The association of familial hypercholesterolemia (FH) with risk of cardiovascular events (CVE) and death in different cohorts is controversial. We aimed to assess the risk of CVE and death in patients with FH in different cohorts, including CHD and ACS patients, White and Asian, different diagnostic criteria.We searched PubMed, MEDLINE, and Web of Science electronic databases through May 2021 to identify cohort studies of CVE and death in patients with FH.We found 18 eligible studies with 1,139,788 participants, including 34,261 patients. There were 31,287 ACS patients, of whom 2,338 were combined with FH. Randomized-effects meta-analysis showed that in patients with FH, relative risk (RR) of CVE and death was 1.87 (95% CI 1.21–2.88), among which CVE was 2.14 (95%CI 1.26–3.64), all-cause of death RR = 1.12 (95% CI 0.89–1.41), and cardiac death RR = 1.03 (95% CI 0.59–1.79). Risk of CVE and death in general population with FH was 2.85 (95% CI 0.72–11.21), hyperlipidemia population RR = 1.59 (95% CI 1.05–2.41), coronary heart disease patients (CHD) RR = 1.46 (95% CI 1.24–1.72), and acute coronary syndrome patients (ACS) RR = 1.71 (95% CI 1.19–2.46). Among ACS patients, the RR of CVE in patients with FH was 1.91 (95% CI 1.55–2.35), the RR of all-cause of death was 1.03 (95% CI 0.80–1.32), and the RR of cardiac death was 1.03 (95% CI 0.59–1.79). The risk of CVE and death in ACS patients with FH in White was 1.69 (95% CI 1.09–2.64) and Asian 1.90 (95% CI 1.31–2.75). RR in patients with Dutch Lipid Network criteria (DLCN) ≥6 vs. <3 points was higher . RR for long-term follow-up was 1.68 (95% CI 1.09–2.61) and for short-term follow-up was 1.80 (95% CI 1.16–2.78). The results of the overall population were similar, but RR for overall population during a short-term follow-up was 1.49 (95% CI 0.81–2.73). We followed PRISMA checklist to complete meta-analysis.The risk of CVE and death was increased in patients with CHD, especially in patients with ACS. DLCN ≥ 6 points was suggested for clinical diagnosis of FH. The risk of long-term and short-term CVE and death increased in ACS patients with FH.INPLASY2021110010. LDLR, APOB, PCSK9 and other genes  is an autosomal dominant hereditary disease characterized by a considerable increase in lifetime total cholesterol (TC) and low-density lipoprotein (LDL), including mutations in er genes . Exposeder genes . Previouer genes . A recener genes . Therefoer genes . HoweverWe did a meta-analysis about the association between Familial Hypercholesterolemia and risk of cardiovascular events (CVE) and death in different cohorts according to PRISMA guidelines. We searched the PubMed, MEDLINE, and Web of Science databases to identify cohort studies reporting the outcome of CVE and death in patients with FH. The article was published from database inception to June 2021. We also reviewed the reference lists of relevant articles to identify additional studies. A broad search strategy based on MeSH Term was used, as follows:  AND (“prognosis” OR “follow-up”). We use this extensive search strategy to avoid missing potential studies. Two researchers independently screened the literature, evaluated quality, and extracted data.Inclusion criteria were: (1) cohort study; (2) included participant groups with and without FH; (3) outcome was at least one cardiovascular event  or death ; (4) provided risk ratio, survival curve, or event rate to calculate the relative risk ratio (RR); and (5) If the same study publishes results from different periods, include the most recent study data.Exclusion criteria were: (1) duplicate or missing information; (2) meta-analysis or systematic review; (3) only included children; (4) conference summaries, guidelines, case reports, letters, and similar reports; (5) animal studies, randomized controlled trials, or diagnostic tests; and (6) We a-priori excluded studies with non-English language owing to quality concerns.Two investigators independently extracted data, including the first author's name, date of publication, country, cohort years, sample size, number of events, follow-up time, and hazard ratio (HR) or RR. In the case of disagreement, a third researcher was consulted. Exposure data included the definitions and criteria for FH, number of participants, and duration of follow-up. Outcome data included the definitions of cardiovascular outcomes, number of participants with and without FH, multivariate-adjusted risk estimates , and variables included in the multivariate analysis. Because the included studies are cohort studies, We used the Newcastle–Ottawa Scale (NOS) to evaluate the quality of the included studies. Two researchers evaluated independently. If the opinions are inconsistent, it shall be solved by a third party.Stata 16.0 software was used for meta-analysis . The RR and 95% confidence interval (CI) were used together with the effect size. The results of each cohort study were reported as RR, HR, OR, or binary frequency data. We used algebraic methods to convert the OR and frequency data to RR. If feasible, we used adjusted risk estimates from a multivariate model ; animal studies (n = 11); studies including children (n = 140); meetings, guidelines and case reports (n = 68); reports with missing information (n = 29); diagnostic experiments and treatment plans (n = 265); and non-English articles (n = 9). Initially, 145 studies were included. We excluded 119 irrelevant articles after reading the abstract and 8 after reading the full text; thus, 18 articles were finally included , so we used the random-effects model for meta-analysis. Different subgroup analyses of patients with or without FH are shown in The heterogeneity among studies was significant  . SimilarWe conducted subgroup analysis for different cohorts. The RR for general population, hyperlipidemia, CHD, ACS and overall were 2.85 (95% CI 0.72–11.21), 1.59 (95% CI 1.05–2.41), 1.46 (95% CI 1.24–1.72), 1.71 (95% CI 1.19–2.46) and 1.75 (95% CI 1.24–2.46), respectively . The RR Subgroup analysis was performed in ACS patients. Using DLCN as the standard score, the score ≥6 was FH, and the scores <3 was non-FH, RR was 2.24 (95%CI 1.69–2.97) . The resPatients with ACS and FH had an increased risk in follow-up ≤1 year and >1 year  . HoweverThe risk of CVE and death in patients with FH was no related to ethnicity, regardless of the ACS patients or the overall population. The RR of ACS patients with FH was 1.69 (95% CI 1.09–2.64) in white patients and 1.90 (95% CI 1.31–2.75) in Asian patients . While iI2 = 99.3%, I2= 0%); There is still considerable heterogeneity in studies of all-cause of death (I2= 74.51%). Therefore, different prognostic events were considered to be important sources of heterogeneity (P = 0.00)  (P > 0.1), studies grouped by the above factors showed large differences in RR (There was significant heterogeneity between studies ( = 0.00) . Similar = 0.00) . Althouges in RR . We did es in RR . The subWe performed a sensitivity analysis to test the robustness and sources of heterogeneity of our meta-analysis results. First, we used the method of omitting one study at a time to conduct a sensitivity analysis for risk of total cardiovascular events and death ; Table 3In this meta-analysis, we found that the latest current evidence from 18 longitudinal studies involving 1,139,788 participants showed that the risk of CVE and death was significantly increased in patients with FH, and the RR was higher after adjusting for time factors, . SimilarOne of the most important problems with FH at present is its low detection rate. However, the detection rate of FH in patients with CHD, especially ACS, is 10 times higher than that of the general population , 26. Ourn = 3,233), which was a defect of the study. Nanchen et al. found that the prevalence of FH detected using three different clinical diagnostic criteria differed, and the prognosis risk also differed , especially in retrospective studies, the rate of missed diagnosis of FH is high. Gene testing is the gold standard for FH diagnosis. The genetic diagnostic subsets in this study were highly homogenous. However, due to its high cost, it is difficult to be widely used in clinical practice. The number of subjects with genetic diagnosis in this study was only 2.37%  of FH all-cause of death, and the SMR of cardiac death was significantly