The subgroup analysis also presented similar association for non-melanoma skin cancer in heterozygote model . Moreover, the further analysis based on the histological type of non-melanoma skin cancer indicated a significantly decreased risk of BCC in allele model  and dominant model . However, neither overall analysis nor subgroup analysis based on cancer subtype revealed a significant association of −1082G>A or −592C>A polymorphisms with skin cancer. The present study suggested a potential association between IL-10 −819C>T polymorphism and decreased risk of skin cancer, but a lack of association for −1082G>A and −592C>A polymorphisms. Further invalidation is urgently needed.The current study was designed to quantitatively summarize the evidence for the strength of the associations between common IL-10 functional polymorphisms and skin cancer risk. Relevant publications concerning the associations between common IL-10 functional polymorphisms and skin cancer were retrieved by a comprehensive electronic literature search in PubMed, Web of Science, EBSCO, Embase, China National Knowledge Infrastructure, Wanfang, Chinese Biomedical Database (CBM). The odds ratio (OR) and 95% confidence interval (CI) were utilized to assess the strength of the relationship. A total of 26 studies including 4090 cases and 4133 controls  were enrolled in the meta-analysis. Overall, the results revealed a borderline decreased risk of skin cancer in heterozygote model (OR = 0.82, 95CI = 0.67–1.00,  Skin cancer classified as either non-melanoma and melanoma dermatic carcinoma represents one of the most common malignancies in white-skinned populations, with increasing incidence in recent years , 2. DespInterleukin-10 (IL-10), as an important immuno-modulator with pleiotropic functions, is produced by multiple cell types including keratinocytes, immunocyte and tumor cells . AlthougIn vitro studies showed striking differences in the ability to produce IL-10 between individuals following mitogen stimulation of whole-blood cultures, which mainly appears in different efficiency of IL-10 mRNA synthesis [ynthesis . The difynthesis . Geneticynthesis . Althouget al. [et al. [Detailed flow of study selection is displayed in Figure et al.  and the  [et al.  on −1082p > 0.05). Similarly, there was no significant association revealed in the melanoma and non- melanoma skin cancer subgroup analyses . Moreover, a further subgroup analysis according to the histological type of non-melanoma skin cancer showed no significant relationship whatever in basal cell carcinoma (BCC) and squamous cell carcinoma . The results are detailed in Table The aggregated ORs and heterogeneity test results for the association between the −1082G>A polymorphism and the risk of skin cancer are presented in Table p = 0.05). The subgroup analysis also presented a reduced skin cancer risk associated with −819 C>T variant of IL-10 in heterozygote model  in non-melanoma skin cancer but not in melanoma skin cancer in any genetic model . Moreover, the further analysis based on the histological type of non-melanoma skin cancer indicated a significantly decreased risk of BCC in allele model  and dominant model  but not in melanoma skin cancer . Furthermore, no significant association was observed in the melanoma and non- melanoma skin cancer subgroup analyses in any genetic model . Also, no significant association concerning the −592C>A and the risk of melanoma skin cancer was suggested whatever in BCC and SCC .Nine studies involving 1419 cases and 1346 controls were pooled into the meta-analysis to investigate the association concerning −592C>A polymorphism. Overall, as shown in Table p = 0.736 for −1082G>A; p = 0.392 for −819C>T; p = 0.729 for −592C>A). Sensitivity analysis by sequential omission of each individual study revealed no substantial alterations of the synthetic results for −1082G>A and −592C>A polymorphisms, suggesting the robustness and reliability of results. However, we found a slight fluctuation of pooled results regarding −819C>T polymorphism under dominant and heterozygote models  should be considered. Fourthly, all the included investigations in the current study were conducted in Caucasian population, which may limit the applicability and representativeness of results.In conclusion, the present study suggested a potential association between IL-10 −819C>T polymorphism and decreased risk of skin cancer, but no association for −1082G>A and −592C>A polymorphisms. In light of the limited sample size and considerable limitations mentioned above, further large-scale multicenter epidemiological, multi-ethnicity-based studies considering comprehensive haplotype effect of IL-10 polymorphisms are urgently needed.Initially, an electronic search of PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Wanfang and Chinese Biomedical Database was carried out to identify relevant studies up to June 2017 with the following search terms: “interleukin-10”, “IL-10”, and “skin cancer”, “skin carcinoma”, “melanoma”, and “polymorphisms”, “polymorphism”, “variant”, “genotype”. All the studies reported in English and Chinese were considered for screening. The bibliographies of identified studies and relevant review articles were further tracked manually and/or electronically for additional eligible studies. In case of duplication, only the study with largest sample size and sufficient information was selected.Studies identified for inclusion subsequent to an eligibility evaluation were required to satisfy the following criteria: (1) studies concerning the associations between three common IL-10 polymorphisms and skin cancer risk; (2) studies with a case-control or cohort design; (3) all the cases with a pathological confirmation in the studies; (4) studies providing sufficient information on the genotype distribution in case and control groups or necessary information to calculate the odds ratios (ORs) and 95% confidence intervals (95% CIs).With a uniform reporting table, all eligible studies were carefully and independently reviewed by two investigators. Any disagreement was resolved by a consensus reached by all the reviewers. The following information was extracted from each study: first author, publication year, country, ethnicity, genotypes distribution in cases and controls, source of control, genotyping methods, cancer subtype and IL-10 polymorphisms.http://www.cochrane.org/software/revman.htm). The significance of the association was determined by a Z test with a random or fixed effect model according to the between-study heterogeneity, and p < 0.05 was considered significant [Q-test and I2 statistic test were performed to evaluate the heterogeneity assumption (p > 0.1 indicated the absence of heterogeneity) [p < 0.05 was considered as significant publication bias [The strength of the associations between IL-10 polymorphisms and skin cancer risk were measured by the pooled ORs and 95% CIs under five genetic models  using the RevMan 5.2 software  . The fixion bias , 38.


