I2 = 27.7%, p-heterogeneity = 0.198) and 5%  greater risks of lung cancer, respectively. According to smoking status, greater WHR was only positively associated with lung cancer among former smokers . In contrast, greater WC was associated with increased lung cancer risk among never smokers , former smokers  and current smokers . The summary RRs for highest versus lowest categories of WC and WHR were 1.32  and 1.10 , respectively. In summary, abdominal obesity may play an important role in the development of lung cancer.Several meta-analyses of observational studies have been performed to examine the association between general obesity, as measured by body mass index (BMI), and lung cancer. These meta-analyses suggest an inverse relation between high BMI and this cancer. In contrast to general obesity, abdominal obesity appears to play a role in the development of lung cancer. However, the association between abdominal obesity (as measured by waist circumference (WC) (BMI adjusted) and waist to hip ratio (WHR)) and lung cancer is not fully understood due to sparse available evidence regarding this association. PubMed and Web of Science databases were searched for studies assessing the association between abdominal obesity and lung cancer up to October 2016. The summary relative risks (RRs) with 95% confidence intervals (CIs) were calculated with a random-effects model. Six prospective cohort studies with 5827 lung cancer cases among 831,535 participants were included in our meta-analysis. Each 10 cm increase in WC and 0.1 unit increase in WHR were associated with 10% (RR 1.10; 95% CI 1.04, 1.17;  Lung cancer is the most common cancer in the world with 1.8 million new cases diagnosed in 2012, accounting for 12.9% of total cancer incidences. In terms of mortality, 1.6 million deaths were caused by lung cancer in 2012, accounting for 19.4% of total cancer deaths ,11. HoweThis meta-analysis was planned, conducted, and reported according to “Meta-Analysis of Observational Studies in Epidemiology (MOOSE) group” guidelines . PubMed To be included in this meta-analysis, the studies had to meet the following inclusion criteria: (a) the study had a prospective design ; (b) examined the association between measures of abdominal obesity (WC and/or WHR) and risk of lung cancer; and (c) relative risks (RRs) or hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were available. Accordingly, retrospective studies, or studies on lung cancer mortality or recurrence were excluded. If multiple publications from the same study were identified, the publication containing the largest number of cases and most detailed information  was selected.Using a standardized data-collection form, the following data were abstracted from each study: the first author’s last name, publication year, country, study population, duration of follow-up, number of participants, number of cases, ascertainment of adiposity, measures of abdominal adiposity, most fully adjusted risk estimates with their corresponding 95% CIs for each category of abdominal adiposity measures, adjustment for anthropometric variables, and adjustment for potential confounding factors. If multiple RRs of the association were available, we extracted RRs with their corresponding 95% CIs from the models that reflected the maximum extent of adjustment for potentially confounding variables, and from the models that further adjusted for anthropometric variables . When studies provided risk estimates according to smoking status, we extracted all of them and used the data in subgroup analysis. The study quality was assessed using the 9-star Newcastle-Ottawa Scale (NOS) , in whicQ and I2 statistics. For the Q statistic, p < 0.1 was considered statistically significant; and for the I2 statistic, the following conventional cut-off points were used: <25% (low heterogeneity), 25%–50% (moderate heterogeneity) and >75% (severe heterogeneity). Both Begg’s rank correlation test and Egger’s linear regression test were performed to investigate potential publication bias [RR was chosen as the common measure of association across this study, and HR was directly considered as RR. A DerSimonian and Laird random-effects model  was usedion bias . If evidion bias .p-values were two-sided, and the level of significance was at <0.05, unless explicitly stated.We only performed subgroup analysis according to smoking status  due to the limited number of studies included in this meta-analysis. In addition, to investigate the impacts of individual studies on the overall results, we also performed a sensitivity analysis by omitting one study in each turn while pooling results from the remainder. We performed a linear dose-response analysis examining the association between measures of abdominal obesity and lung cancer risk according to the method proposed by Greenland and Longnecker  and OrsiA flow chart of study selection, including reasons for exclusion, is presented in I2 = 27.7%, p = 0.198) . The summary RRs according to smoking status were 1.11  for never smokers, 1.12  for former smokers, and 1.16  for current smokers   A. No evi smokers B. Sensit) Online .I2 = 25.2%, p = 0.211) . The summary RRs according to smoking status were 1.07  for never smokers, 1.11  for former smokers, and 0.99  for current smokers   A. No evi smokers B. In a s) Online .To our knowledge, the present meta-analysis is the first quantitative review of prospective studies concerning the association between abdominal obesity and lung cancer risk. Our dose-response analysis revealed that each 10 cm increase in WC and 0.1 unit increase in WHR were associated with 10% and 5% greater risks of lung cancer, respectively. In contrast, observational studies have reported a consistent inverse relationship between general obesity, as measured by BMI, and lung cancer ,13,14. TThe exact mechanisms for the association between abdominal obesity and lung cancer remain poorly understood. One speculative biological mechanism for the contrary associations of abdominal obesity and general obesity to lung cancer may involve complex biologic pathways, such as hyperinsulinemia, decreased levels of sex hormone binding globulin (SBHG), and increased levels of unbound androgens and estrogens. All of these biologic pathways are more strongly related to abdominal fatness than to body fatness ,36,37,38Furthermore, there are several reasonable explanations for the contrary relationships of abdominal obesity and general obesity to lung cancer in regard to the residual confounding by smoking. The interrelations between general and abdominal obesity measures and smoking are complex and are subject to change over time. Smoking is a well-established risk factor for lung cancer , and is A dose-response meta-analysis by Duan et al.  did not Our stratified analysis according to smoking status revealed that higher WC was associated with 11% increased risk of lung cancer in never smokers, whereas no association was observed for WHR. As expected, greater WC was also positively associated with lung cancer among former smokers and current smokers. Regarding WHR, we observed a positive association among former smokers, but not among current smokers. These findings were somewhat surprising and challenging to explain since both WC (BMI adjusted) and WHR are measures of abdominal obesity. There are several explanations for the discrepancies between measures of abdominal obesity. First, WC (BMI adjusted) may be a better predictor of abdominal obesity than WHR ,48. SecoAs mentioned earlier, the findings from several prospective cohort studies have found a positive association between lung cancer incidence and WC, but only after further adjustment for BMI ,19,20,21Finally, it is worth taking into consideration that abdominal obesity and cancer share many risk factors, such as smoking, physical inactivity, and poor diet ,52. For This meta-analysis has several strengths, including incorporated evidence and relevant studies to the date. Because results from individual studies often had insufficient statistical power, the enlarged sample size from this present meta-analysis may enhance the power to detect a significant association and provide more precise estimates of the effects. All of the included studies have long follow-up durations and have a prospective nature that thereby reduced the likelihood of potential biases . Furthermore, given the considerably heterogeneous categories of abdominal obesity measures among included studies, a dose-response meta-analysis is necessary since it provides better precision of risk estimates than merely conducting high versus low analysis.There are several limitations in the present meta-analysis that should be acknowledged. First, almost all of the included studies were conducted in women. Thus, our findings might not apply to men. Unfortunately, we are unable to perform subgroup analysis according to sex of the participants in order to clarify whether the differences in body fat distribution between men and women may influence the overall positive association between abdominal obesity and risk of lung cancer. Further studies focusing on the influence of sex differences on this association are needed to address this issue. Second, although individual studies have considered a wide range of potential confounders in their analyses, the potential impacts of residual/unknown confounding factors on our findings cannot be completely excluded; for example, confounding from smoking may have contributed to observed positive association of abdominal obesity and lung cancer. Third, our analysis was limited by the number of included studies, which limits our ability to perform subgroup analyses . Fourth, the possible errors in WC and WHR measurements obtained by self-report and self-measurement have led to overestimation or underestimation of the true association between abdominal obesity and lung cancer. Fifth, the possible dose-response meta-analysis measurement error should also be acknowledged, as it requires assumptions such as extrapolating the width of the open-ended lowest and highest boundaries from the closest category and assigning the midpoint of each category of abdominal obesity measures to corresponding relative risk. Sixth, because the findings of the current meta-analysis were mainly based on data from studies conducted in Western populations, additional research in other populations is warranted to generalize the findings. Finally, given all of these limitations, the results from our meta-analysis should always be treated with caution. In summary, abdominal obesity may play an important role in the development of lung cancer. Further large prospective studies conducted in never smokers and both sexes are needed to extend and confirm our findings.