higher . Some stIn this study, the current data results do not indicate a significant difference in the risk of prognosis of FH between Whites and Asians, which may be related to the different populations and diagnostic criteria. And the number and proportion of cases involving Asians are very small. Some Asian studies have shown that the DLCN and SB criteria are not applicable to Asian populations, with some changes having been proposed , 38. ForOur results showed that patients with FH had a higher RR of CVE and death. The more co-morbidities and longer follow-up, the higher RR of CVE, but ACS patients with short-term follow-up also had a higher risk of CVE and death. young FH patients may have a greater risk of prognosis. These findings suggest that clear clinical diagnostic criteria (such as DLCN score ≥6 vs. <3) or genetic testing should be used to diagnose FH so as to reduce missed diagnoses of FH and accurately identify patients with FH and prognostic risk, for timely assessment of whether high-intensity lipid-lowering therapy is needed to improve poor clinical prognosis. (Registration Number: INPLASY2021110010. There is no modification to the protocol or registration information).First, the heterogeneity among studies was significant, which may be owing to the different populations, diagnostic criteria, follow-up times, and defined outcome events. Different diagnostic criteria and outcome events in particular contribute more to the heterogeneity among studies. Second, some studies did not report the rate of loss to follow-up, so we could not accurately evaluate bias owing to loss to follow-up nor whether this bias is an important source of heterogeneity and whether it could lead to overestimation of the prognosis risk of FH. Third, our subgroup analysis was a non-paired analysis; we cannot exclude the influence of the differences in factors other than grouping factors  on subgroup comparisons. However, this is a common shortcoming in subgroup analyses of all systematic reviews. Finally, the number of FH subjects was significantly less than that of non FH subjects, which is an irresistible factor and may lead to overestimation of the results. Therefore, we need simple and accurate screening methods to improve the diagnosis rate of FH.The original contributions presented in the study are included in the article/YL and YC designed the research. YY and LC performed the experiments and analyzed the data. YY wrote original draft. LC, HZang, and ZF collected the data and revised the article. QL and HZhao revised and prepared the figures. All authors reviewed and agreed to the manuscript.This work was supported in part by Beijing Lisheng Cardiovascular Health Foundation Pilot Fund key projects to YC, the National Natural Science Foundation of China under Grant 81827808, and the Chinese Cardiovascular Health Alliance -Advanced Fund under Grant 2019-CCA-ACCESS-054.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Studies on the association of Sievers bicuspid aortic valve (BAV) morphology with conduction disorders after transcatheter aortic valve replacement (TAVR) have not reached consensus.We here performed a pooled-analysis to explore whether Sievers type 1 BAV morphology increased the risk of post-TAVR conduction abnormalities and permanent pacemaker implantation (PPI) compared to type 0. Systematic literature searches through EMBASE, Medline, and Cochrane databases were concluded on 1 December 2021. The primary endpoint was post-TAVR new PPI and pooled as risk ratios (RRs) and 95% confidence intervals (CIs). Conduction abnormalities as the secondary endpoint were the composites of post-TAVR PPI and/or new-onset high-degree of atrial-ventricle node block and left-bundle branch block. Studies that reported incidence of outcomes of interest in both type 1 and type 0 BAV morphology who underwent TAVR for aortic stenosis were included.RR = 1.68, 95%CI 1.09–2.60, p = 0.0195) and new PPI  compared to type 0. Random-effects univariate meta-regression indicated that no significant association between baseline characteristics and PPI.Finally, nine studies were included. Baseline characteristics were generally comparable, but type 1 population was older with a higher surgical risk score compared to type 0 BAV morphology. In the pooled-analysis type 1 BAV had significantly higher risk of post-TAVR new-onset conduction abnormalities (Sievers type 1 BAV morphology was associated with increased risk of post-TAVR PPI and conduction abnormalities compared to type 0. Dedicated cohort is warranted to further validate our hypothesis. Large randomized-controlled trials have proved the safety and efficacy of transcatheter aortic valve replacement (TAVR) for native tricuspid aortic valve stenosis , 2. NevePost-TAVR new-onset conduction disorders like high-degree atrial-ventricle node block (HAVB) and new permanent pacemaker implantation (PPI) were associated with increased adverse events . ProceduThe systematic review and pooled-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  and recoSystematic literature searches through EMBASE, Medline, and Cochrane databases were concluded on December 1, 2021. The search strategy included (1) “transcatheter aortic valve implantation” OR “transcatheter aortic valve replacement” OR “percutaneous aortic” OR “transcatheter aortic valve,” (2) “conduction” OR “block” OR “pacemaker,” (3) “bicuspid,” then combined (1) AND (2) AND (3). A manual search was performed using references in published articles and conferences to identify potentially relevant research.The search results were screened and viewed in the title and abstract first to identify relevant studies. Case reports and case serials were not qualified for screening. All identified relevant studies were then placed under full-text review to further validate the eligibility.Based on Population, Intervention, Control, Outcome, and Study Design (PICOS), studies were eligible if they met the following criteria: (1) enrolling BAV population; (2) undergoing TAVR for aortic stenosis; (3) available incidence of post-TAVR PPI or conduction abnormalities in Sievers type 1 and type 0 BAV morphology.The primary outcome of interest was post-TAVR new PPI. The occurrence of high-degree atrial-ventricle node block (HAVB) or in some centers left-bundle branch block (LBBB) was an indication for PPI and might be associated with worse outcomes as well . We defiSpecifically, type 1 BAV were further classified according to the location of fused raphe and cusp: L-R, raphe between left- and right-coronary cusp; R-N, raphe between right- and non-coronary cusp; L-N, raphe between left- and non-coronary cusp . The eveConsidering all included studies were observational, we used Newcastle-Ottawa Scale to assess the quality of included studies. Two authors (JZ and XL) independently completed databases searching and study screening and evaluations. Discrepancies were settled by a third researcher (YC).Duplicates and data overlap were confirmed by authors information and study start and end time, choices were made based on the evaluation of study quality, time period, and the number of subjects. The PRISMA flowchart is provided in CIs) using the Mantel-Haenszel method with random-effects models. A two-tailed p <0.05 was considered statistically significant. Heterogeneity across studies was calculated by I2 and I2 > 50% was deemed unacceptable heterogeneity. Baujat plot and L'Abbé plot were drawn to visualize the origin of heterogeneity. Sensitivity analysis was conducted by removing one or more specific study/studies from the whole collection each time to evaluate the robustness of the pooled results and explore heterogeneity. As observational studies would introduce huge confounding effects and may lead to a biased estimate, we performed a random-effects univariate meta-regression to adjust for the influence of potential effect modifiers. Demographic characteristics and clinical parameters were selected as covariates. Subgroup analyses were performed according to valve type . The publication bias of each item was examined by funnel plots visually based on the symmetry.Following statistical analyses were completed on R (version 4.1.3) with Meta package . The pooAfter dedicated literature search and selection, 9 studies were included in the final