An increasing number of studies have investigated associations between collagen IX alpha 2 chain (COL9A2) and collagen IX alpha 3 chain (COL9A3) gene polymorphisms and the risk of lumbar disc degeneration (LDD). However, these studies have yielded contradictory results. The purpose of this meta-analysis is to investigate the association between the collagen IX gene polymorphisms  and LDD.All relevant articles were collected from PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI). The last electronic search was performed on September 1, 2017. The allele/genotype frequencies were extracted from each study. The odds ratio (OR) and 95% confidence interval (CI) were used to assess the strength of associations under the five comparison genetic models. Statistical analysis was performed by Review Manager (RevMan) 5.31 software.P = 0.11; rs12722877: G vs. C, OR = 0.83, 95% CI = 0.69–1.01, P = 0.06; rs7533552: G vs. A, OR = 1.11, 95% CI = 0.98–1.25, P = 0.09; rs61734651: T vs. C, OR = 1.57, 95% CI = 0.51–4.84, P = 0.43). The Egger text and the Begg funnel plot did not show any evidence of publication bias.The meta-analysis of 10 case-control studies, including 2102 LDD cases and 2507 controls, indicated that COL9A2 gene  and COL9A3 gene (rs61734651) polymorphisms were not associated with LDD (rs12077871: T vs. C, OR = 1.85, 95% CI = 0.87–3.91, rs12077871, rs12722877, and rs7533552 variants in COL9A2 and rs61734651 variant in COL9A3 were not significantly associated with a predisposition to LDD. Large-scale and well-designed studies are needed to confirm this conclusion. Low back pain (LBP) is a prevalent disease in adults, especially those ranging from 40 to 80 years of age . LBP canCollagen IX gene is one of the most recent trending research targets among numerous genes . Collagehttp://www.ncbi.nlm.nih.gov/pubmed), Web of Science (http://www.isiknowledge.com/), and CNKI . To identify all possible studies, we used the following terms: “LDD” or “Lumbar disc disease” or “Lumbar disc degeneration” and “COL9A2” or “COL9A3” or “Collagen IX” or “Polymorphisms” or “COL9A*.” No language or publication date restrictions were applied. The last electronic search was performed on September 1, 2017.The study was conducted by searching literature databases, including PubMed (The following inclusion criteria were used to search eligible studies: (1) investigated the relationship of COL9A2 or COL9A3 gene polymorphisms with LDD, (2) case-control or cohort design, and (3) provided available data for the estimation of an odds ratio (OR) and 95% confidence interval (CI). Studies were excluded according to the following criteria: (1) repeated publications, (2) reported in the form of comment and review, (3) irrelevant to LDD, and (4) unavailable allele and genotype frequencies. Two investigators (W.H.H and W.S.T) independently evaluated the articles for compliance with the inclusion and exclusion criteria. For disagreements, a consensus was reached by a third investigator (C.W.Y).The following data were extracted from all the eligible articles: first author’s name, publication year, country of enrollment, ethnicity, numbers of cases and controls, disease, diagnostic criteria, source of controls, genotyping methods, genotypes, and allele frequency of cases and controls. Data were extracted independently by two reviewers (W.H.H and W.S.T), and a third reviewer (C.W.Y) was needed for any disagreements.The methodological quality of the included studies was evaluated according to a quality evaluation form base in the Critical Appraisal Skills Programme (CASP) for case-control study . The assQ test and I2 test. To calculate the pooled OR, a fix effect model was performed if no heterogeneity existed . Otherwise, a random effect model was used. Five comparison genetic models were conducted to evaluate the association between the four single nucleotide polymorphisms (SNPs)  and LDD risk. Hardy-Weinberg equilibrium among controls was estimated using the HWE version 1.20 program . If there was heterogeneity in some models , we performed the sensitivity test to assess the possible influence of one study on the pooled OR. Studies were removed, in turn, from the overall analysis. In addition, we performed subgroup analysis stratified by ethnicity. Funnel plots and Egger’s tests were used to assess the potential publication bias.Meta-analysis was conducted using Revman 5.31 software . The pooled OR and 95% CI were used to estimate the strength of correlations between COLA9A2  and COL9A3 (rs61734651) variants and LDD. Heterogeneity was tested using the chi-square-based It will be reasonable to estimate the combined effect from a group study if the effects found individually in studies are sufficiently similar. Some variation between the studies is expected because the estimates of the treatment effect are influenced by chance. What we need to know is whether there is more than just a chance-related variation. The heterogeneity test was performed to determine this extreme variation. Therefore, in this study, chi-square statistic was performed together with the degree of freedom. During the meta-analysis, the results were evaluated by incorporating suspicious relevance studies into statistical analyses. Then, these studies, the appropriateness of which were questionable, were excluded from the study and the same analyses were repeated. After comparing the two results, the data for the appropriate ones were interpreted.As shown in Fig. P = 0.11). Furthermore, we performed the subgroup analysis stratified by ethnicity. The result showed rs12077871 was not associated with LDD risk in the Asian population. The subgroup analysis of the Caucasian population was unavailable as there were insufficient studies. The forest plot of the allele contrast genetic model demonstrated the association between rs12077871 polymorphism and LDD susceptibility . Moreover, we performed the subgroup analysis stratified by ethnicity. For the Asian population, rs12722877 polymorphism was associated with LDD predisposition under the allele contrast genetic model . However, a significant association was not found in other genetic models. The subgroup analysis of the Caucasian population was unavailable due to insufficient studies. The forest plot of the allele contrast genetic model indicated the association between rs12722877 polymorphism and LDD predisposition . In addition, we performed the subgroup analysis stratified by ethnicity. The data showed rs7533552 polymorphism was not associated with LDD risk in the Asian population. The forest plot of the allele contrast genetic model demonstrated the association between rs7533552 polymorphism and LDD predisposition . Furthermore, we performed the subgroup analysis stratified by ethnicity. The result showed