Further analyses of individual fermented dairy of cheese and yogurt showed cheese to have a 2% lower risk of CVD  per 10 g/day, but not yogurt. All of these marginally inverse associations of totally fermented dairy and cheese were attenuated in sensitivity analyses by removing one large Swedish study. This meta-analysis combining data from 29 prospective cohort studies demonstrated neutral associations between dairy products and cardiovascular and all-cause mortality. For future studies it is important to investigate in more detail how dairy products can be replaced by other foods. With a growing number of prospective cohort studies, an updated dose–response meta-analysis of milk and dairy products with all-cause mortality, coronary heart disease (CHD) or cardiovascular disease (CVD) have been conducted. PubMed, Embase and Scopus were searched for articles published up to September 2016. Random-effect meta-analyses with summarised dose–response data were performed for total (high-fat/low-fat) dairy, milk, fermented dairy, cheese and yogurt. Non-linear associations were investigated using the spine models and heterogeneity by subgroup analyses. A total of 29 cohort studies were available for meta-analysis, with 938,465 participants and 93,158 mortality, 28,419 CHD and 25,416 CVD cases. No associations were found for total (high-fat/low-fat) dairy, and milk with the health outcomes of mortality, CHD or CVD. Inverse associations were found between total fermented dairy  with mortality  contains supplementary material, which is available to authorized users. Cardiovascular disease (CVD) is the leading cause of mortality and disability worldwide . TogetheThis review was conducted based on guidelines of Meta-analysis of Observational Studies in Epidemiology . ProspecData were extracted from published articles by using a structured extraction form, which included descriptive characteristics of the study, range of intake, median intake, number of participants, number of mortalities, CHD or CVD cases, person-years at risk, and relative risk (RR) with 95% CI for each unit of dairy intake. For studies that reported results from different multivariable-adjusted models, the model with the most confounding factors was extracted for the meta-analysis. If dairy intake was presented in servings or times per period of time –36, 39, In some studies the mean intakes of dairy categories were not reported, in which case we calculated the mean value by using the lower and upper limit. For open-ended upper limits of intake, the same range as the lower category was applied. The categories of dairy types were defined in accordance with the definition in the original articles .Two independent reviewers determined the quality of the 29 studies based on the Newcastle–Ottawa quality assessment scale  . By evalMeta-analyses of each dairy type were performed if the number of studies was three or more. Splined variables were generated by MKSPLINE in STATA version 13.0 to determine the most appropriate knot points of nonlinear associations from goodness-of-fit tests and Chi square statistics. Spine analysis and dose–response generalised least-square trend (GLST) meta-analysis were applied for the further analysis of linear or nonlinear associations. Incremental dose–response RRs were derived from the random-effects meta-regression trend estimation of summarised dose–response data. Ding’s spaghetti plot was used to present the shapes of the association within individual studies, as described previously . Forest 2, >25 kg/m2) and Newcastle–Ottawa quality score < or ≥7. When number of the examined studies ≥10, potential publication bias was assessed by means of the Eggers test [P values <0.05 were considered as statistically significant.To explore heterogeneity between studies, I-squared was calculated from Cochrane Q test . In addiers test  and symm2 (range 22.3–27.1 kg/m2). The duration of follow-up ranged from 5 to 25 years, with a mean follow-up of 13 years. Study characteristics of each dairy intake category by outcomes are shown in Table Overviews of key characteristics of the 29 prospective cohort studies are shown in Table 2 = 62.2%, P = 0.005) and CVD  but not CHD . In sensitivity analyses, heterogeneity among studies of the mortality could be reduced to 50% (P = 0.042) with a RR of 1.00 (95% CI 0.97–1.04) by excluding the study of Soedamah-Muthu et al. [2 = 11.2, P = 0.338) after removing the study of Hu et al. [Total dairy intake (per 200 g/day) was not associated with the risk of all-cause mortality , CHD  or CVD . Considerable heterogeneity was observed in the meta-analyses of mortality  to 0% (P = 0.464) with results of RR 1.01, 95% CI 0.96–1.06) after removing the study of Dalmeijer et al. [P = 0.143) with results of RR 0.98 (95% CI 0.93–1.03) after excluding study Bonthuis et al. [2 = 31.5%, P = 0.232).High-fat dairy intake (per 200 g/day) showed no association with mortality , CHD  or CVD , and there was no significant heterogeneity. In sensitivity analyses of the association between high-fat dairy and CHD, I-squared was reduced from 22.9% .Low-fat dairy intake (per 200 g/day) was not significantly associated with mortality , CHD  or CVD . No heterogeneity was found in the meta-analysis on low-fat dairy. In the sub-group analysis for CVD  on subjects whose BMI > 25 kg/m2 = 97.4, P < 0.001), CHD  and CVD . In sensitivity analyses for the association between milk and all-cause mortality by excluding data of Michaelsson et al. [2 reduced to 70.1% (P < 0.001) with RR 0.99 (95% CI 0.96–1.01). By removing Kondo et al. [2 = 35.10, P = 0.118) with a RR of 1.01 (95% CI 0.97–1.05). Results of high-fat milk or low-fat milk were not reported, as only one study [2 = 0%, P = 0.479). Also, inverse associations were found between milk intake and CVD  for the studies which did not adjust for 7 confounders   or for the NOS score <7 .Milk intake  was not associated with all-cause mortality , CHD  or CVD . Significant heterogeneity was present for all-cause mortality , with RR of 1.00 (95% CI 0.99–1.00). Similarly, total fermented dairy intake  was non-linearly and modestly associated with a 2% lower CVD risk per 20 g/day  . Again, in a sensitivity test, excluding the Swedish study [P = 0.19), with a 1% lower CVD risk . Total fermented dairy intake  showed no association with CHD risk, with a RR of 0.99 (95% CI 0.98–1.01) per 20 g/day increment with no indications of a nonlinear association . The heterogeneity in the CHD and total fermented dairy data was significant . In sensitivity analyses, after excluding the study of Patterson et al. [2 = 32.5%; P = 0.122), but with results remaining similar with a RR of 1.00 (95% CI 0.99–1.01).Total fermented dairy intake  was non-linearly and marginally associated with lower mortality risk, with a RR of 0.98 (95% CI 0.97–0.99) per 20 g/day but with high heterogeneity (I99) Fig. . Signifish study  of womenn et al. , the het2 = 93.3%, P < 0.001) or CVD . In sensitivity analyses, heterogeneity was reduced after removal of the large Swedish study [2 = 11%, P = 0.337 for mortality; I2 = 0%, P = 0.835 for CVD), with no association for mortality and CVD (RR = 1 for both).Cheese (per 10 g/day) was marginally non-linearly inversely related to CVD , CHD  or CVD  .Yogurt (3 populations) was not associated with all-cause mortality  of the associations between total, high-fat, low-fat dairy and milk with risk of all-cause mortality, CHD or CVD, which indicated the findings and conclusions were also affected by characteristics of the study populations within different studies.No associations were found between total dairy and milk consumption with all-cause mortality, CHD or CVD in the current study, which is in agreement with several meta-analyses , 48. LarThree US prospective cohort studies described by Chen et al.  showed a12) [Despite their fat content and composition, milk and dairy products are naturally rich in various minerals , protein and vitamins (e.g. vitamin A and vitamin B12) . Nutrien12) , 58. Sho12) , 60 alsoThe current study also showed total fermented dairy and cheese intake to be marginally inversely associated with mortality and CVD risk, respectively, and large heterogeneity was present. However, by removing the study of Michaelsson et al. , heterogCheese consumption based on 11 populations was found to be modestly and inversely associated with CVD risk, with a 2% lower risk of CVD per 10 g/day of cheese, however, the significant association disappeared after removing the study of Michaelsson et al. . CompareFurthermore, total fermented dairy and cheese were modestly inversely associated with risk of CVD but not CHD in the current meta-analysis, so perhaps both dairy types play a role in reducing the risk of stroke. This is supported by the evidence of another recent meta-analysis , which fThe mechanism of the beneficial association of fermented dairy products and reduced CVD risk and mortality is uncertain. Evidence from randomised controlled trials suggests that the reason, at least in part, may be an effect of the food matrix reducing lipid absorption and short chain fatty acids produced by the bacteria in the large intestine . MoreoveStrengths of our study include the use of dose–response meta-analysis, the inclusion of more studies than in previous meta-analyses and the consideration of examination the individual dairy products separately such as dairy products in terms of fat content  or processing method (fermented or non-fermented). However, investigation of total dairy or total fermented dairy consumption with disease outcomes by combining dairy foods, high and low-fat dairy foods, solids and liquids, simply adding these up is a limitation which should be addressed in future studies by collecting and analyzing more detailed data. In addition, limitations of the study include sub-group analyses that lack statistical power, such as for Asian studies and effects of gender. We have 9 studies with scores of 7 or less by using the Newcastle–Ottawa Scale (NOS) . Study qThe current meta-analysis of 29 prospective cohort studies suggested neutral associations of total, high and low-fat dairy, milk and yogurt with risk of all-cause mortality, CHD and CVD. In addition, a possible role of fermented dairy was found in CVD prevention, but the result was driven by a single study.Supplementary material 1 (DOCX 345 kb)Supplementary material 2 (DOCX 19 kb)Below is the link to the electronic supplementary material.