pooled-analysis , 16–22. Generally, demographic characteristics were comparable between type 1 and type 0 BAV morphology; however, there was a relatively higher STS score in type 1 population. Patients across surgical risk profiles were included and most of them were in their 70's and had New York Heart Association functional class> 2. No patient included in the pooled-analysis had prior PPI. During the TAVR procedure pre-dilation was more frequently used in type 0 than type 1. No difference was found between type 1 and type 0 with regard to other procedural characteristics. In the 9 included studies, 4 were SEV-specific , 16, 22 RR = 1.97, 95%CI 1.29–2.99, p = 0.0016)  which testified the stability of our pooled result  . After ed result .RR = 1.68, 95%CI 1.09–2.60, p = 0.0195). The funnel plot was generally symmetric . Drawing L'Abbé plot   .This is the first pooled-analysis that focuses on the association of Sievers BAV morphology with post-TAVR conduction disorders. Our pooled-analysis demonstrated that there was a higher risk of post-TAVR PPI and conduction abnormalities for type 1 BAV morphology than for type 0.The bicuspid aortic valve as the most common congenital heart disease affects 1~2% of the world population and is the predominant etiology for aortic stenosis in the young population . TAVR foAssociation of BAV morphology with conduction disorders was poorly discovered and such study was scarce. Current observations only indicated numerically but not a statistically higher incidence of post-TAVR PPI for type 1 BAV morphology than type 0. For example, in the Low Risk Bicuspid Study 22 in 132 type 1 needed PPI but none for type 0 . As for Different from SAVR resecting the native valve, the valve in TAVR is reserved and has strong interaction with the implanted transcatheter heart valve . This coIn another view, there are several recognized risk factors for post-TAVR PPI in the BAV population. Deep implantation and oversizing of implanted valves would increase the chance to injure the conduction system –10, 17. 2 dropped sharply to zero, which verified their contribution to the heterogeneity. Actually, in the present pooled-analysis, conduction abnormalities were composite of HAVB, LBBB, and/or PPI. Endpoints in studies of Guo et al. and Hamdan et al. were truly composite, but that in the Ou et al. and the other studies were solely new-onset HAVB and post-TAVR PPI, respectively. Differences among the definitions may lead to heterogeneity. Accordingly, we performed the pooled-analysis with a concentration on post-TAVR PPI then set the composite conduction abnormalities as the secondary endpoint, and the pooled estimates of both suggested a higher risk for type 1 BAV morphology with consistency.There was moderate heterogeneity in the pooled-analysis comparing the risk of post-TAVR conduction abnormalities between type 1 and 0. L'Abbé plot and Baujat plot indicated that the study of Ou et al. and Guo et al. contributed most to the heterogeneity, and the sensitivity analysis excluding the two showed IAccording to Sievers classification, type 1 could be further divided into 3 subtypes depending on the fused cups and raphe location, namely L-R, R-N, and L-N . Type 1 The pooled results should be interpreted with caution because of the following reasons. First, besides type 0 and type 1 BAV morphology, the Sievers classification also included type 2 and undetermined BAV morphology, but they were not included in our analysis because of their extremely low prevalence and scarce data. Second, all included studies were observational so adjustment for confounding factors was necessary. Meta-regression, we preformed, demonstrated no correlation between the effect modifiers and the pooled estimate, which relieved the confounding bias; however, there was relatively small number of studies included in the regression. Moreover, baseline conduction disorders, such as LBBB and RBBB, could be predisposing factors to post-TAVR HAVB and PPI, but such prevalence was seldom reported. Only Guo et al. presented a similar prevalence between type 1 and type 0, so the effect of baseline conduction disorders on the association was unknown. Last but not least, we must recognize the purpose of the pooled analysis was hypothesis-generating rather than proving type 1 BAV morphology as a strong predictor. We uncovered a rarely noticed association that needs more research to further validate.The current study found there was a higher risk of post-TAVR conduction abnormalities and PPI for Sievers type 1 BAV morphology than type 0, and the type 1 subtype L-R have no excess risk of post-TAVR conduction abnormalities compared to the non-L-R subtype. Our hypothesis that type 1 BAV morphology is a novel risk factor for conduction abnormalities warranted large cohorts to validate.The original contributions presented in the study are included in the article/JZ and XL independently completed the database searching, screening, and data extraction and wrote the manuscript. FX provided suggestions on statistical analysis and finished the pooled-analysis on R software. YC took responsibility for data checking and evaluated the eligibility of unsettled studies between JZ and XL. CL contributed to the discussion and revised the finished manuscript. All authors contributed toward data analysis, drafting and critically revising the paper, and agree to be accountable for all aspects of the work.This study was supported by the National Natural Science Foundation of China (82070388), Taishan Pandeng Scholar Program of Shandong Province (tspd20181220), and the National Natural Science Foundation of Shandong Province (ZR2020MH035).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Epidemiologic studies have demonstrated that X-ray repair cross-complementary group 1 (XRCC1) is one of the susceptibility factors in head and neck squamous cell carcinoma (HNSCC) patients. However, its clinical prognostic impact remains controversial. Thus, a meta-analysis was performed to clarify the association between XRCC1 and the survival outcomes in HNSCC patients.Methods: Following the Preferred Reporting Items or Systematic Reviews Meta Analyses (PRISMA) 2020 guidelines, literature searches were systematically performed in PubMed, EMBASE, Web of Science, Wanfang, and Chinese National Knowledge Infrastructure (CNKI) databases with manual retrieval. Hazard ratios (HRs) and 95% confidence intervals (CIs) were collected to estimate the correlation between XRCC1 and the survival outcomes of HNSCC patients.Results: Ten studies including 1995 HNSCC patients who satisfied the inclusion and exclusion criteria were included in this meta-analysis. Pooled analysis indicated that XRCC1 Arg399Gln and XRCC1 high protein expression were significantly correlated with poor overall survival with HR of 1.31  and 2.32 (95% CIs: 1.55-3.48 p = 0.000) in HNSCC patients. In addition, our results demonstrated that XRCC1 was significantly associated with poor progression-free survival  in HNSCC patients.ConclusionThis meta-analysis demonstrated that XRCC1 Arg399Gln and XRCC1 high protein expression increase the risk of poor survival for HNSCC patients. XRCC1 is a potential therapeutic target for HNSCC. Head and neck squamous cell carcinomas (HNSCC), heterogeneous collection of malignancies of the upper aerodigestive tract, salivary glands and thyroid, constitute 90% of cancers that arise in the head and neck . HNSCC rTwo major classes of DNA repair pathways are base excision repair (BER) and single-strand break repair (SSBR). The primary defense mechanism against oxidative DNA damage is BER . X-ray rSeveral studies have investigated that XRCC1 gene polymorphisms (Arg399Gln and Arg194Trp) increase the risk of HNSCC  and suggWe conducted a systematic computerized search in PubMed, Web of Science, EMBASE, Wanfang, and Chinese National Knowledge Infrastructure (CNKI) databases using the following search terms (XRCC1 or X-ray repair cross-complementing 1) and  and  and (squamous cell cancer or carcinoma). Articles published between 1992 and 2022 were considered for study inclusion. The latest search was conducted on 1 June 2022.p values with Kaplan- Meier survival curves that can be estimated for OS and/or PFS.According to the PICOS  principles, the inclusion criteria of the meta-analysis