rs61734651 polymorphism was not associated with LDD susceptibility in the Caucasian population. The subgroup analysis of the Asian population was unavailable due to insufficient studies. The forest plot of the allele contrast genetic model indicated the association between rs61734651 polymorphism and LDD predisposition .Publication bias was appraised by applying Begg’s funnel plots and Egger’s regression test Fig. . The resVarious risk factors were widely considered to be related to symptomatic LDD, including environmental, ergonomic, and biometric factors. Nowadays, increasing evidence indicates that genetic factors play critical roles in LDD . Plenty Several authors reported that collagen IX provided optimal stability to the lumbar disc cross-linked with collagen II  and indiOur meta-analysis of 10 studies, involving 2102 LDD cases and 2507 controls, found no statistically significant association between COL9A2 gene  and COL9A3 gene (rs61734651) polymorphisms and LDD risk. The previous studies had reported that COL9A2 and COL9A3 gene polymorphisms were related to LDD predisposition in different ethnic population groups. Therefore, we performed a subgroup analysis stratified by ethnicity (Caucasian and Asian). Our results showed rs12722877 was associated with LDD risk in the Asian population under the allele contrast genetic model (C vs. G), but not under other genetic models. This finding was in partial accordance with a previous meta-analysis study . We shouIn our systematic review, increasing the number of studies, which were examined, was possible by extending our search criteria. However, we think that this situation may give rise to further confusion among the results and it may prevent making binding inferences. Several limitations of this study should be acknowledged. First, only English and Chinese documents were searched, while reports in other languages were excluded. This may lead to publication bias. Second, the limited sample size of the pooled studies may exert an influence on their statistical power. Third, we did not perform stratification analysis by age, gender, and environmental factors as a data limitation.COL9A2 gene  and COL9A3 gene (rs61734651) polymorphisms were not associated with susceptibility to LDD. The associations of COL9A2 and COL9A3 gene polymorphisms and the risk of LDD could not be fully excluded. Large-scale and well-designed studies are needed to further analyze this field.


Compared with non-consumption, the HRs (95% CIs) of HF across chocolate consumption levels were 0.92 (0.88–0.97), 0.86 (0.78–0.94), 0.93 (0.85–1.03), and 1.07 (0.92–1.23) for 1, 3, 7, and 10 servings/week, respectively. In conclusion, chocolate consumption in moderation may be associated with a decreased risk of HF.Epidemiological studies have shown inconsistent findings on the association between chocolate consumption and risk of heart failure (HF). We, therefore, performed a meta-analysis of prospective studies to determine the role of chocolate intake in the prevention of HF. We searched databases of PubMed, Web of Science, and Scopus through December 2016 and scrutinized the reference lists of relevant literatures to identify eligible studies. Study-specific hazard ratios (HRs) and 95% confidence intervals (CIs) were aggregated using random effect models. The dose–response relationship between chocolate consumption and incident HF was also assessed. This meta-analysis is registered with PROSPERO, number CRD42017054230. Five prospective studies with 106,109 participants were finally included. Compared to no consumption of chocolate, the pooled HRs (95% CIs) of HF were 0.86 (0.82–0.91) for low-to-moderate consumption (<7 servings/week) and 0.94 (0.80–1.09) for high consumption (≥7 servings/week). In dose–response meta-analysis, we detected a curve linear relationship between chocolate consumption and risk of HF ( Heart failure (HF) is a complex clinical syndrome characterized by dyspnea, fatigue, and fluid retention. Globally, there is an estimated 20 million people suffering from this syndrome, with a projected increase of 25% in prevalence in 2030 . DespitePrevious studies demonstrated that consumption of chocolate products may confer salutary cardiovascular effects . It is fThis study was conducted in accordance with the Meta-analysis Of Observational Studies in Epidemiology guideline . We perfStudies were included if they met all of the following conditions: (1) the study was cohort study, case-control study, or post hoc analysis of randomized trials; (2) the exposure was chocolate consumption; (3) the outcome of interest was incident HF ; (4) the risk measures of HF, such as hazard ratios (HRs), were reported. For dose–response meta-analysis, the risk estimates should be provided for ≥3 quantitative categories of chocolate consumption, and the number of cases and person-years or participants for each category were also available . Reviews, comments, abstracts, and duplicates were excluded.Two reviewers independently abstracted the study characteristics. The maximally-adjusted risk estimates were also recorded for pooled analyses. We used the Newcastle-Ottawa Scale (NOS)  to assesThe aggregated risk estimates of HF were presented as HRs with 95% confidence intervals (CIs). To enable the pooling of data, we standardized chocolate consumption across studies using a common measure, i.e., servings/week. In the study by Kwok et al.  that repQ test with a significant level of p < 0.1 and quantified using the I2 statistic. A value of I2 > 50% indicated the presence of high heterogeneity. Subgroup analyses were performed according to sex, body mass index (BMI), prior history of myocardial infarction, and follow-up durations, with differences between subsets confirmed by the Altman and Bland test [We defined the low-to-moderate chocolate consumption as a median intake of <7 servings/week and high consumption as a median intake of ≥7 servings/week. The study by Lewis et al.  only proand test . We alsop-value for nonlinearity by testing the null hypothesis that the coefficient of the second spline is equal to zero. To evaluate the dose–response relationship between chocolate consumption and risk of HF, we conducted a two-stage random-effects dose–response meta-analysis. In the first stage, we estimated a restricted cubic spline model with three knots at the 10th, 50th, and 90th percentiles of chocolate consumption using generalized least-square regression, considering the correlation within each set of published HRs as described by Orsini et al. . Then thp-values < 0.05 were regarded as of significance.All statistical analyses were realized using STATA 12.0  and R 3.2.5  softwares, and The search strategy initially identified 139 publications, of which 62 duplicates and 67 irrelevant