Association between allergic conditions and prostate cancer risk has been investigated for many years. However, the results from available evidence for the association are inconsistent. We conducted a meta-analysis to evaluate the relationship between allergic conditions  and risk of prostate cancer. The PubMed and Embase databases were searched to screen observational studies meeting our meta-analysis criteria. Study selection and data extraction from included studies were independently performed by two authors. Twenty studies were considered eligible involving 5 case-control studies and 15 cohort studies. The summary relative risk (RR) for developing prostate cancer risk was 1.04 (95%CI: 0.92–1.17) for asthma, and 1.25 (95%CI: 0.74–2.10) for atopy, 1.04 (95%CI: 0.99–1.09) for hay fever, 0.96 (95%CI: 0.86–1.06) for any allergy. In the Subgroup and sensitivity analysis, similar results were produced. Little evidence of publication bias was observed. The present meta-analysis of observational studies indicates that no indication of an association between allergic conditions and risk of prostate cancer was found, and the meta-analysis does not support neither the original hypothesis of an overall cancer protective effect of allergic conditions, nor that of an opposite effect in the development of prostate cancer. Prostate cancer is one of most frequently diagnosed cancer in Western countries and is the second most common cancer in men, following lung cancer, worldwide14568Allergy-related carcinogenesis is a topic of interest but has generated considerable controversy. Considering the impact of the prostate cancer risk potentially resulting from allergic diaseases, a number of studies have explored the association between allergic diseases and prostate cancer risk10111213141516171821232425282930Following the development of our search strategy, 1,890 records were initially retrieved. After excluding the duplicates and articles that did not meet the inclusion criteria, we reviewed 34 possible relevant studies in full-text. A total of 14 studies were excluded for the following reasons: Two articles were covered the same population2733343536374041424344The 10121314172324282911161819221521101112131416171819212223242526282916101718192215252629111621131423Adjusted effect estimates could be determined for most cohort and case-control studies. Most risk estimates were adjusted for age (n = 12)101115171819222526283010111516171819252810151617252829101617251619The methodological quality of the included studies was generally good. The NOS scores ranged from five to seven . The medfor heterogeneity = 0.000; I2 = 73.2%), while the pooled SIR was 1.00 (95%CI: 0.68–1.47), with significant heterogeneity    . Egger funnel plot asymmetry test (P = 0.865) and Begg rank correlation test (P = 0.502) were performed to assess publication bias and the funnel plot symmetry (The association of asthma with prostate cancer was investigated in 17 studies10111213141516171821222425262830101115161718212225262830121314= 97.7%) . In subg= 97.7%) . When wesymmetry  was examfor heterogeneity = 0.428; I2 = 0.0%). Subgroup and sensitivity analysis produced similar results       . In subg= 73.2%) . The incfor heterogeneity = 0.287; I2 = 19.3%). Subgroup and sensitivity analysis yielded similar result   , encompassing hay fever, allergic asthma and atopy, are caused by inappropriate immunological response to antigens that do not elicit response in most individuals. Allergy-related carcinogenesis is a topic of interest but has generated considerable controversy. There has been a long-standing interest in determining whether individuals with allergic diseases have an altered risk of developing cancer. Several studies investigated the association between allergic diseases and specific cancers. Asthma, hay fever, and atopy have been associated with the risk of several specific cancers, such as pancreatic cancer, lymphomas, brain tumors, breast cancer and leukemia, although inconsistently101415461216131415172829301011192122232425262324252627282930The present meta-analysis exhibited several strengths, compared to the previous published meta-analysis. The first research highlight of this meta-analysis is its large sample size. The large number of total cases provided high statistical power to quantitatively evaluate the association between allergic conditions and prostate cancer risk. In addition, we expand the meta-analysis and the association between different geographic regions and study design, adjusted for covariates was also explored. Second, publication bias is a potential concern in any meta-analysis because small studies with null results do not get published. However, in our meta-analysis, we found little evidence of publication bias.Nevertheless, there are some several limitations in the present meta-analysis. First, case-control studies have intrinsic limitations, such as selective bias and recall or memory bias. This limitation can partly explained the different results between case-control and cohort studies in the stratified analysis. Second, we cannot exclude the possibility that the observed null relationship between allergic disorders and prostate cancer risk is attributed to confounding factors. Majority of the studies were adjusted for potential confounding factors, but not all potential confounders were adjusted in every study. Although the allergic conditions and prostate cancer share common some potential confounders, such as cigarette smoking, alcohol drinking, old age, BMI and race, in analysis stratified by adjusting the smoking status, age, alcohol drinking BMI and race, similar results were obtained. Third, measurement error in assessment of allergic conditions are known to bias effect estimates, however, none of included studies in the meta-analysis made any corrections for measurement errors. An accurate assessment of allergic conditions remains a challenge, because these measures are based on different assessment methods, such as allergen-specific IgE measurement, skin prick testing, self-reported questionnaire, interviewed by medical staff, and hospital discharge register. Diagnosis of allergic conditions was largely based on a self-reported. Only a few studied were based on measurements that may be condisered to be more objective: serum LgE or skin prick tests. The increasing errors in measurements become inevitable. The imprecise measurement of allergic disorders might have attenuated the true associations. Fourth, potential sources of between-study heterogeneity, which is common in meta-analysis, should be explored although the low heterogeneity was found between hay fever or atopy and prostate cancer risk. Results from subgroup and sensitivity analysis indicated that geographic region, study design, quality of NOS may be potential sources of heterogeneity. Thirds, in subgroup analysis, there was a marginally positive association between hay fever and prostate cancer risk in studies that adjusted for age and alcohol drinking and conducted in the Europe, but a null association among studies adjusted for cigarette smoking and race. Due to the numerous comparisons and few included studies, this positive finding may have been a chance finding. It indicated that more relevant articles are needed to further explore this association. Fifth, analysis of the length of the induction period allows for characterising an exposure–outcome relationship and for falsifying the pathway assumed. The longer the supposed time sequence between the exposure and the occurrence of the outcome, the more crucial to analyze the empirical induction period. The average follow-up ranged from 5.05 years to 43 years among included cohort studies. Patients were followed up over five years in majority of the studies (92.8%). Therefore, the observation period in the included cohort studies covered a reasonable induction period. Overall, these limitations may affect our final conclusions.In the meta-analysis, we found no indication of an association between allergic conditions  and risk of prostate cancer, and there is little observational support for the immune surveillace theory or antigenic stimulation theory in the development of prostate cancer risk. However, these results should be carefully interpreted because of the significant heterogeneity among studies and potential confounders. Additional large-scale and high-quality prospective studies are needed to confirm the association between allergic conditions and risk of prostate cancer.A literature search was performed in March 15, 2016 without restriction to regions, publication types, or languages. The primary sources were the electronic databases of Pubmed and Embase databases. To identify eligible studies, the main search employed various combinations of Medical Subject Headings (MeSH) and non-MeSH terms “prostate carcinoma” OR “prostatic cancer” OR “prostate cancer” OR “prostatic carcinoma” combined with “asthma” OR “asthma*” OR “allergy” OR “allerg*” OR “atopy”. The main search was completed independently by two investigators. Any discrepancy was solved by consultation of an investigator, not involved in the initial procedure. Moreover, the reference lists of all the studies and published systematic reviews, meta-analysis were also screened to identify other potentially eligible studies.To minimize the differences between studies, we imposed the following methodological restrictions for the inclusion criteria: 1) study design of interest was either cohort or case control study 2) the exposure of interest was allergic conditions ; 3) the outcome was prostate cancer; 4) the study reported enough information to extract effect estimates and the corresponding 95% confidence intervals. In case of multiple publications, only the most recent or comprehensive one was considered eligible. Two authors (JKS and XHY) independently evaluated the eligibility of all retrieved studies and disagreements were resolved through discussion or consultation with a third author (LHG).Data from the included studies were extracted and summarized independently by two of the authors using a pre-standardized data extraction form. Any disagreement was resolved by the senior author (ZWD). The following data were extracted from each study: first author, publication year, study design, country, sex, total number of cases and subjects for cohort studies, total number of cases and controls for case-control studies, assessment methods for allergic diseases, quantitative effect estimates  and 95%CI and variables adjusted for in the meta-analysis. The OR in one studyTwo review authors (SJK and ZJG) independently assessed the risk of bias using the Newcastle-Ottawa Scale (NOS), which consists of three factors: patient selection, comparability of the study groups, and assessment of outcome. A score of 0–9  was allocated to each study50I2 was used to assess heterogeneity across studies, with I2 values of 0%, 25%, 50% and 75% representing no, low, moderate and high heterogeneity, respectively. Subgroup analysis was stratified by geographic region, study design, quality of NOS scale, body mass index (BMI) and whether the study adjusted for risk factors, including age, race, alcohol drinking and smoking. The sensitivity analysis was also conducted by removing one study at a time and the rest analyzed to determine whether an individual study affected the aggregate result or not. Small study bias, consistent with publication bias, was evaluated by statistical tests .


The association between non-steroidal anti-inflammatory drugs (NSAIDs) and gastric cancer (GC) risk is controversial. The aim of this study is to evaluate the chemopreventive effect of NSAIDs for GC.A literature search was performed for relevant studies using the PubMed and Embase database (up to March 2016). Risk ratios (RRs) and 95% confidence intervals (CIs) were used as the effect measures. The dose–response analysis and subgroup analysis were also performed.Twenty-four studies were included. Our results indicated that NSAIDs could reduce GC risk , especially for non-cardia GC risk. Moreover, the dose-response analysis indicated the risk of GC decreased by 11% and 5% for 2 years increment of any NSAIDs and aspirin use, respectively. There were nonlinear relationships between the frequency of any NSAIDs use and aspirin use and GC risk (P for non-linearity<0.01), with a threshold effect of 5 times/week. A monotonically decreasing trend was observed only for the frequency of less than 5 times/week.Our results indicate that NSAIDs is inversely associated with GC risk, especially for non-cardia GC risk. NSAIDs use may become a feasible approach to prevent GC. Helicobacter pylori (H. pylori) infection and smoking, GC has a unsatisfying prognosis and still remains the third leading cause of cancer deaths  and corresponding 95% confidence intervals (CIs) could be extracted or calculated from published data, (4) the full text could be obtained. Only the most informative study was included if several duplicated studies were based on the same population. To retain maximum information, some data that only reported in excluded duplicated studies were extracted and added it into the included duplicated study.Two reviewers independently extracted following data: first author, publication country and year, study name, study design, definition of NSAIDs use, medication type, tumor site, sample size, duration and frequency of NSAIDs use, effect measures with corresponding 95% CIs, and adjusted variables. The study quality was assessed by Newcastle-Ottawa Scale criteria . Any disThe association between NSAIDs and GC risk was summarized by RRs with 95% CIs. The ORs provided by case-control studies were used as RRs in the pooled process because GC incidence was sufficiently low and the ORs were close to the RRs . If therA dose–response analysis was used to evaluate the relationship between duration and frequency of NSAIDs use and GC risk  62, 63], 6362, 62 statistic were used to measure heterogeneity [The Cochran Q test and the Iogeneity . If therogeneity –70.All statistical analyses were performed with Stata software . A two-sided P-value <0.05 was considered statistical significance.


