The aim of the current study was to determine the contributions of several common mutations in the Mediterranean fever (MEFV) gene, namely, E148Q, M680I, M694V and V726A, to ankylosing spondylitis (AS) susceptibility.Two investigators independently searched the literature regarding the association of MEFV with AS in the PubMed, EMBASE, Web of Science, and Scopus databases. They independently selected eligible articles and then extracted data from the included studies. The associations between MEFV mutations and AS risk were assessed with odds ratios (ORs) and 95% confidence intervals (95% CI). Further analyses were conducted with STATA 12.0 software .Four mutations  were genotyped in 869 AS cases and 879 controls from the 8 eligible studies. Of the four mutations, M694V  was found to be associated with AS through overall analysis. However, the other mutations demonstrated no relation with AS . No significant publication bias was discovered in the meta-analysis.The present study indicates that the MEFV M694V mutation may contribute to the pathogenesis of AS. The associations between the other mutations and AS need to be validated with more relevant and well-designed studies. Ankylosing spondylitis (AS) is a chronic inflammatory disease involving the axial skeleton, and its main clinical manifestations are back pain and progressive stiffness of the spine. AS typically develops in young adults with a peak age of onset between 20 and 30 years. Many AS patients have poor outcomes, and they may gradually progress to spinal fusion with hyperkyphosis. Patients develop work disability  and an iThe Mediterranean fever (MEFV) gene is located on the short arm of chromosome 16 and is known to be responsible for familial Mediterranean fever (FMF). FMF is a hereditary autoinflammatory disorder that is characterized by recurrent episodes of fever and serositis. Enthesopathy and sacroiliitis occur in some FMF patients –25, and A comprehensive literature search was performed in the PubMed, EMBASE, Web of Science, and Scopus databases up to the date of December 31, 2016. Full text searches were used in the PubMed, EMBASE and Scopus databases, while a medical subject headings (MeSH) search was applied in the Web of Science database. The keywords were “ankylosing spondylitis” and “MEFV”. No restrictions were imposed on the type of studies. The study selection process is illustrated in The included studies met the following criteria: 1) articles published before Dec 31, 2016; 2) case-control studies concerning the correlation between MEFV mutations and AS; and 3) studies with adequate data that allowed for the calculation of ORs with 95% CIs. The exclusion criteria were as follows: 1) case reports or case series; 2) studies without controls; 3) studies without available data; and 4) duplicate studies.The following items were extracted independently by two researchers (Linqing Zhong and Wei Wang): 1) characteristics of included studies, i.e., the title, the first author, publication year, sample size, study population, and genotyping methods; and 2) the frequencies of each MEFV mutation  in the AS patients and controls. Discrepancies between these two investigators were resolved by discussion or consultation with a third researcher (Hongmei Song).The two researchers (Linqing Zhong and Wei Wang) independently evaluated the qualities of the included studies with the Newcastle Ottawa Scale (NOS) . The NOS2 statistic . A fixed-effects model (the Mantel-Haenszel method) was employed when I2<25%, otherwise a random-effects model (the Mantel-Haenszel method) was used. Begg’s funnel plots and Egger’s test were applied to assess the risk of publication bias, and the p-value was set at 0.10. Sensitivity analysis was implemented to determine the influence of each study on the pooled OR. The Hardy–Weinberg equilibriums (HWIs) of the controls were assessed with the STATA software. P-values < 0.05 were considered statistically significant. Subgroup analyses concerning the different populations were not involved in this study.The meta-analysis was performed with STATA 12.0 software . The relevance of the MEFV mutations with AS was assessed with the pooled ORs and 95% CIs. The heterogeneity between studies was estimated with the Q-test  and the IA total of 314 articles were acquired from 4 databases . A total of 297 articles were initially excluded after review of the titles and abstracts; of these, 82 were duplicate articles and 215 were not related to the relevant topic. The remaining 17 articles were reviewed in full text, and then 5 meeting reports were excluded. Among these 5, 4 were conducted by the same researchers as the rest of the studies, and the full text of one article was not available. Ultimately, one case report and 3 studies without control groups were ruled out. Finally, eight eligible case-control studies with 869 cases and 879 controls were included in the present meta-analysis. The characteristics of each study are presented in 2 statistics; therefore, a fixed-effects model was adopted for the analysis of the association of E148Q with AS susceptibility .The association of E148Q with the risk of AS was investigated in 7 independent studies. The frequency of E148Q was 65 of 1338 alleles in the AS patients (4.86%) and 54 of 1358 alleles in the controls (3.98%). No significant heterogeneity was identified by the Q-test and IAll of the included studies explored the relationship between M680I and AS. The M680I incidence rates were 23/1738 (1.32%) and 19/1758 (1.08%) in the AS patients and controls, respectively. A fixed-effects model was applied to estimate the relevance of the association of M680I with AS, and no significant difference was found between the groups .All eligible studies assessed risk of AS in association with M694V. The M694V mutation occurred at a distinctly higher frequency in the AS patients  than in the controls . A fixed-effects model was used to estimate the overall OR and 95% CI because no significant heterogeneity was found. The result suggested that M694V might be a risk factor for AS . A forest plot of the association between the M694V mutation and AS is presented in The connection between V726A with AS was also evaluated in all eight studies. However, one study was excluded from the meta-analysis because it had the same incidence rate for both groups. No significant statistical correlation was discovered  with a fixed-effects model. The frequency of each mutation in the cases and controls are shown in A Begg’s funnel plot was created to recognize potential publication bias. No significant asymmetry was discovered in the funnel plot Figs –6. Next,pyrin, is involved in the assembly of the inflammasome, which is a protein complex that leads to the cleavage and activity of caspase-1 and ultimately results in the activity of the pro-inflammatory cytokine IL-1. Mutations in the MEFV gene are gain of function and thus aggravate inflammatory reactions [MEFV was originally identified as a candidate gene for familial Mediterranean fever , 37. Itseactions . Associaeactions –42.A whole-genome linkage scan detected a linkage between ankylosing spondylitis and chromosome 16p , where MIn this meta-analysis, 8 eligible case-control studies with 869 cases and 879 controls with M680I/M694V and 7 studies with 669 cases and 679 controls with E148Q/V726A were analyzed. Consistent with a previous meta-analysis concerning Behçet's disease , a positTo our surprise, the M694V heterozygous mutation was found in two healthy Chinese people. This is inconsistent with the conclusion of the 1000 Genome Project in which the M694V mutation was not discovered in the Chinese population. However, Chinese participants in the 1000 Genome Project were restricted to Xishuangbanna, Beijing, and southern China, while the study of He C  concentrAnother meta-analysis was published concerning the relationship between MEFV and AS . HoweverIn summary, the current meta-analysis established the potential contribution of the MEFV gene mutation, M694V, to the pathogenesis of ankylosing spondylitis. However, more studies with diverse ethnicities are necessary to validate and extend these conclusions.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 Table(XLS)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(DOCX)Click here for additional data file.