studies were removed. Among the remaining 10 articles selected for full-text reading, 5 articles that failed to meet the eligibility criteria were excluded. Finally, five studies ,17,18,19The baseline characteristics of the studies are displayed in I2 = 0.0%, p = 0.46; and high consumption: I2 = 22%, p = 0.28). When we separated low (<1 serving/week) from moderate (1–6 servings/week) chocolate consumption, the summarized HRs (95% CIs) were 0.87 (0.80–0.94) and 0.84 (0.78–0.91), respectively, for low and moderate consumption (p = 0.58).The pooled HR (95% CI) of HF was 0.86 (0.82–0.91) for low-to-moderate chocolate consumption and 0.94 (0.80–1.09) for high consumption , with nosumption . In subgsumption . Sensitip for nonlinearity = 0.005; In dose–response meta-analysis, a curve linear relationship was found between chocolate consumption and risk of HF (There were limited studies that have investigated the association between chocolate intake and risk of HF. Our meta-analysis showed that light-to-moderate, but not high, consumption of chocolate was associated with a reduced risk of HF. Besides, we observed a nonlinear relationship between chocolate consumption and risk of HF in dose–response meta-analysis.Chocolate is an important dietary source of flavonoids, a subclass of polyphenols. Previous studies have demonstrated that flavonoids in chocolate may be responsible for the salutary effects of chocolate on blood pressure, possibly by acting as an angiotensin converting enzyme inhibitor . Flavono2 [In dose–response meta-analysis, we found a J-shaped relationship between chocolate consumption and risk of HF. Initially, compared to no chocolate consumption, a moderate consumption is associated with a risk reduction in HF incidence of 16%. A higher than moderate intake is not associated with a decreased risk. This result may be attributable to the high calorie content of commercially available chocolate. When consuming chocolate in high amounts, the high-energy content of chocolate may lead to increased weight gain , a known2 ,19 and t2 , a more Our finding is in contrast to a recent meta-analysis , which sOf course, some remaining points need to be addressed. In all of the included studies, the incidence of HF was reported as cumulative incidence in years, and we do not know the HF-free survival curves. Although our results suggest that chocolate consumption may play a role in the prevention against HF, we cannot derive from the data how many years of chocolate consumption are needed to reach this result, and cannot exclude the possibility that it may contribute only to delaying the occurrence of HF, even possibly even only by delaying the occurrence of other cardiac events that would trigger the development of HF. In addition, it is unclear whether the competing risk of death may affect our final results. Competing risk of death is an important consideration in geriatric studies ; howeverThere are several limitations in our work. First of all, the recall and selection bias cannot be eliminated because of the observational nature of original studies. However, all included studies had a prospective design, and we only selected the maximally adjusted HRs for pooling analyses. Second, due to the lack of relevant data, we cannot evaluate the risk of HF for consuming different types of chocolate or different amounts of energy intake as was noted to have an interaction with the effects of chocolate consumption in the study of Kwok et al. . For theIn summary, this meta-analysis indicates that chocolate consumption in moderation may be associated with a decreased risk of HF. Future studies are required to determine whether the association differs by chocolate subtypes or levels of energy intake and to clarify the mechanisms involved.


Gestational diabetes mellitus (GDM) is defined as glucose intolerance with onset or first recognition during pregnancy. It is associated with an increased risk of pregnancy complications. Susceptibility to GDM is partly determined by genetics and linked with type 1 diabetes-associated high risk HLA class II genes. However, the evidence for this relationship is still highly controversial. In this study, we assessed the relationship between HLA class II variants and GDM. We performed meta-analysis on all of literatures available in PubMed, Embase, Web of Science and China National Knowledge Infrastructure databases. The odds ratio and 95% confidence interval of each variant were estimated. All statistical analyses were conducted using the Comprehensive Meta Analysis 2.2.064 software. At the allelic analysis, DQB1*02, DQB1*0203, DQB1*0402, DQB1*0602, DRB1*03, DRB1*0301 and DRB1*1302 reached a nominal level of significance, and only DQB1*02, DQB1*0602 and DRB1*1302 were statistically significant after Bonferroni correction. At the serological analysis, none of DQ2, DQ6, DR13 and DR17 was statistically significant following Bonferroni correction although they reached a nominal level of significance. In sum, our meta-analysis demonstrated that there were the associations between HLA class II variants and GDM but more studies are required to elucidate how these variants contribute to GDM susceptibility. For HLA-DQ alleles, DQB1*02 was reported to be positively associated with GDM in African-American14Meta-analysis is a valued method that integrates the findings of multiple investigations, which enhances the statistical power and generate a more definitive conclusionIn the preliminary database search, we identified a total of 305 articles, of which 50 publications were potentially relevant to our study. After screening the full-text of the papers, we excluded 34 from the study because they were functional studies or presented duplicate data sets or they did not supply sufficient data about HLA polymorphisms. In our analysis, we finally employed a total of 16 studies111315161718192122232425262728I2-statistic for results of meta-analyses. At the allelic level, seven of them reached nominally significant association with GDM . At the serological level, we determined there were four groups that demonstrated nominally significant association with GDM . We determined that there were positive associations for DQ2 , DR13  and DR17 , with EFs of 0.07, 0.07 and 0.15, respectively. In addition, the relationships were heterogeneous amongst the observations of each group , while DQB1*0602 and DQ6 were determined to be main protective factor against GDM (PF of 0.07 for DQB1*0602 and 0.03 for DQ6).There are still some limitations in our study. Firstly, our study only analyzed the role for HLA class II, the main susceptible variant of type 1 diabetes, in disease risk or resistance to GDM. The underlying pathogenetic mechanism common to both GDM and type 1 diabetes could be better understood