Prostate cancer (Pca) is a serious disease associated with considerable morbidity and mortality. As a causative factor, the Asp148Glu polymorphism has been identified in the apurinic/apyrimidinic endonuclease (APEX1) gene. However, the association among Asians is considered controversial.Evidence for this association was obtained from the PubMed, Embase, HuGENet and Chinese National Knowledge Infrastructure (CNKI) databases. In the analysis, four models were applied. Associations between the APEX1 polymorphism and the invasiveness of Pca based on the Gleason score, prostate-specific antigen expression and clinical status were also evaluated.Seven articles were included in the analysis. Positive results were not only discovered in the pooled analysis, but also among patients of mixed descentand Asian descent. However, after considering the Hardy-Weinberg equilibrium (HWE), we observed only a 1.557-fold increase in Pca risk for subjects of Asian descent under the co-dominant model. Additionally, we did not also find any relationship between the APEX1 Asp148Glu polymorphism and invasive Pca risk.On the basis of the function of the APEX1 Asp148Glu polymorphism, recent studies, and our results, we suggest that the APEX1 Asp148Glu polymorphism might be important in stimulating the development of Pca rather than its invasiveness in various populations, especially for Asians. Prostate cancer (Pca) was one of the mostly frequently diagnosed malignant diseases worldwide. It is associated with considerable morbidity and is the second leading cause of cancer mortality in western countries –3. In 20via a hydrolytic mechanism on the 5′-side of abasic sites, thus specifically activating DNA repair  were considered. After re-reading the included studies, three of them were found to contain the necessary data and were analyzed , 22. Forhttp://www.power-analysis.com/). All P values were two-tailed, and data were analyzed using Stata 9.0 .Publication bias was evaluated with Egger's linear regression test and a funnel plot. The statistical power was calculated with Power and Precision V4 software (


PON1 variants with T2DM risk. We carried out a systematic search of PubMed, Embase, CNKI and Wanfang databases for studies published before June 2017. The pooled odds ratios (ORs) for the association and their corresponding 95% confidence intervals (CIs) were calculated by a random‐ or fixed‐effect model. A total of 50 eligible studies, including 34 and 16 studies were identified for the PON1 Q192R (rs662) and L55M (rs854560) polymorphism, respectively. As for the PON1 Q192R polymorphism, the 192R allele was a susceptible factor of T2DM in the South or East Asian population  but represented a protective factor of T2DM in European population  under a heterozygous genetic model. With regard to the PON1 L55M polymorphism, significant protective effects of the 55M allele on T2DM under the heterozygous  and dominant  genetic models were found in the European population, while no significant associations in the Asian populations under all genetic models (P > 0.05). In summary, by a comprehensive meta‐analysis, our results firmly indicated that distinct effects of PON1 genetic polymorphisms existed in the risk of T2DM across different ethnic backgrounds.Many studies have examined the associations between paraoxonase‐1 (PON1) genetic polymorphisms  and the susceptibility to type 2 diabetes mellitus (T2DM) across different ethnic populations. However, the evidence for the associations remains inconclusive. In this study, we performed a meta‐analysis to clarify the association of the two  The rise of diabetes prevalence poses one of the important challenges to global health. It is estimated that approximately 422 million adults were diagnosed with the disease in 2014 worldwide PON1 gene which maps to the long arm of chromosome 7 (q21‐22). It has been observed that serum PON1 activity has an important role in susceptibility and progression of T2DM Human paraoxonase‐1 (PON1) is a calcium‐dependent 45‐kD glycoprotein composed of 355 amino acids. The esterase is synthesized mainly by the liver and secreted into the circulation where it associates with high‐density lipoprotein (HDL) and assists in the antioxidant effect of preventing oxidation of low‐density lipoprotein (LDL). PON1 in human beings is encoded by the PON1 gene can significantly account for the catalytic ability of the enzyme. A missense SNP at position 192 (glycine (Q) to arginine (R) substitution) (rs662) is an important determinant of the PON1 activity PON1 Q192R polymorphism was the major determinant of individual variation in the ability of HDL in protecting LDL against lipid peroxidation. For example, the Q‐alloenzyme confers least ability Single nucleotide polymorphisms (SNPs) in the et al. first found that serum PON activity was significantly decreased in the patients with T2DM PON1 gene with susceptibility to T2DM. However, the previously published results remain controversial. Hence, to firmly elucidate the association between PON1 genetic polymorphisms  and the risk of T2DM, we conducted a systematic review and meta‐analysis of data from 50 studies and also established the association according to the ethnicity.As Ikeda e.g. ‘mutation’, ‘polymorphism’, ‘single nucleotide polymorphism’, ‘SNP’, ‘variant’, ‘variation’) in combination with TD2M . We supplemented this search by reviewing the cited references for all possible studies.A systematic search was conducted in the electronic databases PubMed, Embase, China National Knowledge Infrastructure (CNKI) and Wanfang Data, and all relevant articles were published in English or Chinese from their starting dates to June 2017. The search strategy used the following keywords relating to the paraoxonase‐1 gene  or variations (i) case‐control design, regardless of sample size; (ii) study assessing the associations between Q192R (rs662) and L55M (rs854560) of PON1 gene and type 2 diabetes; (iii) numbers for the PON1 genotypes could be available or calculated in case and control groups; and (iv) genotype distribution in the controls was in Hardy‐Weinberg equilibrium (HWE). If the two investigators  disagreed about the eligibility of an article, it was resolved by consensus with a third reviewer (M. Z. Liu).All identified abstracts were carefully reviewed by two investigators  independently for eligibility. The inclusion criteria were as follows: , who reached a consensus on all of the data extraction items. The following information was extracted from each study: name of the first author, publication year, country of the study, ethnicity of the population, genotype and allele distributions in case and control groups, and also sample size, mean age and gender distribution in case and control groups.P < 0.05. The pooled odds ratio (OR) with 95% confidence interval (CI) was used to evaluate the strength of association in the allelic, homozygous, heterozygous, recessive and dominant models, respectively. The statistical significance of the pooled estimates of the OR was determined by the Z test. The Cochran's Q test and I2 metric were performed to examine the possibility of between‐study heterogeneity. Heterogeneity was considered to be statistically significant at P < 0.05 for the Q statistic and I2 > 50% for the I2 metric P < 0.05 considered representative of significant publication bias. All statistical analyses were performed with STATA version 12.0 .The goodness‐of‐fit chi‐square analysis was used to test the HWE of the genotype distribution of controls. The distribution was considered deviated significantly from HWE with PON1 Q192R (rs662) and L55M (rs854560) polymorphism, respectively. The general characteristics of the studies included in the meta‐analysis are presented in Table The initial screening yielded 332 articles, and 1 article was found to be eligible by reviewing the cited references. A total of 111 articles were excluded because of duplicate publication. Then, 57 articles were excluded from screening based on the titles and/or abstracts. Finally, 37 articles PON1 Q912R polymorphism are summarized in detail in Table PON1 Q912R genetic polymorphism and T2DM under all genetic models: allelic , homozygous , heterozygous , recessive  and dominant .The results of the meta‐analysis of PON1 Q912R genetic polymorphism and T2DM presented in the South Asian subgroup  and East Asian subgroup (under four genetic models), while no significant associations were shown in the Canadian Aboriginal subgroup and in the European subgroup under the allelic, homozygous, recessive and dominant genetic models. By contrast, the significant association for the European subgroup under the heterozygous genetic model showed the 192R allele represented a protective factor of T2DM , but a risk factor for T2DM in South Asian subgroup.When we performed subgroup analyses stratified by ethnicity, the distinct effects in different ethnic populations were observed under all genetic models. Significant associations between PON1 L55M polymorphism are summarized in detail in Table PON1 L55M genetic polymorphism and T2DM did not reach statistically significant under the allelic genetic model , homozygous genetic model  and recessive genetic model . However, significant associations were found under a heterozygous genetic model  and a dominant genetic model .The results of the meta‐analysis of PON1 L55M genetic polymorphism. There were significant protective effects of L allele on T2DM in the European subgroup under the heterozygous  and dominant  genetic models, while no significant results were found in the South Asian, East Asian and Canadian Aboriginal subgroup under all genetic models.In subgroup analyses based on ethnicity, the distinct effects in different ethnic populations were also presented for the PON1 Q912R polymorphism under all of the genetic models . Subgroup analysis stratified by ethnicity indicated that heterogeneity was significantly reduced in the South Asian and East Asian subgroup, while was increased in the European subgroup. Therefore, ethnicity may be one of the sources of heterogeneity between studies for the PON1 Q912R polymorphism in the overall meta‐analysis.There was significant heterogeneity in the overall meta‐analysis of Because substantial heterogeneity still existed in the European subgroup under all genetic models, meta‐regression was used to explore the source of this heterogeneity. The following three covariates were taken into consideration: publication year, MAF  in controls and sample size in the subsequent meta‐regression Table . The resPON1 L55M polymorphism was showed under all genetic models . Subgroup analysis stratified by ethnicity also indicated that no substantial between‐study heterogeneity was found in the Asian subgroup  and in the European subgroup  under all genetic models.In contrast, no significant heterogeneity in the overall meta‐analysis of PON1 Q192R meta‐analysis . However, there was marginal significant publication bias for the homozygous genetic model (P = 0.047).Publication bias of the individual articles was evaluated by using the Begg's funnel plot Fig.  and Eggesis Fig. A, no obvPON1 L55R meta‐analysis  yet.For the sis Fig. B, there PON1 genetic polymorphisms and T2DM were conflicting in the previous studies. This is partly because some previous case‐control studies have been too small to be reliable. Thus, our meta‐analysis could overcome the limitations of single study by pooling the individual dataset and provide more reliable results.So far, the associations between PON1 Q192R polymorphism, no significant association, but strong between‐study heterogeneity, was observed. To address the substantial heterogeneity, we divided the total samples into four subgroups, that is white European, Canadian Aboriginal, South and East Asians. Stratified analyses by ethnicity yielded a significant association of the PON1 Q192R polymorphism with T2DM in South Asian and East Asian populations and, conversely, no association of the PON1 Q192R polymorphism with T2DM in European populations under the allelic, homozygous, recessive and dominant genetic models. In addition, the 192R allele was a