were as follows: 1) Population: patients of any age diagnosed with HNSCC; 2) Intervention: expression of XRCC1 in HNSCC was assessed by immunohistochemical (IHC) analysis. The target gene polymorphisms for XRCC1 were Arg399Gln (rs25487) and/or Arg194Trp (rs1799782) and assessed by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP); 3) Comparison: HNSCC patients without concentration on high XRCC1 expression or without concentration on XRCC1 Arg399Gln (rs25487) and/or Arg194Trp (rs1799782); 4) Outcomes: overall survival (OS) between XRCC1 and HNSCC as a primary outcome. Progression-free survival (PFS) between XRCC1 and HNSCC as a secondary outcome; 5) Study design: Any human-based studies; 6) including hazard ratios (HR) and the 95% confidence interval (CI) directly, or The criteria of exclusion included: 1) abstract-only publications, letters, case reports, meta-analyses, comments, conference articles, on-going or unavailable literature; 2) studies with insufficient original data or focused only on odds ratio without HR values. In case of the same population reported by several publications, the latest literature gained the priority.Two researchers (Jing-cai Chen and Yao Luo) independently conducted the electronic search. Data were carefully extracted and cross-checked by two independent researchers (Liu-qing Zhou and Fan Yang) to minimize variation. If there were divergences, the senior researcher (Yan-Jun Wang) participated in the progress of data extraction for achieving a consensus. To begin with, we removed duplicate literature. After manual screening titles and abstracts, publications were eligible for full-text perusal. Finally, studies that meet the selection criteria were included in this meta-analysis. The following information was extracted from each included study: the name of the first author, year of publication, country, cancer type, sample size, age, gender, stage, follow-up time, survival outcomes, method, HR. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included publications. A star system (maximum is nine stars) of NOS concentrated in three domains: comparability of study groups, selection of participants and ascertainment of outcomes of interest. Studies with NOS ≥6 were high-quality . Reportip values from Kaplan- Meier survival curves following Parmer’s methods . Otherwise, the random-effects model was applied  and recalculating the summary effect size at each iteration until the funnel plot becomes symmetric (Heterogeneity was assessed by the Cochran-based Q test and the I2 test . p < 0.1 applied . Moreove applied . Publica applied . The asyymmetric . All theAs shown in The characteristics of the enrolled studies were summarized in p = 0.027) and XRCC1 high protein expression  were significantly correlated with poor OS in HNSCC patients by the random-effects model. However, XRCC1 Arg194Trp was not a risk for HNSCC patients . The degrees of heterogeneity are as follows: I2 = 0–25%, no heterogeneity; I2 = 25–50%, moderate heterogeneity; I2 = 50–75%, large heterogeneity; I2 = 75–100%, extreme heterogeneity . Large heterogeneity was noted between XRCC1Arg194Trp and OS . No heterogeneity was noted between high XRCC1 expression and OS . Overall, the pooled heterogeneity of XRCC1 in OS was large  (p = 0.001) was observed with no heterogeneity   . Signifi= 0.286) .The sensitivity analysis was conducted to evaluate the effects of each single study on the overall effect. We conducted a leave-one-out sensitivity analysis to evaluate the effect of each single data point against the aggregate. The recalculated outcomes  were notp = 0.03). Therefore, “trim and fill” analysis was further utilized and the pooled HR was 1.246 (95% CIs: 0.967–1.607)  .2 = 56.7%, Pheterogeneity = 0.014). p < 0.10 suggested the heterogeneity is significant and I2>50% indicated the heterogeneity is large across studies. The random-effects mode was employed for analysis with large significant heterogeneity across studies . The fixed-effects model would be performed for analysis with no obvious heterogeneity between studies . Considering the existence of large-significant heterogeneity in our meta-analysis, a random-effects model was chosen for the generation of pooled indexes. The sensitivity analysis confirmed this meta-analysis is stable and reliable. The asymmetric funnel plot and the Egger’s test (p = 0.03) conferred that a significant publication bias existed in our study. Thus, we implemented “Trim and fill” analysis to judge the impact of publication bias. The method of “Trim and fill” analysis was conducted by removing the small studies with the most extreme results (trim) and recalculating the summary effect size at each iteration until the funnel plot becomes symmetric. Results showed that the point estimate of the overall effect size is approximately correct in our study .In the present meta-analysis, we included ten studies with 1995 HNSCC patients. Results indicated that the XRCC1 gene polymorphism Arg399Gln and XRCC1 high protein expression were significantly associated with poor OS for HNSCC patients and XRCC1 was significantly associated with poor PFS. There was large heterogeneity in our study . Therefore, it is reasonable to quest potential biomarkers of treatment by analyzing genomic features.http://www.ncbi.nlm.nih.gov/SNP). Among them, the XRCC1 gene polymorphisms (Arg194Trp and Arg399Gln), which occur within conserved sequences, are the most frequently mutated and the most extensively studied.DNA repair genes have been considered driver genes of HNSCC due to their frequent mutation. Defects in DNA repair promote genomic instability and carcinogenesis . DNA repStudies have investigated the association between XRCC1 Arg399Gln/XRCC1 Arg194Trp polymorphisms and HNSCC risk . HoweverThis meta-analysis prospectively evaluated XRCC1 as a bio-predictor of survival outcomes in patients with HNSCC. There is no doubt that our study is the first meta-analysis including ten published studies with 1995 patients to comprehensively evaluate the survival value of XRCC1 (SNPs and high protein expression) in HNSCC. It might offer useful information for clinical decision-making in HNSCC.After analyzing and summarizing all selected data, the results indicated that high protein expression and Arg399Gln SNPs of XRCC1 significantly predicted poor OS in HNSCC patients with HRs of 2.32 and 1.31. These findings confirmed that XRCC1 could be widely applied as a diagnostic marker and therapeutic target in HNSCC patients. As a genetic-associated study, the Hardy-Weinberg (HWE) principle was used to avoid methodological weaknesses, such as biased selection of subjects or genotyping errors. The enrolled studies in our meta-analysis were all in agreement with HWE principle.This meta-analysis should be interpreted within the context of its limitations. First, all included studies are published with English languages only. Therefore, publication bias is very likely to occur. Second, the number of articles was limited and the sample size was relatively small in the present meta-analysis. False-positive or false-negative findings may have occurred in small sample sizes. Therefore, larger scale and comprehensive studies are needed to achieve a more persuasive conclusion. Third, large heterogeneity was observed in this meta-analysis. The heterogeneity of the included studies was likely due to differences of the baseline characteristics in patients or different sites of HNSCC or tumor treatments or HRs calculated by Parmer’s methods or other parameters. A random-effects model was conducted to minimize the effects of these differences. Forth, studies with positive results are more likely to be published and thus more likely to be enrolled. Hence, the survival association of XRCC1 in HNSCC may to some extent has been overestimated in this meta-analysis.In conclusion, our meta-analysis demonstrated that XRCC1 gene polymorphism Arg399Gln and high protein expression of XRCC1 were associated with poor OS in HNSCC patients. And XRCC1 was significantly associated with poor PFS in HNSCC patients. This current meta-analysis might provide favorable data for future application of XRCC1 as bio-predictor for HNSCC treatment. Larger prospective studies should be conducted in the future to further verify the results in the present study.