if additional genetic links could be discovered. Secondly, we need to investigate more new publications when available on some of the variants that we have analyzed to generate a more robust assessment. This is because a small sample size would reduce the capacity to identify other GDM linked variants. For instance, the protective association that we identified between DQB1*0203 allele and GDM was conducted in two studies16In sum, our meta-analysis indicates that DQB1*02 and DRB1*1302 are firmly associated with increased risk of developing GDM, while DQB1*0602 acts in a protective role against GDM. However, these associations should be interpreted with caution and the role of HLA genes in GDM pathogenesis needs further functional investigations.All of the literatures that were have used to investigate the relationships between HLA class II variants and GDM were extracted from PubMed, Embase, Web of Science and China National Knowledge Infrastructure (CNKI) using the search terms “gestational diabetes mellitus” and “HLA”. The publications used in our analysis were dated up to July 1, 2016. We only selected relevant literatures published in English and Chinese for analysis. Moreover, the references of all the selected articles were manually and independently searched by two of our researchers (G.C-C and J.Y-M). If more than one article was published on the same population, we selected the most complete and updated publication for analysis. We performed meta-analysis on polymorphisms that have been examined in at least two populations.The publications that we have selected in our study had to meet the following criteria before inclusion: (1) relevant HLA class II variant polymorphism and GDM risk, (2) odds ratio (OR) and 95% confidence interval (CI) were presented or they could be calculated from the publication, and (3) case-control studies written in either English or Chinese. We excluded publications that had the following criteria: (1) review papers, family pedigree studies and animal studies, (2) studies that contained a lack of data, and (3) studies that did not present the target alleles.We used two investigators (G.C.-C. and J.Y.-M.) to independently extract data from the literature database according to the selection criteria described above. All disagreements within the extracted data were resolved by a senior investigator (J.C.-X.). The following information was extracted from the publications: (1) the first author’s surname, (2) year of publication, (3) study population, (4) typing method of HLA variants, (5) diagnostic criteria of GDM, (6) number of cases and control group, and (7) study design. The HLA-DR and HLA-DQ genotypic data were grouped into serological types according to agreements from the 13th International Histocompatibility Workshop and ConferenceThe quality of the selected publications for our analysis was assessed according to the Newcastle-Ottawa Quality Assessment ScaleP-value of <0.05 was considered to be nominally significant. Results were adjusted for multiple testing using the Bonferroni correction, which deflates the reported P-value to take into account the number of tests performed, using the formula 1 − (1 − α)1/n Ph and I2 Ph-value was more than 0.10, a fixed-effects model was selected but otherwise a random-effects model was chosen44Meta-analysis was conducted on all available data of polymorphisms from HLA class II variants with GDM risk using Comprehensive Meta Analysis software version 2.2.064 . The statistical significance of the pooled OR was determined by Z-test. Unless otherwise stated, a The expected statistical power was calculated using the PS Power and Sample Size Calculations Version 3.0 software , which indicates the true association between HLA class II polymorphisms and GDM. The level of significance was set at 0.05. The ORs of each study represented the 25 and 75 percentiles of the distribution of effect sizes for HLA alleles and groups  and S2.How to cite this article: Guo, C.-c. et al. The relationships between HLA class II alleles and antigens with gestational diabetes mellitus: A meta-analysis. Sci. Rep. 6, 35005; doi: 10.1038/srep35005 (2016).


CircRNAs, a type of non-coding RNAs with special loop structure, of which the aberrant expression is closely related to tumor growth, proliferation, metastasis and recurrence. It remains unclear whether they have the potential to be biomarkers for diagnosis and prognosis of cancers. The study aims to clarify the relationship of circRNAs expression with cancers diagnosis and prognosis.Sensitivity, specificity, area under curve (AUC) and receiver operating characteristic curve (ROC) were calculated to evaluate the diagnostic efficacy; Hazard ratio (HR) of overall survival (OS), disease free survival (DFS) and recurrence free survival (RFS) were calculated to evaluate the association between circRNAs expression and survival of cancer patients.A total of 27 studies were involved in the meta-analysis, including 16 diagnostic and 11 prognostic articles. Among the diagnostic studies, 18 kinds of circRNAs had been investigated, in which 3 were up regulated and 15 were down regulated. Their pooled sensitivity, specificity and AUC were 0.71(0.65–0.77), 0.77(0.72–0.81) and 0.81(0.77–0.84), respectively. In stratified analysis, a higher specificity was shown in circRNAs for diagnosing gastric cancer and hepatocellular cancer. 12 circRNAs were involved in the prognostic studies, including 6 up-regulated and 6 down-regulated circRNAs. Their overall HR of OS and DFS/RFS were 1.37(0.98–1.75) and 2.28 (0.77–3.79), respectively.CircRNAs have the potential to be biomarkers for diagnosis and prognosis of cancers. Further investigations are still needed to explore the clinical value of circRNAs as tumor markers. Circular RNAs (circRNAs) are formed by the covalent binding between phosphodiester bonds on their 3’ and 5’ ends, which are distinct from linear RNAs –3. Due tAlthough, in recent years, some certain circRNAs have been reported to act as stable markers for diagnosis and prognosis of cancer, there still are some questions affecting the evaluation of circRNAs in cancer diagnosis and prognosis, including limited number of research cases, skimble-scamble sample source and disease status, various experiment methods and other uncontrolled factors. Therefore, the current research data about the clinic role of circRNAs remains unconvincing. Accordingly, we conducted a systematic review and meta-analysis on the association of circRNAs expression with cancer diagnosis and prognosis for the first time. The study aims to clarify their relationship and the possibility of circRNAs as tumor markers, which could be helpful for clinical decision-making and the development of circRNAs-based targeted therapy.A total