susceptible factor of T2DM in the Asian population but represented a protective factor of T2DM in European population under a heterozygous genetic model.In the overall meta‐analysis of the PON1 L55M polymorphism, no significance between‐study heterogeneity was observed. The distinct effects across different ethnic backgrounds also presented in the subgroup analysis based on ethnicity. For example, significant protective effects of the 55M allele on T2DM under the heterozygous and dominant genetic models were found in the European population, while no significant results in the Asian populations under all genetic models. Interestingly, the associations of the two PON1 SNPs in our study were generally very similar in South and East Asians, although Asia is known to harbour genetically different origins PON1 SNPs and risk of T2DM, and no significant associations were found in all genetic models. Therefore, it was inferred that the 192R or 55M allele may decrease the risk of developing T2DM in European ancestry population, whereas the 192R increase the risk of T2DM in the South Asian and East Asian populations.In the overall meta‐analysis of the PON1 genetic variations and T2DM by a comprehensive meta‐analysis. The question remaining to be addressed is how the PON1 Q192R and L55M variants can exert an impact on T2DM with ethnic difference. One potential explanation is that different populations might have experienced very diverse lifestyle and environmental factors during their long‐period evolution. The PON1 activity may be influenced by several environmental and lifestyle impacts, such as cigarette smoking PON1 Q192R and L55M (rs854560) polymorphisms. Nevertheless, the precise mechanism deserves to be investigated in the future.To our knowledge, this is the largest study to underline the importance of ethnicity in the association between https://www.ncbi.nlm.nih.gov/variation/tools/1000genomes/), there are huge racial and regional differences in the distribution of the PON1 Q192R (rs662) and L55M (rs854560) genetic polymorphisms , which is significantly higher than in the South Asian populations (about 40%) and the European populations (<35%). For the PON1 L55M polymorphism, the M allele frequency is rare in the East Asian populations (<5%), which is significantly lower than in the South Asian populations (about 20%) and European populations (>30%). Such heterogeneous genetic backgrounds could be, at least in part, responsible for the heterogeneity of effect on the risk of T2DM detected in our overall population meta‐analysis. Furthermore, subgroup analysis stratified by ethnicity also indicated that the heterogeneity in the Asian group was significantly decreased.According to the included studies among different countries PON1 Q192R polymorphism in the European population subgroup. Meta‐regression was performed to evaluate the potentially important covariates exerting substantial impact on heterogeneity. Our findings have proved that the proportion of heterogeneity explained by the MAF in controls can reach as high as 93.06%. One of the reasons may be the small number of subjects in the control group. For example, the study of Elnoamany et al. PON1 Q192R was 0.213, while the study of Gokcen et al. PON1 Q192R was 0.5. Accordingly, studies with large sample size are needed to be investigated in the future.The meta‐analysis results in the current study should be interpreted with particular caution when large between‐study heterogeneity existed. Obvious heterogeneity was present in all the genetic models for the PON1 Q192R polymorphism meta‐analysis and 16 eligible studies for the PON1 L55M polymorphism, the populations were restricted to Asians, Europeans and Canadian Aboriginals. Studies from other populations should be conducted to confirm the findings. Last but not the least, the information about exposure to environmental substrates was not available in the included studies. This may explain some between‐study heterogeneity in our meta‐analysis. In addition, the gene×environment interactions are needed to be further evaluated in the future.There are some shortcomings in our current meta‐analysis. First, our included studies were limited to English and Chinese language, with some data published in other languages excluded, which may lead to some publication bias and thus affect the pooled results in the meta‐analysis. Second, although there are 34 eligible studies for the PON1 genetic polymorphisms (Q192R and L55M) play important roles in the risk of T2DM with distinct effects across European and Asian populations. Further studies from other populations are needed to confirm these results.In conclusion, we have firmly established that the The authors confirm that there are no conflicts of interest.


P < 0.05). In subgroup analysis, an inverse association between serum selenium levels and prostate cancer risk was found in each of case–control studies, current and former smokers, high-grade cancer cases, advanced cancer cases, and different populations. Such correlations were not found for subgroups containing each of cohort studies, nonsmokers, low-grade cancer cases, and early stage cancer cases. In conclusion, our study suggests an inverse relationship between serum selenium levels and prostate cancer risk. However, further cohort studies and randomized control trials based on non-Western populations are required.Some observational studies have shown that elevated serum selenium levels are associated with reduced prostate cancer risk; however, not all published studies support these results. A literature search of PubMed, Embase, Medline, and the Cochrane Library up until September 2016 identified 17 studies suitable for further investigation. A meta-analysis was conducted on these studies to investigate the association between serum selenium levels and subsequent prostate cancer risk. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the overall OR of prostate cancer for the highest versus the lowest levels of serum selenium. We found a pooled OR (95% CI) of 0.76 (0.64, 0.91;  Although much effort has been directed toward prostate cancer prevention, many aspects of its etiology are still unknown. To address this serious challenge, it is necessary to explore strategies that might reduce the incidence of prostate cancer.Prostate cancer is a common cancer in men, accounting for approximately 25% of all cancers, and has the second highest incidence of cancer in men worldwide.,4 and oxidative stress has been shown to be associated with the pathogenesis of prostate cancer. Excess production of free radicals or a deficiency in antioxidant defences can cause elevated oxidative stress, which in turn leads to cytoarchitecture and DNA damage. However, selenium can mitigate such damage by reducing free radicals. Selenium plays an important role in reproduction, acts as an antioxidant, and has antiaging activities. It is also implicated in many degenerative conditions, including inflammation, neurological disease, and cancer.Research has suggested that trace elements play an important role in the biological processes underlying prostate cancer. Selenium, an essential component of antioxidants, has attracted much attention, This was the first report to suggest that selenium deficiency might be related to cancer. Subsequent studies have consistently concluded that increased serum selenium levels are associated with a reduced risk of prostate cancer.–12 However, other observational studies have not found an inverse relationship between serum selenium levels and prostate cancer risk.–15 These inconsistent results may be partly because of differences in population, study design, smoking status, and other confounding characteristics of participants. Moreover, sample sizes were relatively small in each study, limiting the strength of evidence. To increase statistical power and clarify these conflicting results, a meta-analysis was conducted to assess the association between serum selenium levels and the risk of developing prostate cancer.A 1969 study suggested that cancer mortality in the United States was inversely correlated with the geographic distribution of selenium in the soil.22.1A database search was performed using PubMed, Embase, Medline, and the Cochrane Library and included literature up until September 2016. The search terms “serum selenium” or “plasma selenium,” and “prostate carcinoma” or “prostate cancer” were used either as a combination of free text or as medical subject heading (MeSH) terms. Additionally, further studies were identified within the reference lists of retrieved articles.2.2The following criteria were selected for inclusion of a study in the meta-analysis: the study reported the association between serum selenium levels and prostate cancer risk by comparing the risk for subjects with the highest serum selenium levels against the risk for subjects with the lowest serum selenium levels; the study had a cohort, case–control, or randomized controlled trial (RCT) design; the publication language was English; and where there were duplicate publications using the same study population or by the same authors, we included only the most recent publication.2.3RCTs were assessed for quality using the Cochrane Collaboration's “Risk of bias” tool. Cohort and case–control studies were assessed according to the primary criteria for nonrandomized and observational studies for meta-analyses, using the Newcastle-Ottawa Quality Assessment scale.2.4For each study, the following data were collected in a standardized data extraction form: first author's last name, year of publication, study design, study population, range of ages of subjects, sample size, odds ratio (OR) and 95% confidence interval (CI) of prostate cancer risk from the most fully adjusted model for the highest against the lowest levels of serum selenium, and quality scores.This study was a meta-analysis; as such, ethical approval was not required. All analyses were conducted by 2 independent authors.2.5Q and I2 statistics were used to assess heterogeneity across the included studies. Subgroup analysis was performed to identify the effect of different factors on the overall risk assessment. A sensitivity analysis was also conducted to investigate the influence of individual studies on the overall risk estimate. Publication bias was measured using a funnel plot and Egger test.,18 Differences with P values <0.05 were considered to be statistically significant.In the present study, statistical analyses were performed using STATA 12.0. The combined OR and corresponding 95% CI were used to estimate the relationship between serum selenium levels and prostate cancer risk. 33.1–15,19–29Figure According to the search criteria, we indentified 1352 articles for further investigation. However, most were excluded after reviewing titles, abstracts, or full-text, either because they were not relevant to our study, they were review articles, or there was some other reason. A total of 17 studies were selected for inclusion in our meta-analysis, within which there were 6136 prostate cancer cases and >34,901 controls or participants.,25,26,28 4 were cohort studies,,24,27,29 and 1 was a RCT. Ten studies were conducted using American populations,–13,19–25 1 Danish, 2 Swedish,,15 1 Iranian, 1 Finnish, and 2 were conducted using a mixed population from several European countries.,28 All ORs and corresponding 95% CIs were calculated by comparing the risk of prostate cancer associated with highest serum selenium levels against the risk associated with the lowest serum selenium levels. Table –15,19–29Among the 17 included studies, 12 were case–control,3.2,19,26,28 However, the results showed that there was an inverse relationship between serum selenium levels and prostate cancer risk. In other words, the population with higher serum selenium levels may have a lower subsequent prostate cancer risk. The pooled OR (95% CI) from all the studies was 0.76 ; however, we also found significant evidence of heterogeneity .Figure 3.3Removing 1 study at a time, the combined OR remained similar Fig. ; therefo3.4P = 0.127).The funnel plot and Egger regression test Fig.  showed