Different confounder adjustment strategies were used to estimate odds ratios (ORs) in case-control study, i.e. how many confounders original studies adjusted and what the variables are. This secondary data analysis is aimed to detect whether there are potential biases caused by difference of confounding factor adjustment strategies in case-control study, and whether such bias would impact the summary effect size of meta-analysis.We included all meta-analyses that focused on the association between breast cancer and passive smoking among non-smoking women, as well as each original case-control studies included in these meta-analyses. The relative deviations (RDs) of each original study were calculated to detect how magnitude the adjustment would impact the estimation of ORs, compared with crude ORs. At the same time, a scatter diagram was sketched to describe the distribution of adjusted ORs with different number of adjusted confounders.Substantial inconsistency existed in meta-analysis of case-control studies, which would influence the precision of the summary effect size. First, mixed unadjusted and adjusted ORs were used to combine individual OR in majority of meta-analysis. Second, original studies with different adjustment strategies of confounders were combined, i.e. the number of adjusted confounders and different factors being adjusted in each original study. Third, adjustment did not make the effect size of original studies trend to constringency, which suggested that model fitting might have failed to correct the systematic error caused by confounding.The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium associations so that the direction of causal inference would be even reversed. Therefore, further methodological researches are needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind of bias into consideration when drawing conclusion based on summary estimation of meta-analyses.The online version of this article (10.1186/s12874-017-0454-x) contains supplementary material, which is available to authorized users. Meta-analysis is a widely used statistical technique to synthesize results of several independent homogeneous primary studies . When reIn recent years, meta-analysis has been widely used in combining estimations of other types of studies, including cross-sectional study, cohort study and case-control study . When thConfounding is a kind of important bias in observational studies, especially in case-control study. The common used confounding control strategies include limiting included subjects, matching important confounding factors in study design, as well as stratification, adjustment and propensity scores in analysis phase. Logistic regression model is widely used to adjust confounders in research practice, which is flexible to control multiple confounders simultaneously.In theory, overall consideration and adjustment of potential confounders make the estimation of effect size closer to the true effect value better. However, the difference of model building and fitting may lead to ambiguous adjusted results, which make uncertain bias occur in pooling analysis , 11. AltOur aim is to explore possible bias caused by confounder adjustment strategy in case-control study, i.e. how individual studies deal with confounders and how the difference of strategies would impact the summarized effect size of meta-analysis. As an example, the studies focused on the association between breast cancer and passive smoking among non-smoking women, in which ORs varies from 1.5 to 2.0. The reasons behind why we selected this example include: (1) numbers of relevant case-control studies which had been conducted in different context ; (2) the existed results shown that there was indeed positive association between passive smoking exposure and breast cancer development ; (3) theMeta-analyses focused on passive smoking and breast cancer were identified through three English databases  and three Chinese databases , using terms “passive smoking”, or “tobacco”, or “environmental tobacco smoke or its’ abbreviation of ETS”, combined with “breast neoplasms”, or “breast cancer” and “meta-analysis”, or “systematic review”. The search strategy was attached in Additional file We included all meta-analyses of associations between passive smoking and breast cancer among non-smoking women or meta-analyses in which the results of a passive smoking among non-smoking women subgroups were able to be obtained. Meta-analyses published between January 1966 and December 2016 were included. In addition, we excluded duplications, meeting abstractions, and meta-analyses which we couldn’t obtain full-text from.A measurement tool to assess systematic reviews (AMSTAR) to evaluate the risk of methodological quality of meta-analyses which were included in the present study [We used the nt study . The assAll full-texts of targeted meta-analyses were screened. At the same time, all original articles including interested subgroups were extracted. At the level of meta-analysis, we extracted ID, author, year of publication, country, number of included study, summarized OR and its’ 95% CI , result of heterogeneity test, selection of crude/adjusted OR to conduct pooling analysis. At the original study level, we extracted author, year of publication, type of study, sample size, crude or adjusted OR and its’ 95% CI, number of confounder adjusted and the variable of confounders. Data extraction was conducted by two researchers independently (Zhang Y and Wu ZH). Any disagreement in study selection and data extraction was adjudicated by the third researcher (Liu TY).We calculated the relative deviation (RD), i.e. crude OR minus adjusted OR, then divided by crude OR in each original study to detect how magnitude would the adjustment impact the effect size. We also listed how many confounders each original study adjusted, as well as what the variables were. To describe the distribution of adjusted OR with different number of adjusted confounders, a scatter diagram was sketched using adjusted OR of original studies as Y-axis and using the number of adjusted variables as X-axis. The data management was conducted using Microsoft Excel 2010. The scatter diagram was performed under software of SAS 9.4.Totally 10 meta-analyses were included in this study. From the 10 meta-analyses, the association between passive smoking with breast cancer risk for non-smoking women is the primary outcomes, while the association between passive smoking with breast cancer risk for non-smoking women was reported as subgroup analysis in other 6 meta-analyses , which may introduce potential bias into meta-analysis, especially failing to improve the precision of effect size for weaker or medium association. The heterogeneity among original studies could be made complicated when different adjusting strategies are extremely variability so that the synthesis of evidences would become controversial .It is well known that there are two kinds errors that impact the causal inference; the random error and the systematic error. Random error impact precision of the estimate, whist systematic error influents accuracy. Increasing the sample size will contribute mainly to reduce the random error, but has no effect on systematic error. To reduce the bias leaded by systematic error, researchers should consider and assess the significance of potential bias since study design phase. The inherent risk of bias in case-control study  could make the accuracy of estimation suspicious. In general, strategies for preventing selection bias and information bias are considered at the stage of research design and the implementation stage. Statistical strategies are commonly used to adjust confounding bias in data analysis stages. In theory, when selection bias and information bias have been well-controlled in the stages of study design and implementation, overall consideration and adjustment of potential confounders in data analyses stage could better the estimation of effect size close to the true effect size. Therefore, the adjusted OR of individual studies should tend to be constringency after the systematic error reduced validly. However, the results in this study have shown that various adjustment models have no obvious effect.In fact, it is difficult to adjudicate whether adjusted ORs tend to more validate estimation of OR by adjustment strategies for confounders because both of design and statistical analysis impact the adjusted results. Results of adjustment using multiple regression greatly depend on whether each confounder was measured, how precisely measurement was, and how each variable was taken into the regression model . In addiThe reason why we selected the association between breast cancer and passive smoking among non-smoking women as the case is that the association is weak or medium because weak or medium association is more likely impacted by potential bias, even could be reversed the direction of estimation. For example, one of included meta-analysis (Peter 2016) conducted subgroup analyses by number of confounders and found there was significant heterogeneity between different adjustment strategy groups  compared with eight or less confounder, random-effects OR 1.23(1.03–1.45)) , which sThe Newcastle-Ottawa Scale (NOS), which take three broads of bias into consideration roundly, i.e. the selection of the study groups; the comparability of the groups, and the ascertainment of either the exposure or outcome when conducting a meta-analysis for observational studies [On the other hand, we usually assess the quality of each included original studies using  studies . HoweverAlthough we detected several existing inconformity in meta-analysis of case-control study based on a case of passive smoking and breast cancer, the limitation of the present study, as a case of secondary data analysis is needed to make further consideration. The impacts of different confounding adjustment strategies on weak or medium association in case-control studies couldn’t be generalized all the meta-analyses of case-control studies. Another limitation is that it was not clear that the true effect size of the association between breast cancer and passive smoking among non-smoking women so that we couldn’t assess exactly how the different adjustment strategies impact the effect size of each original study. In addition, individual patient data meta-analysis (IPD) should benefit to clarify the impact of confounding adjustment strategy on better precisely estimations, however, we failed to ask researchers of original studies for their primary data. Even though, the findings in the present study provided a new profile to detect potential bias sources in meta-analysis of case-control studies.The results of the study shows that the difference of adjustment strategies of confounding factors in case-control studies may lead to bias of summary effect size in meta-analysis. Especially when the association strength is weak or medium, such bias will even reverse the direction of causal inference. However, whether it is reasonable to combine mixed unadjusted and adjusted estimates of original study in meta-analyses? How much deviation is caused by confounder adjustment strategy of individual study in meta-analysis of case-control study? How should researchers deal with the heterogeneity introduced by different confounder adjustment strategy? In order to address the above questions, further simulation study based on different adjustment strategy scenarios can provide more robust evidence, while the findings in present study provided useful recommendations for simulation design to make the simulation scenarios reflect the reality case-control studies situation in a better way.The heterogeneity of confounder adjustment strategies in case-control studies may lead to further bias for summary effect size in meta-analyses, especially for weak or medium association so that the direction of causal inference would be even reversed. Therefore, further methodological research is needed, referring to the assessment of confounder adjustment strategies, as well as how to take this kind of bias into account when drawing conclusion based on summary estimation of meta-analyses.Additional file 1:Search strategy. (PDF 86 kb)Additional file 2:AMSTAR score of included meta-analysis. (PDF 87 kb)Additional file 3:Summary of included original study. (PDF 1 mb)Additional file 4:Summary of relative deviation and the confounding adjustment strategy of each original study. (PDF 709 kb)


I2=17.8%, Pheterogeneity=0.274). The relationships were also significant for studies designed by case-control , as well as in European population . No evidence of publication bias was found. This meta-analysis demonstrated that dietary vitamin A intake might inversely associated with the risk of pancreatic cancer.Whether dietary vitamin A intake could reduce pancreatic cancer risk is still conflicting. We therefore conducted a meta-analysis to summarize the evidence from epidemiological studies. We searched the databases of PubMed and Web of Knowledge up to July 2016. Random model was used to combine study-specific relative risks (RR) and 95% confidence interval (CI). Publication bias was assessed by Egger regression asymmetry test and Begg's funnel plot. Eleven studies (10 case-control studies and 1 cohort study) involving 2705 pancreatic cancer cases were included in the present study. The RR (95% CI) of pancreatic cancer for highest category of vitamin A intake compared with lowest category was 0.839 (95% CI=0.712–0.988) with low heterogeneity detected ( Pancreatic cancer is a common gastrointestinal cancer. Early diagnosis of pancreatic cancer is difficult because of the lack of clinical symptoms in the early stages, and the 5-year survival rate ranges from 4% to 6% or less ,2. AlthoA recent study had reported that fruit and vegetable intake is associated inversely with the risk of pancreatic cancer . VitaminA comprehensive search was performed to identify all published studies on dietary vitamin A intake and pancreatic cancer risk. Searches of the PubMed and Web of Knowledge (up to July 2016) were conducted to identify eligible studies, with no language restriction. The key words used for the search strategy were ‘pancreatic’ and ‘cancer’ or ‘carcinoma’ and ‘vitamin A’ or ‘vitamins’ or ‘diet’ or ‘lifestyle’. Handsearching of reference lists of all relevant publications was finally done to identify more studies that could have been omitted from the databases’ search.Studies were eligible for inclusion if the following predefined criteria were met: (1) using a case-control design or prospective design or cross-sectional design; (2) the association was between vitamin A and pancreatic cancer; (3) published as original articles; (4) contained the minimum information necessary to estimate the effects, i.e. odds ratio (OR) or relative ratio (RR) or hazard ratio (HR), and a corresponding measure of uncertainty, i.e. confidence interval (CI); and (5) the articles were included between 1980 and 2016. Otherwise, we excluded studies that had non-human subjects, duplicated data, those lack of OR or RR or HR, those conducted before 1980 and others that were mainly reviews, viewpoints or editorials. No language restrictions were applied.Two independent investigators (Tao Zhang and Hongqiang Chen) independently performed the abstract review and subsequent full text review. The key elements related to the study inclusion criteria were collected from each of the included studies. Extracted data will include OR or RR or HR of the outcomes, and their 95% CI, first author's name, study design, country of region, population size and statistical adjustment. The third reviewer (Shiyong Qin) or by contacting content experts were needed until the two reviewers reached a consensus when discrepancies appeared. The quality of each study was assessed using the established form first developed and applied by McShane et al.  and HayeI2 statistics; values of 25, 50 and 75% were considered low, moderate and high inconsistencies respectively . Besides, we also extracted the detailed information for hospital based case-control studies (HBCC) or population bases case-control studies. And the significant associations were found in the hospital bases case-control studies , but not in population based case-control studies (PBCC) . Studies were also stratified by geographic area, the RR were 0.821 (95% CI=0.693–0.972) for studies conducted in Europe, 0.852 (95% CI=0.588–1.233) for studies in America. There is only one study designed in cohort design and one study conducted in Japan. Thus, the subgroup analysis for them was not conducted. The detailed results are summarized in Table 2.P=0.483) and funnel plot (Sensitivity analysis showed that no individual study had excessive influence on the association of vitamin A intake and pancreatic cancer risk. Egger regression asymmetry test (nel plot  showed nThe present study provided convincing evidence that dietary vitamin A intake is associated with a reduced risk of pancreatic cancer. This relationship between dietary vitamin A intake and pancreatic cancer risk was apparent and consistent in case-control studies and in the subgroup analysis of Europe populations.A recent meta-analysis had been conducted to assess the association between vitamin E intake and the risk of pancreatic cancer . The resAs a meta-analysis of published studies, our findings showed some advantages. First, a highlight of the present study was that we found an inverse association between dietary vitamin A intake and the risk of pancreatic cancer with low between-study heterogeneity. Second, the present study included a large number of cases and participants; this may derive a more precise estimation of the relationship between vitamin A intake and pancreatic cancer risk. Third, no significant publication bias was detected in this meta-analysis. Fourth, the quality scores of each study are assessed with high quality. Fifth, between-study heterogeneity is common in the meta-analysis, and our study found no evidence of between-study heterogeneity in the pooled analysis and subgroup analysis.There are some limitations in this meta-analysis should be concerned. First, our meta-analysis included 10 case-control studies and one cohort study. For the case-control studies, some recall or selection bias may be inherent in the original studies. Although prospective studies can allow a much greater possibility of reaching reasonable conclusions, the case-control study is an important method in aetiology research. Therefore, more original studies especially with prospective design are wanted in the future studies. Second, the association was only significant in the hospital-based case-controls, but not in the population-based case-controls. This may be caused by the little cases included in the population-based case-controls. Third, we did not do a dose-response analysis for vitamin A intake and the risk of pancreatic cancer because of the limited data in the reported articles. Further studies with detailed dose for each category are wanted to assess this association. Fourth, other unpublished literatures on relevant pharmaceutical websites were not searched and only studies in English were included, which may lead to a potential publication bias, although no significant publication bias was found by Egger's test and funnel plot. Finally, we only found significant association in the European populations, but not in the America and other populations. Therefore, more studies conducted in America and other areas are wanted to assess the relationship between dietary vitamin A intake and pancreatic cancer.In summary, results from the present study showed clearly that dietary vitamin A intake can significantly reduce the risk of pancreatic cancer.