However, the effect size of statin use on the risk of gastric cancer was lower in Asian studies compared to Western studies . These findings suggest that the use of statins is associated with a reduced risk of gastric cancer. This reverse association was even stronger among Asian people than Western individuals.Previous epidemiological studies have reported that the use of statins is associated with a decreased risk of gastric cancer, although the beneficial effects of statins on the reduction of gastric cancer remain unclear. Therefore, we conducted a systematic review and meta-analysis to investigate the association between the use of statins and the risk of gastric cancer. Electronic databases such as PubMed, EMBASE, Scopus, and Web of Science were searched between 1 January 2000 and 31 August 2022. Two authors used predefined selection criteria to independently screen all titles, abstracts, and potential full texts. Observational studies (cohort and case-control) or randomized control trials that assessed the association between statins and gastric cancer were included in the primary and secondary analyses. The pooled effect sizes were calculated using the random-effects model. The Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guidelines were followed to conduct this study. The total sample size across the 20 included studies was 11,870,553. The use of statins was associated with a reduced risk of gastric cancer (RR Helicobacter pylori (H. pylori) infection) and non-modifiable  risk factors are associated with gastric cancer [Gastric cancer is a common public health problem associated with a substantial healthcare burden . Gastricc cancer ,6,7,8.Statins are the most commonly prescribed medications and are considered to be effective for lowering cholesterol and protecting against cardiovascular diseases ,10. PrevAlthough statins showed the potential benefits of reducing the risk of gastric cancer, no updated systematic review and meta-analysis of their association has been conducted. This study, therefore, conducted an updated systematic review and investigated the relationship between statin use and the risk of gastric cancer. The evidence of this study will provide adequate answers to this topic and may assist clinicians in weighing the benefits of statins in gastric cancer.This study was based on two main questions. Question 1 was defined as follows: Are patients treated with statins associated with a reduced risk of gastric cancer? Question 2 was defined as follows: Do subgroup analyses support the effect size of the association between statin use and gastric cancer risk? The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement and the guidelines for Meta-analysis Of Observational Studies in Epidemiology (MOOSE) were properly followed to conduct this study ,19 Supp.We conducted a comprehensive search on the most popular databases for scientific literatures such as PubMed, EMBASE, Scopus, and Web of Science to obtain all English-language studies published between 1 January 2000 and 31 August 2022. We considered studies that evaluated the association between statin use and the risk of gastric cancer. The following search terms were used: “statin/s” or “hydroxymethylglutaryl-CoA reductase inhibitors” or “lipid-lowering drugs” or “atorvastatin” or “fluvastatin” or “lovastatin” or “pitavastatin” or “pravastatin” or “rosuvastatin” or “simvastatin” and “gastric cancer” or “gastric carcinoma” or “gastric neoplasm” or “stomach cancer” or “stomach carcinoma” or “stomach adenocarcinoma” or “stomach neoplasm” or “cancer” . AdditioAll observational studies  and randomized control trials (RCTs) that met the following criteria were included: (1) studies that carried out at least one analysis assessing the effect of statins use on gastric cancer, (2) patients with an established diagnosis of gastric cancer by accepted clinical and/or histologic criteria, (3) studies published in English, and (4) studies that provided sufficient information to calculate the pooled effect size. We excluded studies if they were reviews, letters, case reports, or editorials.Two authors (CCW and MMI) independently extracted information from all selected studies using piloted data extraction sheets. Extracted data included (1) demographics: author name, publication year, country, (2) population: age, gender, percentage of male, number of statin users, number of gastric cancer patients, (3) methods: study design, inclusion and exclusion criteria, and (4) results: effect sizes . Any disagreement during the study screening process was resolved by discussing with the third author.The risk of bias of RCTs was assessed using the Cochrane Collaboration tool , which i2. The I2 values were classified into four groups: of 0~29%, 30~49%, 50~74%, and 75~100%, representing very low, low, medium, and high inconsistency, respectively [p < 0.05 was considered statistically significant.We used ORs and HRs to calculate the overall pooled effect sizes of statin use on the risk of gastric cancer. The pooled RRs were calculated using random-effects models. We calculated heterogeneity across studies using the Q-statistic and quantified using the inconsistency Iectively ,23,24. WThese 20 studies consisted of 9 cohort, 8 case-control, and 3 RCTs studies, which comprised of 11,870,553 participants. Twelve studies were conducted in Asia and eight studies were conducted in Western countries. A total of 17 out of 20 studies used administrative databases to identify statin users and gastric cancer patients. More than half of observational studies were of good quality, reflected by a Newcastle-Ottawa score of at least 8. 2 = 92.63, Q = 272.69, τ2 = 0.05) in the random-effects model. Twenty studies  reporting the effect of statins on gastric cancer were included in the meta-analysis. When all adjusted effect sizes were pooled, the summary RR in statin users compared with statin nonusers from the random-effects models was 0.72 (95%CI: 0.64–0.81). There was significant heterogeneity across studies , 0.61 (95%CI: 0.48–0.77), and 0.82 (95%CI: 0.65–1.04), respectively. However, there was significant heterogeneity across the studies .2 = 92.67, Q = 150.22, τ2 = 0.05) and 0.88 , respectively.The pooled RRs for the studies from Asia and Western countries were 0.62 , and 0.72 (95%CI: 0.55–0.94), respectively. However, there was moderate heterogeneity across the studies.Kim et al.  evaluateCheung et al.  investedp = 0.09).In this updated systematic review and meta-analysis, we evaluated the association between statin use and the risk of gastric cancer, which is currently unclear. Our findings are similar to previous evidence ,45,46,47The possible biological mechanisms as to how statin use reduces the risk of gastric cancer is still unclear. However, several biological pathways may help to understand the process of their association. Statin reduces the production of cholesterol, dolichol, and coenzyme Q10 by inhibiting HMG-CoA reductase in the mevalonate pathway ,49. PrevThe effect size of the relationship between statin use and the risk of gastric cancer was different in Asian and Western population. Statin use significantly showed a reduction of gastric cancer in Asian populations, but no association was observed in Western populations. Previous studies assessed statin responses between Asians and Westerners (European Americans), showing a difference in pharmacokinetic and pharmacodynamic effects ,59. StudThe findings of our study also showed that the reduction of gastric cancer among statin users was higher in the case-control studies compared to cohort and RCTs. The inherent risk of bias among case-control studies is consistently high due to potential confounding factors. In the cohort studies, maximum efforts are given to reduce the possible biases, although it does demonstrate a causal relationship. In the clinical-decision making, RCTs are considered the gold standard of study design, revealing the causal relationship between a drug and gastric cancer risk. On the other hand, more chemo-preventive effects of statins were observed in the low-quality studies, which may overestimate their true effect. Low-quality studies often contain a lack of random patient allocation and a lack of adjusting for numerous covariates; therefore, it is not possible to eliminate the possibility of residual confounding factors. Included studies also demonstrated that statins are even more protective against gastric cancer if patients take a higher dose over a longer duration of time ,27,28. KThere are several strengths in this study. First, this is the most updated systematic review and meta-analysis so far that evaluated the relationship between statin use and gastric cancer risk. We included both RCTs and observational studies to summarize overall effect size that ensures the best available evidence through a meta-analytic approach. Second, this meta-analysis included a large sample size and the quality of included studies were high. Therefore, the findings of this study were more reliable. Third, we could identify statin as an independent risk factor for gastric cancer since we adjusted with potential confounding factors to estimate the pooled summary size.This study also has several limitations. First, most studies were observational studies with a highly heterogeneous population with different patient characteristics. The heterogeneity among the studies was high, although this can be explained by study design, region, and study quality. Second, there was limited information regarding the types of statins, indication, follow-up, and duration of statins; therefore, we were unable to pool effect size based on dosage, duration, and follow-up. Third, several potential covariates/confounders related to gastric cancer risk have not been adjusted in the included study. Future studies should adjust all possible confounders to pool the effect sizes and to show a stronger association between statin use and gastric cancer risk.The findings of this updated meta-analysis suggest that statin use is associated with a reduced risk of gastric cancer. Although the pooled effect size of observational studies showed a possible role of statin therapy in the prevention of gastric cancer, the pooled effect size of the clinical trials and the risk of the bias of observational studies do not encourage physicians to consider statin use to achieve a reduction in gastric cancer. More RCTs with larger populations, longer follow-up, and standardized methods are required to consider statin use as a strategy for reducing gastric cancer.