t3.5Lastly, we conducted a subgroup analysis to assess the influences of study design, study population, and smoking status on the estimation of overall OR Table . Individ4 It is also an important component of 3 major proteins: selenoprotein-P, glutathione peroxidase (GPx), and albumin. Within GPx, selenium is part of the most important antioxidant enzyme system that prevents cellular injury. In addition, selenium inhibits the expression of some oncogenes and promotes apoptosis. Selenium is also part of the most important antioxidant enzyme system involved in preventing peroxidation of cells. Like vitamin E, selenium may be a superior scavenger of reactive nitrogen oxide species, and has the capacity to decrease inflammation. Selenium also inhibits cell proliferation and decreases cell cycle progression through the reduction of cyclin in prostate cancer cell lines.Our study shows that increased serum selenium is associated with a reduced risk of prostate cancer. Selenium is an antioxidant and anticarcinogen.; however, several studies presented conflicting results.,12,19 More recent studies have presented results that have supported those of Knekt et al. We hypothesized that the inconsistent conclusions from previous studies might be because of differences in study area, study design, sample size, follow-up time, age range of population, and quality of study. Therefore, we thought it timely to carry out a new meta-analysis of the data from these studies.The relationship between serum selenium and the risk of prostate cancer has been studied for many years. In 1990, a cohort study was conducted by Knekt et al that showed that a elevated serum selenium level was not associated with an increased prostate cancer risk However, the result of that study was unsurprising, given that serum selenium levels reflect long-term accumulation of selenium in the human body and selenium supplements may not have been adequately absorbed by the body. Moreover, the sample size was much larger in our study, suggesting a more credible result.Our study showed an inverse relationship between serum selenium levels and prostate cancer risk. This result was inconsistent with a previous study that assessed the relationship between selenium supplementation and prostate cancer risk.Despite the large sample size from the combined studies in our meta-analysis, there was strong evidence of heterogeneity. Even though we could not identify any clear sources of the heterogeneity, differences in the populations, study design, smoking status, grade and stage of cancer, and other varied characteristics of participants may at least partially explain this result.An inverse relationship between serum selenium levels and prostate cancer risk was found in the case–control studies but not in the cohort studies. This result was unsurprising because there were only a small number of studies in the cohort group. Moreover, most of these cohort studies did not find an inverse relationship to begin with.; however, many studies have suggested that other antioxidants, such as vitamin E, are protective against prostate cancer, particularly in smokers. Other studies have shown that the antioxidant effects of selenium observed in smokers may be enhanced by the presence of oxidative response elements in the promoter regions of genes encoding selenoenzymes.We also observed an inverse association between serum selenium and prostate cancer risk in smokers, but not in nonsmokers. Smoking is a risk factor for the incidence of prostate cancerThere were several strengths to our study. First, it was comprehensive in evaluating the association of serum selenium levels and prostate cancer risk because it included all relevant studies. Second, our study had a large sample size, thereby enhancing the statistical power and increasing the reliability of the results. Most importantly, we found a significantly inverse relationship between serum selenium levels and prostate cancer risk. Because serum selenium is a broad indicator of selenium in the diet, our study suggests that increased selenium intake might help prevent the development of prostate cancer. Our study supports the hypothesis that there is a relationship between serum selenium levels and prostate cancer risk in populations with long-term steady selenium intake. However, selenium measurements in toenail samples and other biomaterials are needed to evaluate short-term and transient changes in selenium intake. Second, there were residual confounders and unmeasured factors present in each of the included studies. Adjustments were made for these factors within each study, but the adjustments were not completely consistent between studies. Residual confounders may alter the measured effect of selenium on the risk of cancer. For example, men with long-term vitamin C supplementation have a 21% reduced risk of prostate cancer. Third, there was strong evidence of heterogeneity among the included studies. Although differences in populations, study design, smoking status, grade, and stage of cancer may explain this heterogeneity, other differences present in the studies should also be considered. For example, there may be measurement errors arising from the use of different methods, and facilities and staff involved in the studies may bias estimates of effect. Fourth, although cohort studies and RCTs are generally considered best for investigating effect, few such studies have been conducted to evaluate the association between serum selenium levels and prostate cancer risk. Finally, the studies included in our analysis primarily investigated Western populations, in particular Americans and Europeans. Therefore, further studies investigating other populations should be carried out in the future.The present meta-analysis has several limitations. First, we only evaluated serum selenium levels. The serum selenium reflects long-term selenium intake and is relatively accurate in ranking selenium intake in population studies.5Our meta-analysis suggests that there is an inverse relationship between serum selenium levels and subsequent prostate cancer risk. Further investigations using well-designed cohort studies and RCTs based on non-Western populations are required.


N-methyltransferase (HNMT) gene has been associated with the risk of developing PD by several studies but not by some others. We carried out a systematic review that included all the studies published on PD risk related to the rs11558538 SNP, and we conducted a meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.Several neuropathological, biochemical, and pharmacological data suggested a possible role of histamine in the etiopathogenesis of Parkinson disease (PD). The single nucleotide polymorphism (SNP) rs11558538 in the histamine Meta-DiSc 1.1.1 to perform the meta-analysis of the eligible studies, and the Q-statistic to test heterogeneity between studies.We used several databases to perform the systematic review, the software HNMT rs11558538 SNP and the risk for PD . The frequency of the minor allele positivity showed a statistically significant association with a decreased risk for PD, both in the total series and in Caucasians. Although homozygosity for the minor allele did not reach statistical significance, the test for trend indicates the occurrence of a gene–dose effect. Global diagnostic odds ratios  for rs11558538T were 0.61 (0.46–0.81) for the total group, and 0.63 (0.45–0.88) for Caucasian patients.The meta-analysis included 4 eligible case–control association studies for the HNMT rs11558538 minor allele is related to a reduced risk of developing PD.The present meta-analysis confirms published evidence suggesting that the  HRH3 is implicated in neurotransmitter release in the central nervous system. Histidine decarboxylase is the enzyme responsible for the synthesis of histamine (from its precursor histidine), whereas histamine N-methyltransferase (HNMT) and diamine oxidase (or ABP1) are the responsible enzymes in inactivating histamine, respectively, in the brain and in the peripheral tissues (revised in Ref.).Histamine is stored and released in the brain, mainly in mast cells and histaminergic neurons of the tuberomammilary nucleus of the posterior basal hypothalamus. Histaminergic fibers project from this nucleus to many regions of the brain, including the striatum, thalamus, cerebral cortex, hippocampus, and amygdale.substantia nigra of rats, recent neuropathological, biochemical, and pharmacological data arisen from studies in patients with Parkinson disease (PD), and in experimental models of parkinsonism, which are summarized in Table –24Together with the demonstration that histamine infusion could induce neuronal death and inflammatory phenomena in the HNMT gene , which causes the amino acid substitution Thr105Ile (related to decreased enzyme activity), has been the matter of several case–control association studies trying to establish its association with the risk of developing PD. However, the results of studies addressing this association have been controversial. For this reason, we performed a systematic review and a meta-analysis of eligible studies, including an estimation of the genetic association of each study and of the pooled data, and investigated the heterogeneity between studies.The single nucleotide polymorphism (SNP) rs11558538, located in the exon 4 C314T of the 22.1http://archive.pdgene.org/). The search using these databases showed 6 case–control association studies on rs11558538 SNPs in the HNMT gene and the risk for PD.–30 However, we excluded from the review and meta-analyses 2 studies included in the PD Gene Data Base because the genotype and allele frequencies of the analyzed SNP were not available in the respective reports.,27 Therefore, only 4 case–control studies were included in the final meta-analysis.,28–30Figure 2.2HNMT rs11558538 genotype, genotyping method, and demographics, and we calculated allele frequencies, from each study. We also analyzed the statistical significance of the association of HNMT rs11558538 alleles and the risk of developing PD for each study to avoid statistical inconsistencies, and indicated all associations as diagnostic odds ratios (ORs) with their corresponding 95% confidence intervals (CIs). Fixed effects of the pooled OR, as well as random pooled OR effects, were estimated, based on individual ORs.We extracted the following information: journal, publication year, first author, number of cases and controls for each 2.3Meta-DiSc 1.1.1 . The Mantel–Haenszel and the DerSimonian–Laird methods were used, respectively, to calculate the global diagnostic OR when no heterogeneity was observed and when statistically significant heterogeneity existed.The meta-analyses of the eligible case–control studies regarding association between rs11558538 SNP and PD risk were carried out by using the software  Heterogeneity was considered significant when P < 0.10, and was quantified by using the I2 metric (I2 = [Q] degrees of freedom [d.f.])