Our results indicated that COL1A1 rs1800012 polymorphism may be associated with the reduced risk of sports-related tendon or ligament injuries, especially in ACL injuries, and that rare TT may played as a protective role.It has been reported that the single nucleotide polymorphism (SNP) rs1800012 in COL1A1 might be associated with the susceptibility to sports-related tendon and ligament injuries such as ACL injuries, Achilles tendon injuries, shoulder dislocations and tennis elbow. But the data from different studies have been conflicting. Here we attempted to systematically summarize and clarify the association between the SNP and sports-related tendon and ligament injuries risk. Six eligible studies including 933 cases and 1,381 controls were acquired from PubMed, Web Of Science and Cochrane library databases. Significant association was identified in homozygote model (TT  With the improved quality of life, increasingly sports demands were raised, and growing individuals are suffering from sports injuries, which is estimated of a 15.47 per 1,000 incidence in NCAA athletes Tendons and ligaments are collagenous structures which is made up of type I collagen fibrils. , 4 And CA multiple of diseases can have a genetic disorder, some are the Mendelian inherited conditions while the others are non-Mendelian inheritance spectrum such as tendon and ligament injuries, which are results from multifactorial issues and the severity of the conditions are determined by the complex gene-gene and gene-environment interactions . StudiesA total of 1200 studies were acquired from PubMed, Web Of Science and Cochrane library databases . Six studies –15 contaversus GG: OR = 0.17, 95%CI 0.08-0.35, PH = 0.00 Figure versus GT/GG: OR = 0.21, 95%CI 0.10-0.44, PH = 0.00 Figure versus G: OR = 0.89, 95%CI 0.75-1.05, PH = 0.17), heterozygote model , and dominant model . , heterozygote model , and dominant model . .Sensitivity analysis was performed to examine the influence set by the individual study on the pooled ORs for COL1A1 rs1800012 polymorphism by deleting one study each turn in every genetic model.  There waThis meta-analysis of six eligible case-control studies including 933 cases comparing 1381 healthy controls showed that rare TT genotype was likely a protective factor for sports-related tendon and ligament injuries, as the odds ratio was 0.17 in the homozygote model and 0.21 in the recessive model respectively. In subgroup analysis, similar results were found when the analysis was limited to ACL injuries. However, this finding should be interpreted with caution for limited sample heterogeneity.Type 1 collagen, representing up to 80% of the dry weight of tendon and ligament tissue , is compOur meta-analysis has several strengths. In the first place, this is the first meta-analysis focused on the association between COL1A1 polymorphism and the susceptibility to sports-related tendon and ligament injuries. Compared with the former review regarding ACL injury gene etiology , more COThe present meta-analysis has the following limitations that must be taken into account. Firstly, the number of included studies for COL1A1 rs1800012 polymorphism limited further analysis due to shortage of original studies. Secondly, the cases enrolled in this study are from different sports groups, some are skiers, some are soccer players, while some others were not mentioned. To our knowledge, sports-related tendon and ligament injuries have both intrinsic and extrinsic risk factors , charactIn conclusion, our results indicated that COL1A1 rs1800012 polymorphism may be associated with the reduced risk of sports-related tendon or ligament injuries, especially in ACL injuries, and that rare TT may played as a protective role. Nevertheless, despite our rigorous methodology, the inherent limitations of included studies and insufficient data prevent us from definitive confirming the association of sports-related tendon or ligament injuries and rs1800012 in COL1A1. Future studies with large-volume and more ethnic groups are awaited to validate and update the findings of this analysis.A literature search was performed in Pubmed, Web Of Science and Cochrane Library databases on June 2, 2016, without restriction to regions, publication types, or languages. We used the following search terms in [Title/Abstract]:  AND [muta* OR varia* OR polymorphi* OR SNP] AND [Wounds and injuries OR injur* OR trauma* OR sprain* OR strain* OR fracture* OR bone broke OR dislocation* OR tendinopathy OR luxation* OR contusion* OR tendon* OR muscle tear OR rupture*]. The reference lists of all retrieved studies, review articles, and conference abstracts were also manually searched for further relevant studies.Virtually all common sports injuries occurred in the shoulder, elbow, knee or ankle joint. Sports injuries which will be covered in this meta-analysis include the rotator cuff tendon injuries in the shoulder (rotator cuff injuries), tendon injuries in the elbow (tennis elbow), the cruciate ligament injures in the knee (cruciate ligament injuries), and Achilles tendon injuries in the ankle (Achilles tendon injuries). Studies in this meta-analysis must also meet the following inclusion criteria: (1) evaluation of the association between COL1A1 polymorphisms and sports injuries; (2) case-control study; (3) studies focusing on human being; (4) detailed genotype data could be acquired to calculate the odds ratios (ORs) and 95% confidence intervals (CIs); Exclusion criteria: (1) duplication of previous publications; (2) comment, review and editorial; (3) family-based studies of pedigrees; (4) study with no detailed genotype data. When there were multiple publications from the same population, the most recent or complete study was included. Eligible studies was achieved by two contributing authors independently in accordance with the inclusion and exclusion criteria by screening the titles, abstracts and full-text. Any disagreement was resolved by discussions.Data from the included studies were extracted and summarized independently by two of the authors (Li and Chen). Any disagreement was resolved by the adjudicating senior authors (Liu and Wang). The contents listed below were collected: name of first author, year of publication, the characteristics of cases and controls, country of origin, the detective sample, ethnicity, genotyping methods, the criteria of injury, Hardy-Weinberg equilibrium, number of cases and controls, genotype frequency in cases and controls.Studies were rated for the level of evidence provided according to the Newcastle-Ottawa scale , 26, whiP < 0.05 was considered a significant departure from HWE. OR and 95% CIs were calculated to evaluate the strength of the association between COL1A1 SNP and susceptibility to sports injuries. Pooled ORs were performed for allelic comparison (T versus G), heterozygote model (GT versus GG), homozygote model (TT versus GG), dominant model (TT + GT versus GG ), recessive model (TT versus GT + GG), respectively. A statistical Z-test was used and P value less than 0.05 was taken to indicate statistical significance. Statistical heterogeneity was evaluated using Cochran Q tests and the I2 statistic (greater than 50% as evidence of significant inconsistency) [We conducted our meta-analysis following preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement . We evalistency) . The ran


P = 0.03; CC vs CT + TT: OR = 0.80, 95% CI: 0.68–0.93, P = 0.00), and the rs895819 polymorphism wasassociated with significantly increased cancer risk in the Asian population  and in colorectal cancer subgroup . In addition, a subtly decreased risk was observed in the Caucasian population and in breast cancer subgroup. In conclusion, the rs2292832 polymorphism was significantly associated with increased breast cancer risk, and the rs895819 polymorphism contributes to the susceptibility of colorectal and breast cancer.The aim of this study is to provide a precise quantification for the association between miR-149 T > C (rs2292832) and miR-27a A > G (rs895819) and the risk of cancer. We conducted a systematic literature review and evaluated the quality of included studies based on Newcastle-Ottawa Scale (NOS). Pooled odds ratios (ORs) and corresponding 95% confidence intervals (95% CIs) were calculated to assess the strengths of the associations. We identified 40 studies for pooled analyses. Overall, the results demonstrated that the rs2292832 polymorphism was subtly decrease the risk of breast cancer (CT + CC vs TT: OR = 0.83, 95% CI: 0.70–0.98,  MicroRNAs (miRNAs) are a group of short noncoding RNAs of about 22 nucleotides which are involved in diverse physiological and developmental processes by controlling the gene expression of target mRNAs , 2. AccuSingle nucleotide polymorphisms (SNPs) represent the most common genetic variation in human genome. SNPs in miRNA genes are regarded to affect function by three ways: first, through the transcription of the primary transcript; second, through pri-miRNA and pre-miRNA processing; and third, through effects on miRNA-miRNA interactions . RecentlTo further determine whether there is an association of the rs2292832 and rs895819 in the miRNA genes with the risk for developing cancer, a comprehensive review and analysis of published data from different studies is needed. In this study, we performed a meta-analysis on all eligible case-control studies to drive a more powerful estimation of the association of rs2292832 and rs895819 SNP with cancer risks.The search process and the final selection of relevant studies are shown in Figure Characteristics of included studies are presented in Table All studies were case-control studies, including 40 studies on 10 breast cancer, 7 gastric cancer, 7 colorectal cancer, 4 lung cancer, and 12 on other cancer types. There were 28 studies of Asian descendent, 11 of Caucasian descendent. A classic PCR-RFLP assay was used in 17 out of 40 studies, the other molecular genotyping methods, such as Taqman, MassARRAY, and HRM, were used in other studies. 