The prevalence of small for gestational age (SGA) may vary depending on the chosen weight-for-gestational-age reference chart. An individual participant data meta-analysis was conducted to assess the implications of using a local reference (STOPPAM) instead of a universal reference (Intergrowth-21) on the association between malaria in pregnancy and SGA.Individual participant data of 6,236 newborns were pooled from seven conveniently identified studies conducted in Tanzania and Malawi from 2003–2018 with data on malaria in pregnancy, birthweight, and ultrasound estimated gestational age. Mixed-effects regression models were used to compare the association between malaria in pregnancy and SGA when using the STOPPAM and the Intergrowth-21 references, respectively.STOPPAM of 14.2% and SGAIG21 of 18.0%, p < 0.001. The association between malaria in pregnancy and SGA was stronger for STOPPAM (adjusted odds ratio (aOR) 1.30 [1.09–1.56], p < 0.01) than for Intergrowth-21 , particularly among paucigravidae .The 10th percentile for birthweights-for-gestational age was lower for STOPPAM than for Intergrowth-21, leading to a prevalence of SGAThe prevalence of SGA may be overestimated and the impact of malaria in pregnancy underestimated when using Intergrowth-21. Comparing local reference charts to global references when assessing and interpreting the impact of malaria in pregnancy may be appropriate.The online version contains supplementary material available at 10.1186/s12936-022-04307-2. The World Health Organization (WHO) estimated that 11.6 million pregnant women in sub-Saharan Africa were exposed to malaria in 2020 , with thSmall for gestational age is defined as a birthweight below a pre-defined cut-off for a specific sex and gestational age (GA), often the 10th percentile , 7. DecrThe Intergrowth-21 birthweight chart (IG21) is a universally applicable reference developed based on the assumptions that in healthy (low-risk) pregnancies, all fetuses achieve a similar growth potential, irrespective of ethnic or geographical differences, and that maternal and paternal anthropometric characteristics do not influence birthweight . HoweverIn 2011, a local Tanzanian reference chart (STOPPAM) was developed using data from 583 healthy newborns  as a hybIn this individual participant data meta-analysis, the performance of the IG21 was compared to the STOPPAM reference in estimating the association between MIP and SGA.This was a meta-analysis of individual participant data from studies in Tanzania and Malawi. The primary outcome was SGA defined as birthweight < 10th percentile based on IG21 or STOPPAM sex-specific references while the primary exposure was MIP.The study hypothesized that IG21 would overestimate the prevalence of SGA and ultimately weaken the strength of the association between MIP and SGA.A literature search was performed through PubMed, Medline, the Cochrane Library, and EMBASE. The search terms were  AND (SGA OR birthweight OR “birth weight”). In addition, personal communication was made for unpublished studies identified through existing research network. The inclusion criteria were pregnancy-related studies from East and Central Africa with data on GA estimated using ultrasound, birthweight measured within 24 h post-delivery or adjusted if measured > 24 h, newborns’ sex, and MIP.https://www.improve-consortium.org/). Eight authors agreed to collaborate, and seven of them shared the individual participant data  selected potentially relevant studies according to the eligibility criteria after reviewing the abstracts or full texts Fig. . Then, rata Fig. .Fig. 1FlThe meta-analysis included all live-born singleton newborns without congenital malformation, and with birthweight measured within 24 h of birth or birthweights measured > 24 h if the original study teams had already adjusted them , 39, knoThe quality of each study was evaluated by one author (GM) using the Cochrane tool for individually randomized trials  and the Analysis was done using Stata software, version 16 . Continuous variables were described as a mean with standard deviation (SD) or a median with interquartile range (IQR). Categorical variables were summarized as proportions with 95% confidence intervals (CI). The percentiles , GA-specific birthweight z-scores, and the prevalence of SGA were compared for the IG21 and STOPPAM references. In addition, SGA was stratified as low birthweight (LBW < 2.5 kg) and normal birthweight (NBW ≥ 2.5 kg).MIP was defined as any positive test at any point during pregnancy , polymerase chain reaction (PCR), or placental histology). In all analyses, the malaria-negative control group was defined as never having had malaria detected on any test.STOPPAM and SGAIG21, and the results graphically presented as forest plots.A one-stage approach was used to combine the individual participant data using a mixed-effects regression model. The unadjusted and adjusted odds ratios (uOR and aOR) for SGA in relation to MIP were calculated using this model. The overall effect was obtained from the preceding mixed-effects regression and the study-specific effects were obtained by logistic regression. This was done separately for both references, SGAIG21-AGASTOPPAM, (h) only SGASTOPPAM-AGAIG21.The main model compared SGA and MIP. This was further stratified by gravidity (paucigravidae (1st and 2nd pregnancy) vs multigravidae) and the time of infection . In sensitivity analyses, data were restricted to (a) only HIV-negative women-newborn pairs, (b) exclusion of sub-patent infections , past infections , or only positive placental histology , (c) exclusion of studies that only used RDT  or only In addition, the inclusion criteria used in the STOPPAM and IG21 studies were applied to the cohort , 43 and Potential confounders were tested in univariate analysis using a mixed-effects regression model and included GA at enrolment and delivery, gravidity, maternal age, hemoglobin level, mid-upper arm circumference, and body mass index (BMI) at enrolment, utilization of IPTp, treated bed net, and iron plus folic-acid supplements, the number of antenatal visits, and syphilis or HIV-positivity. Variables with p-values < 0.2 in the univariate analysis were included in the multivariate model, and a step-wise backward elimination approach was used to obtain the final model, retaining confounders with a p < 0.1. A p-value < 0.05 was considered statistically significant.2 statistics could not be estimated in the one-stage approach because residual variability is not reported under mixed-effects regression with binary outcomes [2 statistics and to assess the robustness of the analyses.Ioutcomes . Hence, outcomes . FurtherA funnel plot was used to evaluate publication bias. The trim and fill method and contour enhancement funnel plot were used to determine whether the asymmetry in the forest plot was due to a small study effect or factors other than publication bias.The seven studies covered 7,443 newborns Fig. . Of thesAmong the included studies, two were prospective cohorts , 45, andTwo randomized trials were graded as being of good quality; the other three were potentially at high risk of bias  vs. SGAIG21 7.0% (95% CI: 5.0–9.0), p < 0.001). All preterm SGA newborns were also LBW  vs. SGASTOPPAM 14.1% (95% CI: 13.2–15.0), p < 