/Q), which is independent of the number of studies included in the meta-analysis. I2 takes values between 0% and 100%, with higher values denoting greater degree of heterogeneity. We also calculated the statistical power for the pooled sample of the eligible studies.The Q-statistic was used to test heterogeneity between studies.Because this study is a systematic review and meta-analysis, ethical approval was not needed. This work was elaborated according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.3HNMT rs1155858 SNP and the risk for PD . The genotype distribution and the minor allele frequencies from patients with PD and control groups in the eligible studies are summarized in Tables The meta-analysis included a total of 4 eligible studies analyzing the association between the HNMT rs11558538 and the risk for PD, both in the total series and in the series confined to Caucasian populations  showed a significant association between ns Table A and B, HNMT rs11558538 and the risk for PD, both in the total group . For overall (Caucasian and Asian) patients the power is equal to 99.6% for 1-tailed association and 99.0% for 2-tailed association, and for Caucasian patients it was 97.9% for 1-tailed association and 95.7% for 2-tailed association.The statistical power for the presence of the SNP analyzed in this study was determined from the variant allele frequencies observed in control individuals with a genetic model analyzing the frequency for carriers of the disease gene with a relative risk value = 0.65 . Data suggesting the possible implication of histamine , the strongest associations related to polymorphisms being in the HNMT gene and the increased risk for PD. Two further studies, 1 involving Caucasian patients and other involving Asian patients, showed similar results, whereas another group reported lack of association. Case–control association studies on other histamine-related genes showed lack of association between the ABP1 His645Asp polymorphism, the nonsynonymous HRH1 SNP designated as rs2067470 (Leu449Ser), and the promoter HRH2 SNP designated as rs2067474 (G1018A) polymorphisms and the risk for PD.Our group described an association between the major allele of the rs1155838 SNP in the HNMT rs11558538 SNP in patients with PD than in controls, both in the allele positivity analysis and in the comparison of minor allele frequencies, whereas the association of HNMT rs11558538TT homozygosity with PD risk did not reach statistical significance because of the low frequency of the homozygous genotype. Nevertheless, the high significance of the test for trend with the number of minor alleles  to the N∊2 atom of the imidazole ring, which results in the production of the histamine inactive metabolite N-methylhistamine and S-adenosyl-l-homocysteine (AdoHcy). Pang et al showed, using a theoretical 3D model of human HNMT, that the polymorphic residue Thr105Ile is located in the turn between an α helix and a β strand on the protein surface away from the active site of HNMT, and that the presence of Ile105 caused destabilization of folded HNMT, leading to the formation of a misfolded protein that is cleared by proteasomes, and therefore to a decreased enzymatic activity. The decreased activity of HNMT in patients carrying the rs11558538 minor allele should hypothetically lead to an increase in brain histamine levels, an increase in brain mRNA levels of HNMT, or both. The results of the present meta-analysis suggest that decreased histamine metabolism in the central nervous system should play a protective role against development of PD.The mechanism by which HNMT inactivates histamine consists in the transference of a methyl group from HNMT rs11558538 SNP and PD risk that fulfill inclusion criteria, our data point at a protective role of the HNMT rs11558538T variant on the risk of developing PD , and give support to the hypothesis of a possible role of histamine in the pathogenesis of this disease.Despite the fact that our study has as the main limitation the relatively low number of studies on the association between


Results from publications on inflammatory markers of C-reactive protein (CRP), interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) and risk of colorectal adenomas are not consistent. A meta-analysis was conducted to explore the above-mentioned associations. Relevant studies were identified by a search of Embase, Medline and PubMed through February 2016. A random effect model was adopted to combine study-specific odds ratio (OR) and 95% confidence interval (95% CI). Between-study heterogeneity and publications bias were assessed. Dose–response relationships were assessed by restricted cubic splines. Nineteen observational studies were included. For highest vs. lowest levels, results from this meta-analysis did not support an association between circulating levels of CRP [OR (95% CI): 1.15 (0.94-1.40)], IL-6 [1.17 (0.94-1.46)] and TNF-α [0.99 (0.75-1.31)] and risk of colorectal adenomas, respectively. The findings were supported by sensitivity analysis and subgroup analysis. In dose-response analysis, the risk of colorectal adenomas increased by 2% [1.02 (0.97-1.08)] for each 1 mg/L increment in circulation CRP levels, 9% [1.09 (0.91-1.31)] for each 1 ng/L increment in circulation IL-6 levels, and 6% [1.06 (0.93-1.21)] for each 1 pg/mL increment in circulation TNF-α levels. Moderate between-study heterogeneity was found. No evidence of publication bias was found. Circulation levels of CRP, IL-6 and TNF-α might be not useful biomarkers for identifying colorectal adenomas, respectively. If data were duplicated in more than one study, we included the study with the most recent one; otherwise, the one with the most number of cases was included.Two investigators (ZXQ and LSL) independently reviewed all identified studies, and studies were included if they met the following criteria: (i) an observational study published as an original study; (ii) the exposure of interest was circulating levels of CRP, IL-6 or TNF-α; (iii) the outcome of interest was colorectal adenomas  and (iv) relative risk or odds ratio (OR) with 95% confidence interval (CI) were provided , or mean and standard deviation were available from which an OR could be calculated . Information was recorded as follows: the first author's last name, publication year, number of cases and participants, measurement of exposure, country where the study was performed, variables adjusted for in the analysis, OR estimates with corresponding 95% CI of colorectal adenomas. For dose–response analysis, the number of cases and participants (person-years) and OR (95% CI) for each category of CRP, IL-6 and TNF-α were also extracted. We extracted the ORs that reflected the greatest degree of control for potential confounders.http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp, accessed 4/21/2016).Pooled measure was calculated as the inverse variance weighted mean of the logarithm of OR with 95% CI to assess the strength of association. OR (95% CI) was calculated with the mean and standard deviation if it was not provided. A random-effect model was used as the pooling method, which considers both within-study and between-study variation. The I2 was used to assess heterogeneity, and I2 values of 25, 50 and 75% represent low, moderate and high heterogeneity, respectively . PublicaFor dose–response analysis, a two-stage random-effects dose–response meta-analysis  was perf


To combine the data from previously conducted studies about the associations between miR-608 rs4919510 polymorphism (C>G) and breast cancer risks.2 statistic. Publication bias was analyzed using contour-enhanced funnel plots.According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review of the related literatures searched from PubMed, Embase, Cochrane Library, Web of Science, and China National Knowledge Internet (CNKI) (time: ~ December 2016). Using DerSimonian-Laird random-effects models [Pooling Model: Mantel Haenszel (MH)], odd ratios (ORs) with 95% confidence intervals (95% CIs) were estimated in the allele model, homozygote model, heterozygote model, dominant model and recessive model. Heterogeneity was analyzed using Labbr plots and IWe included 5 eligible studies with 7948 patients. The ORs and their 95% CIs in the 5 genetic models mentioned above were 1.009 , 1.098 , 1.076 , 1.043 , 1.007 , respectively.In the present meta-analysis, no relationships between miR-608 rs4919510 polymorphism (C>G) and the risk of breast cancer were found. More studies are warranted to further validate the conclusion. As one of the malignancies with the highest incidence and mortality rates globally, breast cancer accounts for more than a million cases every year, 2. In NMicroRNAs, as gene expression regulators, regulate a variety of biochemical processes, such as apoptosis, proliferation, metabolism, cellular differentiation, and cancer development–6. It haTwo authors (XK and JW) independently searched the database of Embase, PubMed, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), and Web of Knowledge (time: ~ December 2016). Search terms used separately or in combination were: “breast carcinoma or breast cancer” and “rs4919510 or miR-608” and “mutation or variant or polymorphism”. Detailed searching strategies with the start and end date of searches were listed in According to the inclusion criteria set in According to the methodological quality assessment scale see , which w2 statistic  software. The Stata commands is metan.According to PRISMA statement, a study selection flowchart was reported in A total of 35 studies were identified: 7 in Pubmed, 7 in Embase, 0 in Cochrane Library, 14 in Web of Science and 7 in CNKI . FinallyThe main results including heterogeneity tests, effect models adopted accordingly, and the pooled OR with 95% CI and P value of this meta-analysis were shown in Sensitivity analysis demonstrated that the pooled ORs were not affected by deleting every single study . The conhttp://www.gopubmed.com.Recently, gene polymorphisms which may contribute to the tumorigenesis of breast cancer have attracted more and more scholars’ attention. Some geRecently, rs4919510 polymorphism in miR-608 has been reported to predict clinical outcomes for cancer patients in different cancer types. Hashemi et al. evaluated the impact of miR-608 rs4919510 C>G variant on the breast cancer risk. HoweverA single study cannot be sufficient enough to confirm the correlation between miR-608 rs4919510 polymorphism and breast cancer risks convincingly, especially for small-sample-size studies. Given this, Pubmed, Embase, Cochrane Library, Web of Science, and CNKI databases were combined to further analyze the associations. The results of our study failed to demonstrate any significant correlation. This analysis is the most updated one to provide an evaluation of the correlations between miR-608 rs4919510 polymorphism and breast cancer risks.On a contour-enhanced funnel plot, “if the area where studies are perceived to be missing are areas of high statistical significance (the right part of the funnel plot), then publication bias isn’t the cause of funnel asymmetry”. In the 2 are wide, inferences about the heterogeneity extent should be cautious, thus, calculating the confidence intervals for I2 is important for estimating the heterogeneity if the number of included studies are large enough. However, since the present study is only a small meta-analysis, and we used DerSimonian-Laird random-effects models for all the analyses of all the 5 genetic models, we did not calculate the confidence intervals. After all, Cochran Q (i.e. chi-square) is somewhat underpowered to detect heterogeneities, especially for small meta-analyses; thus, we only used the I2 statistic as a rough reflection; (6) Regarding heterogeneity estimates, all these estimates are very likely off, especially for small meta-analyses, and we should be wary about homogeneity assumptions. In this smaller meta-analysis, we failed to identify any heterogeneity, which might exist. In addition, since fixed effect models might underperform in the presence of any heterogeneity, while DerSimonian-Laird random-effects models are more conservative and able to provide better estimates with wider confidence intervals, we adopted the latter for all the analyses of all the 5 genetic models; (7) Publication bias tests and plots only relevant if >10 studies are included otherwise underpowered to detect much and tend to lead to conclusions that are not justified. In the present study, we don’t have enough studies to assess, which is another limitation.Several limitations existed in our study: (1) Included studies were relatively insufficient to do subgroup-analyses; (2) The effect of gene-environment interactions and gene-gene interactions was not emphasized; (3) More accurate ORs should be adjusted by patient factors such as gender, age, living styles, medication consumption and other exposure factors; (4) Only published articles were included, the unpublished and ongoing studies could convert our result; (5) When the 95% confidence intervals around IIn conclusion, our results suggested that miR-608 rs4919510 polymorphism may not be associated with the susceptibility of breast cancer.S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 Table(DOC)Click here for additional data file.