32 studies were randomly repeated a portion of samples as quality control while genotyping.According to the NOS for quality of case-control, the study-specific quality scores are summarized in Table P = 0.00).For all of control subjects included in this study, the frequencies of risk C allele in rs2292832 for Caucasians and Asians were 33.66%  and 50.20%  Figure . The freP = 0.03; CC vs CT + TT: OR = 0.80, 95% CI: 0.68–0.93, P = 0.00)  Table .P = 0.02)  , whereas a significantly increased risk was observed in colorectal cancer  , cancer type, matched controls (yes or not), language (English or Chinese), source of control , assay, sample size (300 as the boundary) and quality control (with or without). It was detected that the systemic results were not altered by these characteristics .In the present study, an association between the two common SNPs in microRNAs (rs2292832 and rs895819) and cancer risk was evaluated by the pooled results from 40 published studies. The results demonstrated that the rs2292832 was associated with a significantly reduced risk for developing cancer in the breast cancer (dominant and recessive model), and for the rs895819 G allele, AG genotype and dominant model were associated with a decreased risk for Caucasian population and breast cancer, in contrast, a subtly increased risk was observed in a Asian population (dominant model) and colorectal cancer .Thus far, for the rs2292832, no significant association was observed in overall pooled results , 55. In The rs895819 is well recognized to be involved in the pathogenesis, metastasis, and invasion of multiple cancer types, by functioning as an oncogene via complex mechanisms –59. The This comprehensive and updated meta-analysis further support the rs895819 G allele was associated with a decreased risk for breast cancer, whereas a subtly increased risk was observed in colorectal cancer. In addition, significant associations with an increased risk for the Caucasian population, but a significantly reduced risk for the Asian population, suggesting a possible ethnic difference in the genetic background and the environment, which was the similar to that reported by Wang et al.  and ZhonAlthough meta-analysis is robust, our study still has some limitations. Firstly, we pooled the data based on unadjusted information and lack the consideration of combination genetic factors together with environmental exposures, while a more precise analysis needs to be conducted if individual data are available. Secondly, although all eligible studies were summarized, the relatively small sample size of studies may lead to reduced statistical power when stratified according to the cancer type or ethnicity. Thirdly, the different genotyping strategies may contribute to the bias in the analysis. Fourthly, Publication bias may exist, because only published studies were included in this meta-analysis, although the result for publication bias was not statistically significant. Finally, the data sets without excluding the studies with inefficient scores base on NOS.In summary, current data suggest that the rs2292832 polymorphism may contribute to increased susceptibility to breast cancer, and the rs895819 polymorphism was a protective factor for cancer development among Caucasian and may contribute to breast and colorectal cancer susceptibility. Further multi-centric studies are still needed to confirm the present results.A comprehensive literature search was conducted using the PubMed, Springer, Elsevier, CNKI (Chinese), and Wanfang (Chinese) Digital Dissertations Databases for relevant articles published in English or Chinese up to July 2015 with key words ‘microRNA/miR-149/miR-27a’, ‘rs2292832/rs895819’,‘polymorphism’, and ‘cancer’. The full text of the candidate articles were examined carefully to determine whether they accorded with the inclusion criteria for the meta-analysis. The present study was conducted in accordance with PRISMA guidelines .The inclusion criteria were as follows: 1) about the rs2292832/rs895819 polymorphisms and cancer risk, 2) based on case-control studies (including cohort studies), 3) sufficient published data for estimating an odds ratio (OR) with 95% confidence interval (CI), and 4) genotype distribution of control groups must be in accordance with the assumptions of Hardy-Weinberg equilibrium (HWE).In case of redundant publications, only the studies with the largest sample size and/or latest published date were included.Data were extracted independently by two investigators (YJF and FJD). Data for analyses, including first author, publication year, cancer type, country of origin, ethnicity, study design, genotype detection methods and quality control or not. If discrepancies existed, consensus would be finally reached on discussion.Quality assessment criteria were utilized to evaluate methodological quality of included studies based on Newcastle-Ottawa Scale (NOS)  for qualThe analyses were conducted in Review Manager 5.0 . The overall strength of an association between rs2292832 and rs895819 polymorphisms and cancer risk assessed by crude ORs together with their corresponding 95% CIs. The stratified analysis was conducted by ethnicity , cancer type, source of control and sample size (300 as the boundary).2 based Q-test among the studies [P < 0.05. In case of no significant heterogeneity, point estimates and 95% CI was estimated using the fixed effect model (Mantel-Haenszel), otherwise, random effects model (DerSimonian Laird) was employed [Z-test.Heterogeneity in meta-analysis refers to the variation in study outcomes between different studies. Between-study heterogeneity was evaluated with a χ studies . Heterogemployed , 70. TheP < 0.05.If there were significant heterogeneity among included studies, the sources of heterogeneity would be explored using meta-regression in Stata 12.0 . To assess the stability of the results, one-way sensitivity analyses were performed to assess the stability of the results, in which a single study in the meta-analysis was deleted each time to reflect the influence of the individual data set to the pooled OR. The publication bias was diagnosed by using inverted funnel plots, Begg's test and the Egger's test by Stata 12.0. Statistical tests performed in the present analysis were considered significant whenever the corresponding null-hypothesis probability was


ZNF350 variant can increase, decrease, or have no effect on the risks of breast cancer depending on the polymorphism and genetic model used. Further studies will be required to validate these findings.Some studies have reported an association between the zinc-finger protein 350 (ZNF350), also known as zinc-finger and BRCA1-interacting protein with a Kruppel-associated box (KRAB) domain (ZBRK1), and risks of breast cancer, although the results remain controversial. A systematic search was conducted on PubMed, Web of Science, EMBASE, Ovid, Chinese National Knowledge Databases, and WanFang databases with relevant keywords. Four studies of five distinct populations involving 5824 breast cancer cases were used to conduct a meta-analysis that summarizes the current evidence of 5 genetic polymorphisms: Asp35Asp, Leu66Pro, Pro373Pro, Ser472Pro, and Ser501Arg in the ZNF350 gene. The T allele in Asp35Asp polymorphisms not significantly associated with increased risk of breast cancer . The minor C allele of the Asp35Asp polymorphism is protective in the overdominant model . The Pro allele in the Leu66Pro polymorphism is protective in all of the models examined . The Pro373Pro is not associated with breast cancer in all of the models tested. The Pro allele of the Ser472Pro polymorphism is protective using the dominant model  but deleterious using the overdominant model . The Ser501Arg polymorphism is deleterious only when using the recessive model . In conclusion, this meta-analysis suggests that genetic polymorphisms in the  Breast cancer is the most common malignancy in women worldwide  and leadAlthough the exact pathogenic mechanism of breast cancer remains elusive, polygenic models assuming a multiplicative effect on suggest that near 50% if all breast cancer cases fall within 12% of the population with increased risks of breast cancer , 5. ThusBRCA1 expression strongly correlated with accelerate growth and progression of sporadic breast cancer . The Leu66Pro polymorphism is also protective to the risks of breast cancer when using the the dominant, recessive, or the overdominant model Figure .The A allele Pro373Pro (C > A) polymorphism is not associated with risks of breast cancer using the allelic model  or the dominant, recessive, or overdominant models Figure . The SerThe Arg allele of the Ser501Arg polymorphism is not associated with the breast cancer risks when using the allelic model . However, the Ser501Arg polymorphism is linked to breast cancer when applying the recessive model  [GADD45A [ANG1 [HMGA1 [p21 [MMP9 [FGF2 [KAP1 [ZNF350 is a 532 amino acid protein that contains an N-terminal A+B box domain, eight Cn (CTRD) , 30. Then (CTRD) , 32. ZNF[GADD45A , ANG1 [15A [ANG1 , HMGA1 [1 [HMGA1 , p21 [2021 [MMP9 , FGF2 [3P9 [FGF2 , and KAPF2 [KAP1 .The ZNF350 gene is mapped to chromosome 19q13.4 and is near a cluster of other KRAB-Zinc finger proteins. SNPs in ZNF50 has been previously linked to the risks of developing breast cancer, although to conflicting results , 21–23.We have conducted the first meta-analysis summarizing the evidence regarding the association between the five ZNF350 SNPs and the risks of developing breast cancer. Our results suggest that the Leu66Pro polymorphism is mostly likely associated with modifying the risks of breast cancer, while patients with Asp35Asp and Ser501Arg SNPs have increased odds of breast cancer. Asp35Asp and Ser472Pro could be protective using the overdominant model.Publication bias, the preferential publication of studies with positive results, is a significant problem in many meta-analyses. However, our meta-analysis also includes studies with negative conclusions. Furthermore, our funnel plots do not appear asymmetric, suggesting that publication bias is not a problem within our study.Several limitations should be noted in interpreting the results of our meta-analysis. First, we were not able to adjust for potential confounding effects conferred by age, gender, lifestyle, and environmental factors due to the lack of individual data. Our results were based on unadjusted estimates - a more precise analysis could be conducted if all raw data related to the confounders were available. The lack of important individual health data, such as body mass index (BMI), drug history, diet, and age, also forbid us from performing a more sensitive analysis.Although the functional significances of the mutations studied in the current study is unknown, we postulate that mutations such as Leu66Pro have many important biological roles as it is found in the KRAB-domain of the protein. In conclusion, the pooled results of our meta-analysis studying We propose to that both future large-scale clinical studies and functional studies are needed to elucidate the role to which ZNF350 modify the risks of breast cancer.We searched the literature hosted on PubMed, Web of Science, EMBASE, Ovid, Chinese National Knowledge Databases and WanFang with keywords related to breast cancer and the gene of interest . Genetic association studies published before May 2017 were retrieved and no earlier publication date limit was applied. The last search was performed on the May 1st, 2017. For each study screened, we checked their references to identify other relevant publications to the topic. The systematic search was conducted without any restrictions on the language used and the minimum number of patients required to be included. The study focused on human studies.All retrieved study were screened and considered elgible if satisfying each point of the following criteria: 1) case-control or cohort study, 2) original