0.001)  vs 18.0% (95% CI: 17.1–19.0)), p < 0.001) (Table The STOPPAM reference was more sensitive than the IG21 reference in detecting an association between MIP and SGA (STOPPAM: uOR 1.54 (95% CI: 1.30–1.82), p < 0.001; aOR 1.30 (1.09–1.56), p = 0.004. IG21: uOR 1.38 (95% CI: 1.18–1.61), p < 0.001; aOR 1.19 (1.00–1.40), p = 0.044)  or only testing symptomatic cases during antenatal visits, newborns with adjusted birthweight, newborns with GA ≤ 38 weeks, and HIV-seropositive. When solely defining malaria as microscopy blood smear positive, the effect of malaria was not statistically significant for neither SGAIG21-AGASTOPPAM (aOR 0.90 (0.67–1.20), p = 0.47), nor SGASTOPPAM-AGAIG21 (aOR 1.02(0.62–1.69), p = 0.93) ; aOR 1.21 (0.99–1.43)) and the IG21 reference (uOR 1.39 (1.14–1.69); aOR 1.12 (0.92–1.31))  nor IG21 reference (p = 0.35). Similarly, the contour-enhanced funnel plot indicated the distribution of studies in both contours with small and large p-values  were SGA same GA , 47, 48.The findings from this meta-analysis support prior studies showing that an international reference may overestimate SGA in a high-risk population with increased exposure to multiple causes of poor fetal growth, including infections like malaria and poor nutrition , 49 whilThe study findings have implications in research settings where the correct diagnosis of SGA is important to accurately estimate the effect of malaria interventions for improving pregnancy outcomes. When SGA is misclassified, particularly in randomized clinical trials using composite endpoints that include SGA, the treatment effect can be weakened, especially when the proportionate reduction of adverse pregnancy outcome is small.The difference in the 10th percentile between the two references is critical. The study revealed a mean difference in the 10th percentiles between STOPPAM and IG21 of 133 g for boys and 123 g for girls at GA 40 + 0 weeks. This may affect a study’s ability to detect an impact on SGA given the relatively small difference in mean birthweight resulting from malaria interventions, such as insecticide-treated nets or IPTp with sulfadoxine-pyrimethamine (+ 2.5 to 3%) , 53.IG21 was 15% and 17% when applying the IG21 [STOPPAM, respectively. This indicates that the study population is more similar to the STOPPAM reference and the higher proportion of SGA when using IG21 is likely an overestimation.It is important to determine which reference is the most representative for the study population. Both the IG21 and the STOPPAM reference were based on low-risk populations. Therefore, the IG21 and STOPPAM criteria were applied to limit the cohort to the healthy/low-risk population, expecting the prevalence of SGA to be close to 10% on a representative reference. However, SGAthe IG21  and STOPthe IG21  criteriaSTOPPAM compared to MIP and SGAIG21 was observed. This supports the use of the STOPPAM reference despite the different methodology compared to IG21.There are differences in the construction of the two references, with the STOPPAM reference being a hybrid chart including fetal weights until GA 38 and IG21 being a pure birthweight chart. A levelling of growth was observed in late pregnancy on the STOPPAM reference. The Hadlock formula was used for estimating fetal weight, which may be slightly overestimated when applied in an African population . This coThe strength of this analysis is the use of a large number of individual participants from a similar geographical area, all with GA estimated by ultrasound. The quality of birthweight was optimized by excluding newborns with unadjusted birthweight measured > 24 h post-delivery, twin deliveries, congenital malformations, and stillbirths. However, there are several limitations. First, the analysed studies used different methodologies for malaria diagnosis, with only one study including placenta histology and some studies using either only one type of malaria test or testing symptomatic cases only. This has a potential for misclassification bias. Except for the analyses on microscopy positivity  of total newborns and thus are unlikely to have led to selection bias. Furthermore, these newborns were not different from included newborns with respect to malaria exposure and the main confounders though there were some differences with respect to maternal age, gravidity, and BMI . The study aim was not to get a precise estimate of the association between MIP and SGA through a systematic review including all possible studies, but rather to investigate the impact of using one reference versus another. Data were not obtained for three eligible studies. Therefore, it can’t be ruled out that this may have influenced the result, given the fewer studies for publication bias assessment.Finally, the analysis conveniently included studies that were part of the IMPROVE Consortium  for randomized trials. Table S3. Risk of Bias assessment by Newcastle scale for cohort studies. Table S4. Prevalence of small for gestational age by gestational age and birthweight. Table S5. Prevalence of small for gestational age when applying the inclusion criteria for each reference chart. Table S6. Sensitivity analysis for the association between malaria in pregnancy and SGA when using STOPPAM vs Intergrowth-21st reference. Table S7. association between malaria and small for gestational age for discordant groups. Table S8. Characteristics of analysed mother-newborn pairs vs excluded.Additional file 2: Figure S1. Birth weight percentiles by sex and gestational age for STOPPAM vs. Intergrowth (IG21) references. The percentiles before and after 33 weeks for Intergrowth were merged, hence the bend in the 10th percentile.Additional file 3: Figure S2. The birth weight z-scores comparing STOPPAM vs. Intergrowth (IG21) references. The dash line indicates the mean birthweight z-scores.Additional file 4: Figure S3. Association between small for gestational age (SGA) and malaria in pregnancy excluding all HIV seropositive women. Panels A and B shows the unadjusted odds ratio (uOR) for SGA when using STOPPAM (SGASTOPPAM) and Intergrowth-21 (SGAIG21) references. Panels C and D shows the adjusted odds ratio (aOR).Additional file 5: Figure S4. Two stage individual participant data meta-analysis on the association between malaria in pregnancy (MIP) and small for gestational age (SGA) using the STOPPAM (SGASTOPPAM) vs. the Intergrowth-21 reference (SGAIG21). uOR: unadjusted odds ratio in panels A and B, aOR: adjusted odds ratio in panels C and D controlling for body mass index, gravidity, gestational age at enrolment, HIV, and hemoglobin level at enrolment. In addition, adjusted for gestational age at delivery for SGAIG21, CI: confidence interval, malaria was defined as positive slide or positive malaria rapid test or positive polymerase chain reaction or positive placenta histology, % Weights are from random effects analysis.Additional file 6: Figure S5. Funnel plots for meta-analysis. The closed dots indicate the observed studies, panel A indicate the trim and fill funnel plot for STOPPAM (P = 0.10) and panel B for Intergrowth-21 reference (P = 0.35). The contour enhanced funnel plot for STOPPAM (panel C) and Intergrowth-21 (panel D) show the distribution of studies in both the small and large p-values contours, hence no publication bias.