of 1905 records were retrieved initially from databases, and 27 articles were involved in our final meta-analysis after multiple steps of selection . Samples in most researches were selected from cancerous and paracancerous tissues taken from surgery, while circRNAs expression in plasma was only detected by a single study. Quality assessment of diagnostic accuracy studies-2 (QUADAS-2) was employed to evaluate the quality of enrolled diagnostic studies. All of them were suggested to have moderate to high quality and thus appropriate for meta-analysis  and 15 were down-regulated  and cancer type . In the subgroup with large sample size (> 100), the pooled sensitivity, specificity and AUC were 0.710.63–0.78), 0.76(0.52–0.72) and 0.77(0.73–0.80); while 0.74(0.66–0.80), 0.84(0.75–0.90) and 0.78(0.74–0.82) for small sample size (< 100). The pooled sensitivity, specificity and AUC in the subgroup of gastric cancer were 0.66(0.57–0.74), 0.80(0.72–0.85) and 0.80(0.78–0.83); while 0.72(0.60–0.82), 0.67(0.58–0.76) and 0.76(0.72–0.79) for colorectal cancer and 0.73(0.59–0.83), 0.79(0.72–0.85), 0.86(0.83–0.89) for hepatocellular cancer, respectively . Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of enrolled studies, and they were all suggested to be appropriate for meta-analysis . Among them, two articles were focused on disease free survival (DFS) and recurrence free survival (RFS); eight were focused on overall survival (OS); the other one was related to both DFS and OS. The main characteristics of prognostic studies were shown in Table analysis .Among the 12 prognosis-related circRNAs, 6 were up-regulated  and 6 were down-regulated  and 0.46(0.32–0.59), respectively  and 15 down-regulated circRNAs . It is widely believed that circRNAs are with cancer forewarning function. For example, hsa_circ_0000190  and hsa_Twelve prognosis-related circRNAs were involved in the meta-analysis, in which 6 were up regulated  and 6 were down regulated . A circRNAs combination was found to be associated with poor prognosis for GC patients, containing the three down-regulated circRNAs and one up-regulated circRNA, hsa_circ_101308. And another circRNAs combination including hsa_circ_0007874 and hsa_circ_104135 was related to more benign prognosis for HCC patients. Apart from them, the up-regulation of ciRS-7, hsa_circ_100876, circRNA-MYLK, circRNA_100338 was also suggested poor prognosis, while circPVT1, hsa_circ_100269, hsa_circ_0007874, hsa_circ_104135 and circ-ITCH indicated a better outcome. Generally speaking, oncogenes can elevate the susceptibility to cancer and confer to poor survival. However, some molecules were malignant could lead to better prognosis or higher sensitivity to chemotherapy ; while JSeveral limitations should be acknowledged. First, all the samples in our study were selected from Asian population and the detection method for circRNAs expression was major in qRT-PCR. Single sample source and technology might mask the possible impacts of ethnicity and experimental methods on the results. Second, some literatures was not successfully extracted due to the no response of the investigators, which would produce some bias for the selection of the recruitment. Moreover, the sample size involved in the meta-analysis was still relatively small limited by few available articles to date.In summary, as a type of stably expressed molecules, circRNAs could be promising biomarkers for diagnosis and prognosis of cancers. More association studies focusing on circRNAs expression with cancer are needed to further explore the practical values of circRNAs expression on clinical diagnosis and treatment.This study was carried out on the basis of Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) .A literature search of PubMed and Web of Science was performed for studies related to the association of circRNAs with cancer diagnosis or (and) prognosis up to September 10th, 2017, using the following key words: “circRNA cancer”, “circRNA carcinoma”, “circRNA tumor”, “circRNA neoplasm”, “circularRNA cancer”, “circularRNA carcinoma”, “circularRNA tumor”, “circularRNA neoplasm”.Two reviewers (Hanxi Ding and Qian Xu) evaluated the eligibility of retrieved articles independently. All selected studies met the following criteria: (1) Cases were histopathologically diagnosed as cancer; (2) Information of control groups was available; (3) CircRNAs were used for cancer diagnosis or prognosis; (4) The effect indicators contained AUC, sensitivity, specificity or OS, DFS, RFS, HR and 95% CI; (5) Data was sufficient for quantitative analysis. The exclusion criteria were: (1) Duplicate studies; (2) Reviews; (3) Not related to human or cancer; (4) Irrelevant to the study subject; (5) Insufficient data for quantitative analysis. Two reviewers reached consensus regarding all items.Two investigators (Hanxi Ding and Qian Xu) independently extracted the data according to critical criteria. The following information was obtained from each article: first author’s name, publication year, origin country and ethnicity, circRNAs’ name, cancer type and stage, total number of cases, sample source, and detection method. Diagnostic indicators included sensitivity, specificity and AUC; Prognostic indicators were survival and HR with 95% CI for DFS or OS. When HRs with 95CIs were not presented in the study, they were extracted from Kaplan-Meier survival curves using a method introduced by Tierney et al .Quality assessment of diagnostic accuracy studies-2 (QUADAS-2) was employed to evaluate the quality of enrolled studies. Prognostic studies quality was assessed based on the Newcastle-Ottawa Scale .P < 0.05 was considered as statistically significant.All analyses were conducted using Stata software, version 11.0. 2 statistic [Sensitivity, specificity and AUC were involved in the diagnostic meta-analysis. The pooled parameters were all estimated by continuous meta-analysis model. The area under summary receiver operator characteristic curve (SROC) was calculated to evaluate the diagnostic efficacy. Inter-study heterogeneity was examined with the Itatistic . To expltatistic . Deek’s tatistic . Sensiti2 statistic were used to judge the inter-study heterogeneity [P > 0.10 and I2 < 50%, suggesting an absent heterogeneity [In the prognostic meta-analysis, the pooled OR with 95% CI was calculated to evaluate the association between circRNAs expression and survival of cancer patients in both fixed-effect and random-effect models. Cochran’s Q test and Iogeneity . We poologeneity ; otherwiogeneity . Sensiti