papers containing independent trials, 3) confirmation of breast cancer, and 4) genotype distribution information of both the control and experimental group or odds ratio (OR) with its 95% confidence interval (CI) and P value. The major reasons for exclusion of studies were case-only studies, overlapping data, insufficient data for analyses, and review articles.Data extraction was performed independently by two reviewers using a standard extraction form. All data were checked for internal consistency and disagreements were resolved through thorough discussion between all authors. If there were doubts about the result of studies, the corresponding author of the study of interest was contacted. For each study, the following were extracted from each article: first author’s name, publication year, diagnostic criterion, definition and numbers of cases and controls, ethnicity of the study population, frequency of genotypes, genotyping method, source of controls, Hardy–Weinberg equilibrium (HWE), age, body-mass index (BMI). Studies with different ethnic groups within the same study were considered as individual studies for our analyses.The association strength between the five ZNF350 polymorphisms and breast cancer was assessed by calculating OR with 95% CI.2) test was used to evaluate whether there is a significant deviation from HWE among the control subjects of the study. The per-allele OR of risk allele T was compared between cases and controls in each study. The ORs were pooled using both the random-effects model (the DerSimonian and Laird method) and the fixed effects model (the Mantel-Haenszel method) as previously described [The chi-square (χescribed , 35. Theescribed . The res2Q test [Q test was also performed to detect the heterogeneity within each subgroup. Publication bias was assessed using linear regression to measure funnel plot asymmetry on the natural logarithm of OR using Egger’s method [P values were for two-sided analysis. Type I error rate was set at 0.05.Heterogeneity across individual studies was examined using Cochran’s χ2Q test . Q test s method . All sta


Epidemiological studies have clarified the potential associations between regular aspirin use and cancers. However, it remains controversial on whether aspirin use decreases the risk of cancers risks. Therefore, we conducted an updated meta-analysis to assess the associations between aspirin use and cancers.The PubMed, Embase, and Web of Science databases were systematically searched up to March 2017 to identify relevant studies. Relative risks (RRs) with 95% confidence intervals (CIs) were used to assess the strength of associations.A total of 218 studies with 309 reports were eligible for this meta-analysis. Aspirin use was associated with a significant decrease in the risk of overall cancer , and gastric , esophageal , colorectal , pancreatic , ovarian , endometrial , breast , and prostate  cancers, as well as small intestine neuroendocrine tumors .These findings suggest that aspirin use is associated with a reduced risk of gastric, esophageal, colorectal, pancreatic, ovarian, endometrial, breast, and prostate cancers, and small intestine neuroendocrine tumors.The online version of this article (10.1186/s12885-018-4156-5) contains supplementary material, which is available to authorized users. Aspirin has been used as an analgesic and in the prevention of cardiovascular diseases events in the past decades and is one of the most commonly used drugs worldwide , 2. ClinAlthough several meta-analyses have been conducted to assess the associations between aspirin use and the risk of cancers –18, mostThis systematic review was conducted in accordance with the checklist proposed by the Meta-analysis of Observational Studies in Epidemiology group . We searThe inclusion criteria were: 1) case-control or cohort studies; 2) studies that evaluated the relationships between the use of aspirin and the risk of cancers; 3) studies that reported risk estimates with 95% confidence interval (CI) or provided information that enabled us to calculate them. The exclusion criteria were: 1) studies that used other combinations of NSAIDs, which prevented the determination of the specific effect of aspirin, and 2) studies involving patients with specific diseases . Only the latest or the most informative study was included when multiple studies were published on the same study population.The following information was obtained from each study: first author name, year of publication, study period, study location, study design, number of cases, number of participants, gender, definition of aspirin exposure, as curtained methods of exposure, odds ratios (ORs), hazard ratios (HRs) or relative risks (RRs) with their corresponding 95% CIs, and confounding factors adjusted in the analysis. The most fully-adjusted risk estimates with its corresponding 95% CIs (when available) were preferentially extracted. Data extraction was conducted independently by two authors (Y.Q. and T.T.Y.), and discrepancies were resolved by discussion with a third investigator (Z.X.L.).Quality assessment of eligible studies was performed independently by two reviewers (Y.Q. and T.T.Y.) according to the Newcastle-Ottawa Quality Assessment Scale . This scRRs were used as the common measurement of the associations between aspirin use and the risk of cancer. Because cancer is a rare event in general, we could generally ignore the distinctions among the various measures of relative risk  , and conI2 statistic  were used [P values) were two-tailed with a significance level of 0.05.To assess the heterogeneity in results of individual studies, ere used . Publicaere used . StatistFigure The main characteristics of the 218 eligible articles published between 1985 and 2016 are summarized in Tables Figures Additional file We conducted a subgroup analysis stratified by questionnaires and medical records, and found a lower risk in medical records with most cancers , however, significant heterogeneity of effects was noted for those subgroups .The funnel plot showed asymmetry Fig. . In addiThe results of our meta-analysis supported the presence of inverse associations between aspirin use and the risk of overall cancer, gastric, esophageal, colorectal, pancreatic, breast, ovarian, endometrial, and prostate cancers, as well as small intestine neuroendocrine tumors. However, no significant associations were observed between the use of aspirin and the risk of other cancers, including hepato-biliary, lung, cervical uterus, renal, renal pelvis and ureter, bladder, brain, head and neck, thyroid, and skin cancers, as well as lymphoma, and leukemia.There are several potential biological mechanisms through which aspirin could reduce the risk of cancer. First, aspirin and other NSAIDs have been proven to inhibit the activity of the enzyme cyclooxygenase 2 (COX-2), which is responsible for the synthesis of prostaglandins . COX-2 hThe results of this meta-analysis indicated that utilization of aspirin had different protective effects on the development of cancer. This difference may be attributed to the different expression levels of COX in various cancers . FurtherThe decreased risk of gastric, esophageal, pancreatic, lung, breast, and ovarian cancers was observed in the case-control studies but not in the cohort studies. One possible explanation for the difference might be that cases in the case-control studies might have a recall bias and tended to overestimate the risk of cancer by aspirin use. Another possible explanation is that misclassification or measurement errors for aspirin use in the cohort studies might have distorted the association because most of our analyses were based on baseline data, and there might be a discrepancy between initial recruitment and subsequent aspirin consumption.The longer those who had used aspirin, the lower their risk of cancer was, with longer duration of use associated with an RR of 0.90 (95% CI 0.89–0.74), based on 118 studies that reported associations with longer (≥5 years) duration of aspirin use and 105 studies that reported associations with shorter (< 5 years) duration of aspirin use. For most cancers , risk reductions were more pronounced with longer duration of use, and these results agree with those of previous studies –41. In aThere was no statistically significant difference between the pooled RRs for the frequency of aspirin in most studies. Given that a few studies were included in the subgroup analysis on the basis of the frequency of aspirin use and most studies lacked information on this variable, the results on the risks associated with the frequency of aspirin use should be interpreted with caution. Further studies that explore the associations between the frequency of aspirin use and cancer risk are necessary to elucidate the effects of aspirin.In addition, our results indicated that the strongest reduction in the risk of most cancers associated with aspirin was found in North American countries. However, two-thirds of the included studies were performed in North America and a few studies were performed in Asian and European countries, which might distort the accuracy of the results. Therefore, more studies are necessary to examine the discrepancies among the different countries and regions.Bosetti et al. (2011)  conducteAlgra and Rothwell (2012)  conducteThis study is the most up-to-date comprehensive review of the effect of aspirin use on the risk of all types of cancers, and the large sample size provides reliable results with greater precision and power. The potential limitations of this study should be noted. First, there was substantial heterogeneity across the included studies, which was likely due to differences in the definitions of exposure, units, assessment methods, and the adjusted variables across different studies. Second, misclassification or measurement errors for aspirin use might distort the association because our analyses were based on baseline data, and changes in the exposure to aspirin were not updated during the follow-up period. Third, the visual inspection of a funnel plot showed asymmetry, and the Begg’s test and Egger’s test also identified evidence of publication bias among the studies included in our meta-analysis.Our meta-analysis indicated a beneficial role for aspirin for overall cancers; however, the results should be interpreted with caution. Considering that most evaluated studies were based on secondary prevention rather than on primary prevention, the totality of evidence for the high-risk population was incomplete, and it is appropriate to let the beneficial role remain uncertain. At present, we should accept the uncertainties, and future chemoprevention trials should clarify the extent to which aspirin decreases cancers incidence.Evidence from observational studies indicates that utilization of aspirin is associated with reduced risk of gastric, colorectal, esophageal, pancreatic, ovarian, endometrial, breast, and prostate cancers, in addition to