Stratified analysis by ethnicity showed that the relationship is stronger and more stable in Asians. In summary, our current work indicated that APOBEC3 copy number variations might have a good screening accuracy for breast cancer.Recently, a deletion in the human apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) gene cluster has been associated with a modest increased risk of breast cancer, but studies yielded inconsistent results. Therefore we performed a meta-analysis to derive a more precise conclusion. Six studies including 18241 subjects were identified by searching PubMed and Embase databases from inception to April 2016. Pooled odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were evaluated under allele contrast, dominant, recessive, homozygous, and heterozygous models. All the analyses suggested a correlation of APOBEC3 deletion with increased breast cancer risk (D  Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females worldwide . AccumulThe discovery of submicroscopic copy number variations (CNVs) present in our genomes has changed dramatically our perspective on DNA structural variation and disease. It is now thought that CNVs encompass more total nucleotides and arise more frequently than SNPs. CNVs may account for 13% of the human genome and have been supposed to explain some of the missing heritability for complex diseases after the findings from GWASs .Recently a deletion in the APOBEC3 gene cluster was identified , 18. ThiFor the process of eligible studies’ identification and selection, 16 publications were initially retrieved from PubMed and Embase databases. After further screening according to the inclusion and exclusion criteria, 6 relevant reviews and 4 molecular mechanism research studies were excluded. Finally, a total of 6 case-control studies with 18241 subjects were identified to be eligible for this meta-analysis –24. The Finally, 6 epidemiological individual studies including 8783 cases and 9458 controls were enrolled in this meta-analysis. All studies reported detailed number of three genotypes Insertion/Insertion (I/I), Insertion/Deletion (I/D), Deletion/Deletion (D/D). To be comprehensive, the correlation of APOBEC3 CNVs with breast cancer risk was analyzed by five different comparison models: allele contrast, dominant, recessive, homozygous, and heterozygous.vs I: OR = 1.29, 95% CI = 1.23-1.36)  Figure . For thevs I/I: for total, OR = 1.34, 95% CI = 1.26-1.43; for Asians, OR = 1.40, 95% CI = 1.30-1.51; for Caucasians, OR = 1.20, 95% CI = 1.06-1.35)   Figure . Similar) Figure .vs I/D+I/I) and homozygous model (D/D vs I/I). After the exclusion, positive results were only found in Asians but not in Caucasians    Figure .Sensitivity analysis was conducted by deleting one study at a time to examine the influence of individual study to the pooled ORs. No single study materially altered the pooled ORs when they were sequentially deleted, suggesting that our results were stable and robust (data not shown).P-values from the Egger's test and the Begg's test were listed in Table The funnel plot revealed no obvious publication bias with a symmetrical distribution of study results around the pooled measurement of effect, indicating that publication bias was generally not a factor influencing the results Figure . Egger'sThe APOBEC3 gene family, including APOBEC3A, APOBEC3B, APOBEC3C, APOBEC3D, APOBEC3E, APOBEC3F, APOBEC3G, and APOBEC3H, plays pivotal roles in intracellular defense against viral infections , 26. The+ breast cancer, which strongly suggests that genetic aberrations induced by APOBEC3B contribute to breast cancer progression [Up to now, emerging studies support a positive association between APOBEC3 CNVs and cancer risk , 33, pargression . Additiogression .Herein we performed a comprehensive databases search for all the eligible studies that reported the association between APOBEC3 CNVs and breast cancer risk. After pooling all the available data, we got a conclusion that the APOBEC3 deletion mutation significantly increases the risk of breast cancer, and the results are especially stable in Asians. OR (95% CI) of 1.29 (1.23-1.36) associated with deletion allele compared with no deletion allele strongly suggested a positive relationship between APOBEC3 deletion and breast cancer risk. And generally, consistent results were observed under the other four genetic models. When assessing by the homozygous and hetarozygous model, APOBEC3 deletion was also significantly associated with breast cancer risk, with OR (95% CI) of 1.28 (1.19-1.36) associated with one-copy deletion and 1.75 (1.56-1.95) associated with two-copy deletion compared with subjects with no deletion. The results present a possibility that the deletion copy number may be directly proportional to the breast cancer susceptibility.In particular consideration of the influence of ethnicity, we conducted stratified analysis by ethnicity. Notably, the results showed that the relationship is weaker in Caucasians than in Asians. The ORs in Caucasian subgroup were always lower than those in Asian subgroup, and results in recessive model and homozygous model analysis revealed no statistical significance. Although analysis by other three genetic models showed positive results, we cannot convincingly conclude that APOBEC3 deletion would confer risk for breast cancer in Caucasian populations from the current assessment. More studies with large sample size in Caucasian populations are warranted to verify our results.Our work has several strengths. Above all, this is by far the first meta-analysis evaluating the association between APOBEC3 CNVs and breast cancer risk. And it was comprehensively analyzed by five different comparison models. Besides, all the included studies were of high quality with NOS scores ranged from 8-9 score, which is critical for the reliability of our pooled results. What's more, no obvious heterogeneity was observed in all the analysis by five models and the ethnicity subgroup analysis further reduced the heterogeneity. Also, sensitivity analysis indicated no study to be deleted and no evident publication bias was detected. All these points significantly increased the statistical power of our analysis.Despite its strengths, some limitations should be taken into consideration. Firstly, three of the included studies were based on a relatively small sample of less than 500 subjects and Long's study with 11622 subjects weights much higher than others. Secondly, only literatures in English were included in our study. Finally, many other factors could influence our analysis, such as distinct covariant factors, various genotyping methods among studies and non-coincident baseline characteristics of different samples. All of these potential discrepancies interfere with the standardization of our pooled data, but we were unable to conduct further stratified analyses for lack of detailed information. Thus, further studies investigating this issue should consider the factors mentioned above.In summary, our current work indicates that a high copy number of APOBEC3 deletion confers risk for breast cancer, suggesting a possibility that APOBEC3 CNVs has a good screening accuracy for breast cancer.Potentially eligible articles were obtained through searching PubMed and Embase databases up to April 2016. The literature search was performed using free-text words combined with Medical Subject Headings (MeSH). Gene-specific terms  were combined with polymorphism-specific terms (polymorphism or polymorphisms or variation or variations or variant or mutation or mutations or genotype or genotypes) and disease-specific terms (breast cancer or breast cancers) to retrieve eligible studies. References from retrieved articles were further screened manually for other potentially available reports.Inclusion criteria for studies were the following: (1) case-control or cohort study design; (2) evaluating associations between APOBEC3 gene deletion and breast cancer risk; (3) providing OR estimates with 95% CIs or sufficient data for calculation; (4) published in English; and (5) performed on humans. Exclusion criteria were the following: (1) reviews and comments; (2) insuffient data for calculation; (3) performed on animals; and (4) duplication of a previous publication.Data extraction was performed independently by two investigators (Y. Han and Q. Qi) and disagreements were adjudicated by a third reviewer (Q. He). For each study, general characteristics such as the first author, publication year, country and ethnicity of patients, sample size, and genotyping method were collected.http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp; maximum score = 9 points) was used to evaluate the methodological quality, which scored studies based on the selection of patients, the comparability of the groups, and the quality of the sampling process. A study awarded a score of 0-3, 4-6, or 7-9 was considered as a low-, moderate-, or high-quality study, respectively. Two authors (Y. Han and Q. Qi) independently assessed the study quality, and inconsistency was discussed with another reviewer-author (Q. He), who acted as an arbiter.The Newcastle-Ottawa Scale and Agency for Healthcare Research and Quality . All P values were two sided and P-values < 0.05 were considered statistically significant.To obtain a more comprehensive assessment of associations between APOBEC3 deletion and breast cancer risk, five different comparison models were used: allele contrast, dominant, recessive, homozygous and heterozygous. Risk estimates were expressed as ORs and 95% CIs. Heterogeneity arising from pooled individual studies was examined by the