Molecular epidemiological studies suggest that microRNA polymorphisms may be associated with an increased risk of coronary heart disease (CHD). However, the results of these studies were inconsistent and inconclusive. To derive a more precise evaluation, we performed a meta-analysis focused on the associations between microRNA polymorphisms and CHD risk. PubMed, Embase, CNKI and Wanfang databases were searched. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to assess the association between microRNA-146a rs2910164, microRNA-196a2 rs11614913, microRNA-499 rs3746444 and microRNA-149 rs71428439 polymorphisms and CHD susceptibility. Heterogeneity, publication bias and sensitivity analysis were conducted to measure the robustness of our findings. A total of thirteen related studies involving 8,120 patients and 8,364 controls were analyzed. Significant associations between microRNA-146a rs2910164 polymorphism and CHD risk were observed in the total population, as well as in subgroup analysis. For microRNA-196a2 rs11614913 and microRNA-499 rs3746444, similarly increased risks were also found. In addition, no significant association was detected between microRNA-149 rs71428439 polymorphism and CHD risk. In conclusion, our meta-analyses suggest that microRNA polymorphisms may be associated with increased risk of CHD development. Coronary heart disease (CHD) has become a main cause of morbidity and mortality worldwide . In 2010MicroRNAs (miRNAs) are small single-stranded non-coding RNA molecules which function in the post-transcriptional regulation of gene expression . EmerginBy affecting the miRNA maturation and the binding to target mRNAs, single nucleotide polymorphisms (SNPs) located in pre-microRNA (pre-miR) genes may alter the expression levels of a large number of target genes and cause the complex functional consequences . TherefoIn total, 285 relevant publications were retrieved according to the search strategy. Firstly, we excluded 254 articles after title reviewing and duplicate screening. Then, 19 studies including 6 reviews, 12 studies not for focus polymorphisms, and 1 study without available information  were exc2I<0.5). So we used the fixed effect model to calculate the ORs and 95% CIs. Overall, an increased CHD risk was detected in all five genetic models  .Ten eligible studies including 4,996 cases and 5,644 controls were included to assess the association between miR-146a rs2910164 polymorphism and CHD risk. The heterogeneity in all genetic models was not significant statistically  and heterozygous model  . However, when sensitivity analysis was performed, some changes of the pooled ORs were detected under both dominant and heterozygous models  Figure  were cons models .P = 0.015, 2I = 17.8%; GG vs. AA + AG: OR = 1.55, 95% CI = 1.07–2.27, P = 0.022, 2I= 58.1%; GG vs. AA: OR = 1.54, 95% CI = 1.08–2.20, P = 0.017, 2I= 52.6%)   . However= 0.821) .P = 0.107, 2I = 82.1%; GG vs. AA+AG: OR = 1.50, 95% CI = 0.98–2.27, P = 0.059, 2I = 64.2%; AG + GG vs. AA: OR = 1.31, 95% CI = 0.89–1.93, P = 0.169, 2I = 75.8%; GG vs. AA: OR = 1.67, 95% CI = 0.93–3.01, P = 0.086, 2I = 78.1%; AG vs. AA: OR = 1.18, 95% CI = 0.87–1.59, P = 0.281, 2I = 55.6%).A total of 2 studies with 1,208 cases and 1,185 controls were selected in the meta-analysis. This polymorphism was not found to be significantly associated with CHD risk in all five models . There also existed the possibility that other targets of miR-196a2 might play some roles in the development of CHD, despite it was unknown by far.To the best of our knowledge, this is the first meta-analysis assessing the association of miRNA-196a2 rs11614913 T>C, miRNA-499 rs3746444 A>G, and miRNA-149 rs71428439 A>G polymorphisms with CHD susceptibility. Interestingly, by increasing the sample size, the results of the combined analysis revealed a significant association with CHD risk for microRNA-196a2 rs11614913, even though no association was found in each single original study. How can we explain the association of miRNA-196a2 rs11614913 with CHD susceptibility? First, the miRNA-196a2 rs11614913 polymorphism involved a T to C nucleotide substitution and situated in the 3p strand of mature miRNA regions, which might affect both pre-miRNA maturation of 5p and 3p miRNAs and the interacting of target mRNAs to 3p mature miRNAs . Second,Our meta-analysis had several limitations. First of all, the ethnicity of most subjects was Asian in the current study and this restricted the general application of the results to other populations. Second, only articles published in English or Chinese were selected, potentially causing a language bias. Third, in the sensitivity analysis for miRNA-196a2 rs11614913 T>C and miRNA-499 rs3746444 A>G, we found that omission of each study made some significant differences on the results. Although it may be explained by the small number of studies included, the caution should be indicated when interpreting the association of these two miRNA polymorphisms with CHD. Third, the heterogeneity existed in our meta-analysis for miRNA-499 rs3746444 A>G and microRNA-149 rs71428439 A>G. For rs3746444, although subgroup and sensitivity analyses were performed, unfortunately, we have not found the sources of heterogeneity. Also, as for rs71428439, only two included studies were too small to analyze the sources of heterogeneity. Fourth, CHD is both multi-factorial disease influenced by genetic and environmental factors. However, in our current meta-analysis, the inter-gene and gene-environment interactions could not be conducted owing to the data deficiency. Last but not the least, genetic epidemiological studies show different genetic variants can predispose to different subtypes of CHD –42. So sIn conclusion, the current meta-analysis demonstrated that three functional polymorphisms of microRNA-146a rs2910164 G>C, microRNA-196a2 rs11614913 T>C and microRNA-499 rs3746444 A>G might take important part in the development of CHD. Considering the limitations in the current meta-analysis, our results should be interpreted with caution. More eligible studies with rigorous design are needed to confirm the association of above polymorphisms in miRNA and CHD risk in the future.We searched four electronic databases  for articles written in English or Chinese published prior to August 31, 2016. The following medical subject heading terms were used: (microRNA OR miRNA) AND  AND .All selected studies had to meet the following criteria: (1) published studies based on case-control design assessing the association of rs2910164 G>C in miR-146a, rs11614913 T>C in miR-196a2, rs3746444 A>G in miR-499 and rs71428439 A>G in miR-149 with CHD risk; (2) availability of allele or genotype frequency for calculating odds radio (OR) and their 95% confidence interval (CI). Studies were excluded if they investigated the progression, severity, phenotype modification, response to treatment, survival or family based studies. Moreover, meeting abstracts, case reports, editorials, review articles and non-English and non-Chinese