small intestine neuroendocrine tumors. A stronger protective effect was observed in the North American populations and patients who used aspirin for at least 5 years. It is important to address immortal time bias not only to ensure the integrity of the meta-analysis, but also to ensure the integrity of pharmacoepidemiological studies. Moreover, given the confidence limits of the evaluated studies, adequately powered mechanistic studies should help elucidate the mechanisms underlying this correlation.Additional file 1:Table S1. Summary table. Table S2. Subgroup analysis of relative risk of gastric cancer. Table S3. Subgroup analysis of relative risk of esophagus cancer. Table S4. Subgroup analysis of relative risk of colorectal cancer. Table S5. Subgroup analysis of relative risk of hepato-biliary cancer. Table S6. Subgroup analysis of relative risk of pancreatic cancer. Table S7. Subgroup analysis of relative risk of lung cancer. Table S8. Subgroup analysis of relative risk of breast cancer. Table S9. Subgroup analysis of relative risk of ovarian cancer. Table S10. Subgroup analysis of relative risk of endometrial cancer. Table S11. Subgroup analysis of relative risk of prostate cancer. Table S12. Subgroup analysis of relative risk of renal cancer. Table S13. Subgroup analysis of relative risk of bladder cancer. Table S14. Subgroup analysis of relative risk of brain tumor. Table S15. Subgroup analysis of relative risk of head and neck cancers. Table S16. Subgroup analysis of relative risk of skin cancer. Table S17. Subgroup analysis of relative risk of lymphoma. Table S18. Subgroup analysis of relative risk of leukemia. (DOC 549 kb)


BRCA2 and rs17879961 in CHEK2 were associated with lung cancer. However, the associations between these two variants and urinary tract cancers risk remain largely unexplored. We applied imputation of three genome-wide association studies published in the database of Genotypes and Phenotypes (dbGaP). Unconditional logistic regression analysis and meta-analysis were performed to assess the association between these two variants and the risk of urinary tract cancers. Our results showed that rs11571833[T] had an effect on urinary tract cancers predisposition , especially associated with increased the risk of bladder cancer . Moreover, rs17879961[C] had a protective effect on the urinary tract cancers  and was mostly associated with a lower incidence of renal cell carcinoma . Together, our study indicates that BRCA2 and CHEK2 play an important role in the genetic susceptibility to urinary tract cancers.Previous studies have shown that two rare variants, rs11571833 in  According to statistics, approximately 429,800 newly diagnosed cases of bladder cancer occurred and caused 165,100 deaths in 2012 worldwide156Genome-wide association study (GWAS) and its corresponding meta-analysis have successfully identified several risk loci and regions, which had small or moderate effect to increase the risk of diseases89111213815BRCA2  and rs17879961 (c.470T > C) in CHEK2 , which have large effect on lung cancer in populations of European ancestryBRCA2 and CHEK2, two important DNA repaired genes, acted a crucial role in response to DNA alterations and involved in maintenance of genome stability181921BRCA2 and CHEK2 that changes amino acid may alter their function of DNA damage repair, which may influence the risk of diseasesBRCA2 and CHEK2 confer susceptibility to multi-organ cancers, such as breast, lung, prostate and bladder cancer2425262728In recent, an imputation-based genome wide association study had identified two rare variants rs11571833 (c.9976A > T) in A total of three GWAS studies including 6,064 cases and 8,661 controls were enrolled in our study. The detailed characteristics of GWAS studies are shown in P = 4.5 × 10−3). Simultaneously, rs17879961[C] was related with decreased the risk of renal cell carcinoma in Illumina 610 array and bladder cancer in Illumina 610 array .Our logistic regression results are applied in combined = 1.70, 95%CI = 1.19–2.42 and Pcombined = 3.6 × 10−3), but showed non-significant association between renal cell carcinoma and prostate cancer . There were no remarkable associations between rs17879961 and the other two cancers  and rs17879961[C] was associated with a significantly lower risk of urinary tract cancers . In conclusion, rs11571833 may play a risk factor in urinary tract cancers predisposition, especially be associated with the risk of bladder cancer. Meanwhile, rs17879961 is associated with decreased risk of urinary tract cancers and mostly associated with the risk of renal cell carcinoma.In consideration of the relative small sample, we attempted to combine the original GWAS data to implement joint analyses. We merged genotype data across each cancer  to increase the sample size. Totally, the sample size is 3591 cases and 4132 controls for bladder cancer, 1322 cases and 3428 controls for renal cell carcinoma, 1151 cases and 1101 controls for prostate cancer. Our results indicated that rs11571833[T] was significantly associated with increased the risk of bladder cancer . In addition, a significant association between rs11571833[T] and bladder cancer was observed in the subgroup meta-analysis  and had a protective effect on renal cell carcinoma  plays an important role in encoding a pluripotent kinase which can induce cell cycle arrest or apoptosis in response to unrepaired DNA damage34CHEK2 and injures binding of principal substrates. The rs17879961 (CHEK2 p.Ile157Thr) substitution may alter its ability to bind p53, BRCA1 and Cdc25A proteins436BRCA2 (breast cancer early onset 2) is a widely known anti-oncogene and associated with the risk of breast cancer and ovarian cancerBRCA2 also involves in the maintenance of genome stability through interacting with RAD51 recombinase, specifically in the homologous recombination pathway for DNA repair394041423444Recently, an imputation study identified two rare variants rs11571833 in In this study, we investigated the associations between rare genetic variants of rs11571833 and rs17879961 and the risk of urinary tract cancers  and found that the rare variant rs11571833 (c.9976A > T) was associated with increased risk of urinary tract cancers, especially associated with bladder cancer. Concurrently, rs17879961 (c.470T > C) played a protective role in the urinary tract cancers carcinogenesis and mostly decreased the risk of renal cell carcinoma. Our meta-analyses result show highly consistency with joint analyses, which strengthen our conclusion that the rs11571833 is associated with increased the risk of urinary tract cancers and rs17879961 reduces urinary tract cancers predisposition. Interestingly, association signals of these two variants in urinary tract cancers  are in the same direction to lung cancer . It is noteworthy that the rare variants rs17879961 may impair function of CHEK2, but it was associated with decreased the risk of renal cell cancer. A speculation for the possible protective mechanism is that CHEK2 can have two opposite effects on damaged stem cells and it impedes stem cell division until DNA damage has been repaired or actives apoptosis if unrepaired DNA damage happened. Accumulating evidence has shown that in the circumstance of continued DNA damage by long-term exposure of tobacco, the normal stem cell defenses that involve CHEK2 can be attenuated by reducing the CHEK2 activity as a result of rs17879961 (p.Ile157Thr)1732There are several limitations in our study. Firstly, the available GWAS data published in dbGaP database provides relatively little samples, which may influence the power to identify the association between the rare variants and diseases. Furthermore, our analysis based on public database is short of relevant demography information applied in stratification analysis. Additionally, our study is an imputation-based analysis from public database and the ORs of two rare variants are relatively modest. Besides, the sample sizes of controls are unevenly matched with cases in some cohorts, which may result in sample bias. Further large well-designed studies in other independent populations and functional studies are needed to validate our findings. Meanwhile, the interaction between environmental exposures and genetic susceptibility should be also considered in the future researchBRCA2 and CHEK2 play an important role in the genetic susceptibility to urinary tract cancers.In conclusion, our imputation analysis results indicated that the rare variant rs11571833 (c.9976A > T) showed an effect on urinary tract cancers predisposition, especially associated with increased the risk of bladder cancer. However, rs17879961 (c.470T > C) may play a protective role in the urinary tract cancers carcinogenesis and notably decrease the risk of renal cell carcinoma. Association signals of these two variants in urinary tract cancers are in the same direction to lung cancer. These results suggest that GWAS data from three cancer studies were available, which were requested from dbGaP. Two genotype datasets were excluded because of low-density genotype panel and low sample size . In the final analysis, we included three bladder cancer studies, three renal cell carcinoma studies and one prostate cancer study, totally including 6,064 cases and 8,661 controls.P < 1.0 × 10−6; (4) A/T or C/G SNPs with MAF >0.45.First, we applied the LiftOver tool to convert study data from earlier genome builds (NCBI build 36) to NCBI build 37. Few SNPs that failed in the LiftOver were excluded from the imputation. Before performing imputation, we filtered the data to remove low-quality variants and individuals to increase the accuracy of the results. For individuals, (1) we excluded those missing rate per person >5%; (2) excluded samples with ambiguous gender; (3) additional duplicates or probable relatives were excluded according to PI_HAT > 0.5; SNPs filter criterion : (1) completion rate per locus <95%; (2) minor allele frequency <0.05; (3) Hardy-Weinberg Proportion for autosomal SNPs in control population with We used SHAPEIT, a highly accurate phasing algorithm, to infer the haplotypes underlying genotype dataI2 statistics. I2 values ≥ 75% were considered to be significant heterogeneity. All statistical analyses were two-sided, and a P value < 0.05 was considered statistically significant.An unconditional logistic regression model was applied to calculate the odds ratio (OR) and 95% confidence interval (CI) for each SNP in an additive model using SNPTEST software. We adjusted for some covariates such as age, gender, study and significant principle components (PCs). The principal component analysis (PCA) was carried out to assess for population stratification of study cohorts. Meta-analysis was conducted by Stata v.10 . Heterogeneity was evaluated by Cochran’Q and How to cite this article: Ge, Y. et al. Rare variants in BRCA2 and CHEK2 are associated with the risk of urinary tract cancers. Sci. Rep.6, 33542; doi: 10.1038/srep33542 (2016).