articles were also excluded. For duplicate publications, the one with more complete design or larger sample size was finally selected.The two of the authors independently extracted the data from each relevant study including the first author, publication year, study country/region, ethnicity of participants (such as Asian or Caucasian), sources of controls, genotyping method, case-control matched status, HWE status of controls and number of genotypes in CHD cases and controls. Disagreements were reconciled through group discussion. The Hardy-Weinberg equilibrium (HWE) was calculated based on the genotypes of the controls.2I statistic and 2I>50% indicates significant heterogeneity between the studies. Based on the test of heterogeneity, a pooled OR was calculated by using fixed or random effect model, along with the 95% CI to measure the strength of the genetic association. For the microRNA-146a rs2910164 G>C polymorphism, the pooled ORs were obtained for the allele contrast (C vs. G), recessive model (CC vs. GG+GC), dominant model (GC+CC vs. GG), homozygous (co-dominant) model (CC vs. GG) and heterozygous (co-dominant) model (GC vs. GG). Similar genetic models were also assessed for microRNA-196a2 rs11614913 T>C, microRNA-499 rs3746444 A>G and microRNA-149 rs71428439 A>G variants. Subgroup analyses of ethnicity, source of controls, genotyping methods, case-control matched status and HWE status of controls were also submitted to statistical testing. In order to evaluate the stability of the results, sensitivity analysis was used, which meant omitting one study at a time, and then compared to show whether a significant difference existed between the former and the latter results. Publication bias was examined by the visual inspection of funnel plot, and Egger's regression test. Data were analyzed and processed using Stata 12.0 . P<0.05 was considered statistically significant.Heterogeneity among studies was examined with the


PLOS ONE Editors had the article reassessed by a member of our Editorial Board and one of the journal’s Statistical Advisors with expertise in meta-analyses. This assessment confirmed that there are reporting errors in the published article as well as concerns about the study design, data analyses, and conclusions.Following publication of this article , concernSpecific concerns and errors include:The authors did not report the dates of inclusion for the literature search, and they did not specify whether language exclusions were applied in the literature search.Reasons for exclusion listed in the flow diagram are vague, presenting a concern about reproducibility.et al. (2013) is a population-based retrospective cohort study assessing association between medications and survival, but did not assess cancer development or risk. Thus, it should not have been included in the current meta-analysis.Holmes et al. 1998, Saltzman et al. 2013), and four studies listed in Table 1 are not included in the case-control subgroup analysis , Li et al. 2003, Li et al. 2013). The reasons for excluding these articles are not explained by the authors. Li et al. (2013) is a case-control study but was included in the cohort subgroup in the analysis shown in Figure 2.In Figure 2, two studies listed in Table 1 are not included in the cohort subgroup meta-analysis  in the >5 years subgroup analysis in Figure 3 (438 instead of 4381), and the numbers reported for this study in substrata are total subject numbers instead of subgroup numbers.The number of cases was incorrectly reported for Fryzek et al.  do not correspond to those reported in the primary literature. The data presented in Figures 4 and 6 for Li et al. (2013) were not found in the primary article.Numbers reported in Figures 2, 3 for Li et al. (2013) were grouped in Figure 2.Lobular and ductal cancer cases from Li Different values for subtotal estimate (SE) and confidence intervals are reported for the “ever used” subgroup in Figure 3 versus in the Abstract and Results section.In the Results section, “Quantitative Summary ”, the authors report a “non-significant inverse association in case-control studies  [P = 0.02].” This statement is misleading, as the pooled estimate (RR = 0.98) indicates a neutral result. The meaning of the P value provided here is unclear.Data provided in the quantitative summary in Figure 6 does not match the corresponding data reported in the Results section.RR and 95% CI data presented in Figure 5 are not consistent with those shown in Figure 6.Only 12 of the 17 articles are included in the publication bias assessment, and the reason for excluding the remaining 5 is unclear.The Methods section statement beginning “When there was a significant publication with regard to CCB intake and breast cancer risk …” is misleading, as the trim and fill method was not reported as having been applied in this study.In Table 1, authors mention adjustments for sex in included studies, yet the meta-analysis reportedly included only female subjects.Concerns were raised regarding the use of a pooled risk ratio of only two studies, and regarding the pooling of risk ratios and odds ratios to derive an overall risk ratio.The authors pooled cohort and case-control studies in meta-analyses.The study lacked sensitivity analyses needed to adequately describe the results, including hospital-based vs population-based studies, studies with satisfactory adjustment sets vs. unsatisfactorily adjusted studies, high vs low quality studies, mortality vs incidence studies, leave-one-out-analysis, subgroup analyses by study region, or cancer stage.et al. (2013) studies: " …for the 3 studies which followed patients for >10 years." This sentence gives the incorrect impression that the three studies presented in the figure are all cohort studies with a long follow up and implies that the controls were patients at the time of CCB assessment. This figure includes two cohort studies and a case-control study.Concerns were raised about potentially misleading language in the description of Figure 4 results: Li Conclusions assert that this study found a “significant relationship with breast cancer”, but the estimates were predominantly indicative of neutral effects and did not achieve statistical significance.Conclusions also note that there was no indication of publication bias, but the authors did not discuss the limitations of tests used for analyzing small numbers of studies. Based on the results presented, the tests came close to statistical significance and some degree of bias was suggested by the funnel plot data.PLOS ONE Editors retract this article, as the integrity and validity of the study and its conclusions are compromised by the errors in reporting and analysis.In light of the above issues, the The authors could not be reached for comment.