Whether opioid-receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) is associated with nicotine dependence is controversial. We analyzed the combined results from published studies of this possibility.Literature reviews were performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Web of Science, Chinese National Science Infrastructure (CNKI), PubMed, Embase and Google Scholar database searches using MeSH terms were conducted to find all relevant researches up to October 2016. Odds ratios (ORs) and their 95% confidence intervals (95% CIs) were calculated in allele, homozygote, heterozygote, dominant and recessive models. Ethnicity-specific subgroup meta-analysis, heterogeneity, sensitivity analysis and publication bias were considered.Seven eligible studies with 3313 patients were included. The ORs in the five genetic models mentioned above were 1.000 , 1.032 , 0.963 , 1.006 , 0.967 , respectively. Only in dominant model is the association significant. Upon ethnicity-specific subgroup analysis, there is no statistical significance.OPRM1-A118G polymorphism (A>G) is not associated with nicotine dependence. Nicotine dependence is one of the commonest behavioral disorders. It involves psychological and physical dependences on nicotine and loss of control of in spite of frequent undesirable complications . SmokingA significant neurotransmitter system relevant to nicotine-induced reward is the endogenous opioid system. Nicotine consumption can lead to increased endogenous opioids, especially β-endorphin. The binding of β-endorphin to μ-opioid receptors (genetic locus OPRM1) might reinforce nicotine dependence by increasing dopamine actions in reward centers , 6. As sFigure The 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 Table Since ethnicity may have effect on this association, ethnicity-specific subgroup analysis was also performed. All ethnicities involved in these 7 articles can be divided into Caucasian group and Asian group. The subgroup results of heterogeneity tests and meta-analysis were also shown in Table The sensitivity-analyses suggested that the final OR was not influenced by removing each single literature Figure . Funnel In consideration of the significance of μ-opioid receptor systems in physiological mechanisms about the reward center, biologically, it is plausible that OPRM1 polymorphisms can modulate the risks of nicotine-dependence. Previously published reports demonstrated that OPRM1 A118A mRNAs were 1.5 to 2.5 folds more abundant than 118G mRNAs in cerebral homogenate, and 118G could lead to a 10 folds reduction at OPRM1-protein levels . This inIn the recent years, big data has established very close associations between OPRM1-A118G polymorphism and nicotine, alcohol, and opioid-dependence. Kapur et al. and Tan et al. found a positive correlation between the OPRM1-A118G polymorphism and heroin-dependences , 14. AltA single study cannot confirm the correlation between OPRM1-A118G polymorphism and nicotine-dependence risks convincingly. This is particularly true for researches with relatively small sample-sizes. Given this, we pooled several databases to analyze the associations between nicotine-dependence and the OPRM1-A118G polymorphism. In our study, the statistically correlation between OPRM1-A118G polymorphism and increased nicotine-dependence risks was not detected in any of the five genetic models . Also, different ethnicities might contribute to variable association findings. Thus, we also performed an ethnicity-based subgroup analysis. Similarly, no matter for Caucasian population or Asian population, the OPRM1-A118G polymorphism has no correlation to nicotine-dependence in all there five genetic models. Regarding the testing statistic, the integrated ORs were calculated. Generally, relative risk (RR) and OR are usually comparable in magnitude if the studied diseases are rare, like this case. However, using RR can sometimes magnify or overestimate risks, especially if the diseases are with higher incidence. We carefully reviewed our manuscript and related articles and we are happy to say in our meta-analysis, OR for study outcomes are comparable as RRs and these additional data is adding value to estimate a more accurate effect. In our meta-analysis, no publication bias was suggested according to the funnel-plot. We also conducted the Egger's test [There may be some limitations in our meta-analysis. Firstly, the number of the included literatures and the sample-size for each ethnicity were limited. Hence, type-II error couldn't be dismissed. Secondly, the effect of gene-environment interactions and gene-gene interactions was not emphasized because not all researches had this information, or even when they did, adjusted factors were reported differently. Thirdly, more accurate ORs should be adjusted by patient factors such as gender, age, living styles, medication consumption and other exposure factors. Fourth, only published articles were included, the unpublished and ongoing studies could convert our result.Two authors searched Chinese National Knowledge Infrastructure (CNKI), Web of Science, PubMed, Embase and Google Scholar independently (cut-off date: 30 October 2016) to include case control researches about the correlation between the polymorphism of OPRM1-A118G (rs1799971) and nicotine-dependence risks. Search terms include “nicotine or tobacco or smoking” and “rs1799971 or A118G or OPRM1”. Relevant references were also searched to identify other potentially available researches. The inclusion-criteria and the exclusion-criteria are shown as Table According to the inclusion criteria set in Table In accord with the methodological quality-assessment scale  A118G Polymorphism (rs1799971) is not associated with nicotine dependence in white or Asian populations.


Identifying patient priorities and preference measurements have gained importance as patients claim a more active role in health care decision making. Due to the variety of existing methods, it is challenging to define an appropriate method for each decision problem. This study demonstrates the impact of the non-standardized Analytic Hierarchy Process (AHP) method on priorities, and compares it with Best-Worst-Scaling (BWS) and ranking card methods.We investigated AHP results for different Consistency Ratio (CR) thresholds, aggregation methods, and sensitivity analyses. We also compared criteria rankings of AHP with BWS and ranking cards results by Kendall’s tau b.The sample for our decision analysis consisted of 39 patients with rare diseases and mean age of 53.82 years. The mean weights of the two groups of CR ≤ 0.1 and CR ≤ 0.2 did not differ significantly. For the aggregation by individual priority (AIP) method, the CR was higher than for aggregation by individual judgment (AIJ). In contrast, the weights of AIJ were similar compared to AIP, but some criteria’s rankings differed. Weights aggregated by geometric mean, median, and mean showed deviating results and rank reversals. Sensitivity analyses showed instable rankings. Moderate to high correlations between the rankings resulting from AHP and BWS.Limitations were the small sample size and the heterogeneity of the patients with different rare diseases.In the AHP method, the number of included patients is associated with the threshold of the CR and choice of the aggregation method, whereas both directions of influence could be demonstrated. Therefore, it is important to implement standards for the AHP method. The choice of method should depend on the trade-off between the burden for participants and possibilities for analyses.The online version of this article (doi:10.1186/s13561-016-0130-6) contains supplementary material, which is available to authorized users. Measurement of patient preferences and priorities has gained more relevance in health care. One reason is the increasing importance of patient participation in health care. In Germany, the Robert Koch-Institute used to call the patients “costumers” and “evaluators” in their Information System of the Federal Health Monitoring . PatientDecisions regarding treatment preferences must consider a variety of characteristics, so called multi-criteria decision problems. Possible options for solving decision problems are value-based methods, strategy based methods, and Conjoint Analyses (CA). The German Institute for Quality and Efficiency in Health Care (IQWiG) tested and confirmed the Analytic Hierarchy Process (AHP) method as decision making tool in health technology assessments . ApplicaThis study accompanied a research project designed to gather patient needs concerning the establishment of a central information portal about rare diseases . Since the available space on the website was limited, the most important information categories for patients occupy the most space followed by the less important information categories. Various information requirements on diagnosis, therapy, self-help, research, and specialized care facilities for people living with rare diseases, their relatives, and health care professionals were identified in qualitative interviews (see ). HoweveThe AHP method originates from the marketing sector, invented by Thomas Saaty in the late 1970s. Dolan et al. applied the method of AHP the first time in the health care sector several years later in 1989 , 23. Neva bootstrap 95%-CI because our sample was small and in this case bootstrap CI were more accurate and correct than the standard CI [First, we briefly report the results of information requirements of patients with rare diseases. Second, we compare the results of CR ≤ 0.1 and CR ≤ 0.2 for median, quartiles, and extreme values (as box-plots). Third, different aggregation methods  are used and the differences in results noted. Saaty suggested to calculate group priorities by aggregating judgments or final outcomes by geometric mean to satisfy the reciprocal property of the AHP . Reciprondard CI . All ourndard CI .As a second method in this paper, we applied BWS Case 1 in the same study population population . Here, dUsing ranking cards resulted in an ordinal ranking of criteria, implying that distances between criteria could not be measured. Besides, it was a well-established warm-up task , and couFurthermore, the results from AHP, BWS, and ranking cards were compared. We placed the results in a table and examined differences in the rank. The AHP’s weights could not be compared with the weights from the BWS, because they are based on deviating mathematical calculation methods and scales. In addition, we conducted tests for correlation between the ranks with the help of Kendall’s tau b coefficient. This coefficient was used for rank ordered data, and identifies concordant and discordant rankings between two or more variables . The KenThe study sample consisted of randomly selected participants from the qualitative main study of the ZIPSE project . A positFinancial support for this study was provided in part by a grant from the Federal Ministry of Health. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.Initially, we report the AHP results including the criteria description and their hierarchical arrangement. Then, we show the information criteria priorities evaluated by patients with rare diseases or their relatives. The following subsections investigate the outcomes of different methodological approaches in the AHP method. Finally, we report the comparison of AHP results with BWS and ranking tasks.medical issues, research, current events, and social advisory and support services. The topic of medical issues was again subdivided into diagnosis, treatment, and disease patterns. The first two were split into provider and methods at the fourth level. Disease patterns contained aetiology, frequency, typical symptoms, and progression at the lowest level. At the third level research implied current studies, study results, and registries. Current events at level two contained no further subcategories. The last category at level two was divided into social law counseling, psychosocial counseling, and self-help at level three. Self-help further held the subcategories of personal contacts and online contacts (fourth level). Further details and descriptions can be found in Additional file Figure The sample for our decision analysis consisted of 31 women and 8 men with mean age of 53.82 years. The inequitable distribution of gender was due to the fact of unequal proportions in the qualitative main study.In the first scenario, all participants who reached a CR at second level exceeding 0.1 were excluded from the analyses. Then 22 included participants  remained for further analytical steps. In this scenario, we calculated weights for each included participant and then aggregated the weights (AIP method). The first approach was aggregating the weights by median. In Fig. medical issues were the most important criteria for the participants with a median weight of 0.4548 (SD = 0.1728), followed by social support (weight (w) = 0.1575, SD = 0.1777), and research . The least criterion was information about current events with a median weight of 0.0913 (SD = 0.1550). The SDs of social support, research, and current events indicated high variations of the priorities in the sample.The boxplots show that medical issues with the highest weight for diagnosis (median weight (mw) = 0.4517, SD = 0.2240), followed by treatment , and disease patterns . The second information criterion of research (blue boxplots) included current studies, study results, and registry. The most important sub-criterion was study results with a local weight of 0.4416 (SD = 0.2015), the second current studies , and the third was the information about registries . The green boxplots displayed the local weights for the category of social support. Self-help  reached the highest weight followed by psychosocial counseling , and law counseling with the lowest weight of 0.2167 (SD = 0.1768). We did not compare the global weights of sub-criteria against each other because high weights at the second level  would highly influence the weights at the third level. Therefore, we used the sub-criteria’s local weights for comparisons within each criterion because the global weights were not important for our methodological considerations.Figure t-test indicate no significant differences of median for each criterion (not shown here). However, a difference in the ranking by median occurs at level three: law counseling gained a higher weight for an extended threshold and received rank 9 (w = 0.0310) instead of the 13th and last rank (w = 0.0452). At the same time, psychosocial counseling fell from rank 10 to 13 (weight 0.0372 onto 0.0254). A rank reversal occurs for current studies (weight 0.0353 onto 0.0324) and registries (weight 0.0319 onto 0.0325). In summary, the medians between a lower and a higher CR threshold did not differ significantly. Nevertheless, when small differences in weights occurred, rank reversals could be observed. In this study, rank reversals occurred only for the last four rankings.Figure In the next step, we analyzed differences in global weights by different aggregation methods. All mean calculations were based on geometric mean calculation as it serves the Pareto Principle and therefore seems to be the correct approach in theory , 34. In diagnosis, treatment, and research, because for scenario 1, research (w1 = 0.2038) and treatment (w1 = 0.1862) were more important than diagnosis (w1 = 0.1691), whereas in scenario 2, research (w2 = 0.1916) and treatment (w2 = 0.1892) were less important than diagnosis (w2 = 0.1955). Likewise, the ranking differs for self-help, study results, and disease patterns: in scenario 1, disease patterns (w1 = 0.0940) were more important than self-help (w1 = 0.0871) and study results (w1 = 0.0860), and in scenario 2, it was the other way round . A third rank reversal can be seen for the two scenarios between current studies , psychosocial counseling , and law counseling . The CR for the second level was 0.004 in the first scenario, whereas the CR was 0.05 in the second scenario.Figure current events, registries, and self-help). The last comparison of AIP and AIJ was conducted by their means. Here, the AIP were markedly higher than most of the AIJ, also in comparison with the AIPs of the previously mentioned aggregation methods. Additionally, the weights summed up to 1 at first level, and they yielded the appropriate weights at lower levels. However, the most important question in this context was whether the ranking position changed through the different aggregation methods. Table In the next step, the AIJ and AIP were compared by median. The table for these comparisons can be found in Additional file self-help, which took the ranking positions from 7 to 13 over the different methods. Another striking criterion is current studies, which obtains ranking positions between 5 and 11. Two less intensive varying criteria were social support and disease pattern that differed between 5 positions. The further 9 criteria varied between 3 ranking positions, so a relatively stable valuation could be assumed.The noticeable difference occurs for the criterion Finally, the influence of aggregation method on CR had to be examined. The CR in the scenario of aggregation by geometric mean was markedly lower for AIJ than for AIP , although only participants with a CR ≤ 0.1 were included for the AIP. By using the median  or mean scenario , the CRs were similar, but still much higher than the CR from AIJ by geometric mean, as expected.self-help to results showed CIs from approximately 0.03 to 0.14, and the CIs were rather small, particularly social support. Then, the criteria of current studies, research, disease patterns, therapy, and diagnosis covered a CI from approximately 0.11 to 0.30. A markedly higher CI arose for medical issues (CI: 0.34–0.49). It could be concluded that within the first two groups, the criteria were likely vulnerable to rank reversal. In contrast, the first rank for medical issues was assumed to be robust.Usually AHP examine a combination of (sub-)criteria weights resulting in decision alternatives. Thereafter, the sensitivity of alternatives can be analyzed. However, the underlying study does not integrate a hierarchy level with decision outcomes, but only criteria and sub-criteria. Therefore, we looked at the stability of the criteria’s ranking positions. Consequently, we calculated the CIs for each global weight see Fig. . In addimedical issues in all three methods, followed by social support and research. The least important criterion, current events, was also equal for AHP and BWS, but for the ranking cards it was also ranked position 3. At level three for medical issues, the most important criterion was treatment in the BWS, and diagnosis in the AHP. Disease patterns took the third position in both cases. The sub-criteria for research were ranked as followed for BWS and also AHP: 1) study results, 2) current studies, 3) registry. In the category of social support, the most important sub-criterion was self-help. The positions 2 and 3 differed between BWS and AHP. In the BWS, the second important sub-criterion was law counseling, whereas it was psychosocial counseling in the AHP. The ranking cards results showed doubled ranking positions at all levels, particularly when BWS and AHP were indifferent.In the next section, we wanted to contrast the results of the AHP and the BWS. Table Because the ranking cards gave orientation for the AHP in the interviews, we assumed that there was a correlation between their results. Therefore, we did not evaluate the correlations for AHP and ranking. We examined the correlation between AHP and BWS rankings by Kendall’s tau coefficient, for each hierarchical level. We found significant moderate to strong correlation between the two methods in the rankings  as well as the AIP method (scenario 2). The first difference was the number of participants that were included with a CR ≤ 0.1. In the first scenario, we included 31 participants, and in the second scenario, we had to exclude 9 participants because they showed CRs > 0.1. In the first scenario, we had a CR of 0.004 for the second level calculated after aggregating the judgments. In the second scenario, the CR at the second level was 0.05, and thus higher than in scenario 1, although the participants with CRs > 0.1 were excluded from the final CR calculation. The results received from scenario 1 showed almost the same weights compared to the results from scenario 2. Besides, the criteria’s rankings differed between the scenarios, due to short distances between the weights. The AIJ method implies that the group decides as a new individual whereas the AIP method is based on the assumption that each individual decides on her or his own and the resulting decisions are aggregated . Therefo as well In the third step, we opposed the criteria’s rankings received from aggregated weights and judgments by geometric mean, median, and mean. Here, the ranking positions showed deviating results and rank reversals. These aspects should be considered when results derived by different aggregation methods in studies are compared.As no sensitivity analysis is suggested for AHPs that do not include alternatives, we tried to find an appropriate one. The aim of sensitivity analysis in AHP is to find instable criteria that could cause rank reversal. Therefore, we illustrated the 95%-CIs for all criteria. Where CIs overlap because of similar weights, the risk for rank reversal increased.Finally, we evaluated the criteria’s rankings for the different methods . However, we could not compare the weights from AHP with the weights from the BWS, because they use different scales. Therefore, only the rankings could be compared between the methods. Here, we found moderate to strong correlations between the AHP and BWS.Correlated results between the methods were similarly reported by prior studies. Pignone et al. (2012) investigated differences in value elicitations with CA, rating, and ranking tasks . They coA major problem was the inconsistent response behavior of the participants in the AHP. Our sample consisted of patients with different rare diseases. The diverse clinical pictures and disease stages could have led to different priorities in the evaluation of the information criteria. Although in our study the participants used ranking cards for assistance during the AHP, the CRs were not all below the defined threshold. This phenomenon raised the question, whether the AHP method was not applicable in certain participant groups or in a heterogeneous sample. Therefore, future research projects should investigate the requirements for their participants, because this could bias the results. Further studies should also examine whether the aggregation of judgments always leads to higher values than the aggregation of weights, as detected in our study.Another aspect was the small number of participants. Although we neglected this aspect in our study, the number of participants could also be an influencing factor of the results. Recent literature suggests that AHP is particularly useful for small groups, because priorities can be calculated for each participant . As we uIn the AHP method, the number of patients is influenced by the CR aggregation method and the threshold of the CR, which could bias the results. Therefore, it is important to establish guidelines and investigate the differences for each study as also mentioned by Schmidt (2015) . The comThe AHP seemed to be a challenge for some participants. Reasons could be the unusual scale and the need for consistency over several questions. However, we could not identify special groups because our sample was too small and homogenous. The BWS also forced the participants to make decisions. However, here only the best and worst decision had to be made. Therefore, the cognitive burden is reduced compared to other methods, for example, the DCE . The res