Sma-and mad-related protein 7 (SMAD7) can affect tumor progression by closing transforming growth factor-beta intracellular signaling channels. Despite the extensive research on the correlation between SMAD7 polymorphisms and colorectal cancer (CRC), the conclusions of studies are still contradictory. We conducted a study focusing on the association of SMAD7 polymorphisms rs4939827, rs4464148, and rs12953717 with CRC.We searched through 5 databases for articles and used odd ratios (ORs) and 95% confidence intervals (CIs) to discuss the correlation of SMAD7 polymorphisms with CRC risk. The heterogeneity will be appraised by subgroup analysis and meta-regression. Contour-enhanced funnel plot, Begg test and Egger test were utilized to estimate publication bias, and the sensitivity analysis illustrates the reliability of the outcomes. We performed False-positive report probability and trial sequential analysis methods to verify results. We also used public databases for bioinformatics analysis.T allele of rs12953717  and the C allele of rs4464148  can enhance the risk of CRC.We conclusively included 34 studies totaling 173251 subjects in this study. The minor allele (C) of rs4939827 is a protective factor of CRC . the Rs4939827 (T > C) can decrease the susceptibility to CRC. However, the rs4464148 (T > C) and rs12953717 (C > T) variants were connected with an enhanced risk of CRC. Hereditary genomic alterations have been linked to a person’s chance of acquiring cancer for decades. As a result, research into the genetic variables that influence CRC susceptibility is critical. Sma-and mad-related protein 7 (SMAD7), as a member of the SMAD family, may play a damaging role in the transforming growth factor-beta (TGF-β) signaling pathway by interacting with the mobilization of other SMAD proteins, which indirectly contributes to tumorigenesis. As a critical component in the intracellular signaling shutdown mechanism of transforming growth factor (TGF), it can block the tumor-suppressive function of TGF-β at an early stage of carcinogenesis, such as CRC.Colorectal cancer (CRC) is a global disease with a high incidence and death rate, ranking fourth and fifth among all malignancies.β family is strongly associated with development and endocytosis in most tissues. TGF-β family members bind to type II and type I receptors, forming a receptor complex that phosphorylates type I receptors, initiating TGF-β signaling and phosphorylating the made-associated proteins SMAD2 and SMAD3. Later on, phosphorylated SMAD2 and SMAD3 bound to SMAD4 to forge the SMAD4- RSmad complex, which then enters into the nucleus and regulates the transcription of specific target genes with the help of DNA-binding protein chaperones.–6 TGF activation inhibits TGF-mediated phosphorylation of SMAD2 and SMAD3 since SMAD7 may connect to the TGF receptor complex but is not phosphorylated.The TGF- Rs4939827 and rs12953717, as 2 adjacent polymorphisms, do not have the same direction of base mutation. Rs4939827 mutates from base T to base C. In contrast, rs12953717 mutates from base C to base T to affect gene expression. rs4464148 has the same direction of base mutation as rs4939827. This irreversible mutation alters the protein structure at the molecular level and thus affects biological function.All 3 polymorphic variants occur on chromosome 18. rs4939827, rs464148 and rs12953717 are located within intron 3 of SMAD7 on chromosome 18q21.–12 Among them, CRC is the most. However, many studies have conflicting results. Some studies concluded that SMAD7 variants are not significantly associated with CRC.–15 but most of the results indicated the increased risk.–18 The inconsistent results might be attributed to a small sample or chance error. Therefore, we included studies of these 3 variants with CRC, providing a more adequate and accurate study of the correlation between SMAD7 polymorphisms and CRC.Since its discovery, SMAD7 has been widely researched, especially to study its single nucleotide polymorphisms with cancer because of its possible signaling inhibition in the cell nucleus. We found that rs4939827, rs4464148, and rs12953717 polymorphisms were studied more in association with various cancer, which contains colorectal, breast, hepatocellular carcinoma, esophageal, chronic lymphocytic leukemia.https://www.crd.york.ac.uk/PROSPERO/. Since we are not engaged in human or animal experiments, we do not have to submit an ethical application. Our study was closely carried out according to the PRISMA guidelines.Our research has been registered in PROSPERO and the details are available at http://links.lww.com/MD/I297, which shows detailed search strategies). We also reviewed articles about our study by the references cited in the included studies; if feasible, gray literature searched via manual was also included. Two researchers independently searched through the above search strategy and deliberated on inconsistent search results. If necessary, we need a third researcher join us until reaching a consensus. There were no language constraints in this search.Studies included in this meta-analysis that met the inclusion criteria were obtained from 5 databases , with a search time limit of literature published earlier than January 2022. The search strategy incorporated these terms: “Neoplasm,” “tumor,” “cancer,” “malignancy,” “colorectal cancer,” “CRC,” “SNP,” “Polymorphism,” “mutation,” “SMAD7,” “SMAD7 protein,” “rs4939827,” “rs4464148,” “rs12953717,” “case–control study”; the specific search formula can be viewed in the supporting information Case–control studies.(b)evaluating the correlation between SMAD7 loci  and CRC risk, participants in the case group must have malignancy confirmed by pathological methods.(c)Full text, acquired genotype frequencies existed in both the case and control groups.Duplicate literature.Non-human experiments. In multiple studies with overlapping, duplicate data published, only the most recent or intact study was included.χ2 test, and P > .05 was consistent with HWE. We will exclude trials that do not conform to HWE.The 2 researchers respectively derived some contents from available pieces of literature: first author, country region, year of publication, ethnicity, source of the control group, cancer type, and genotype frequency of case and control groups, genotyping method. The 2 researchers cross-checked the extraction data to avoid any discrepancies. Genotype frequencies in the control group must follow Hardy-Weinberg equilibrium (HWE). HWE for each study was measured by http://links.lww.com/MD/I298, which show the results of literature quality evaluation). In case of differences between the 2 investigators, it was necessary to discuss with a third party until the 3 parties reached an acceptable resolution.Two investigators assessed the value of included studies under the Newcastle-Ottawa scale, a total score of 9 points. Case–control trials were scored in 3 dimensions: selection, comparability, and exposure. Scores of 5 to 9 were categorized as high quality versus scores of 0 to 4, which were considered low quality , trial sequential analysis (TSA) 0.9.5.10 Beta.software: Stata 15.1 (The pooled odd ratios (ORs) and 95% confidence interval (CIs) were taken to evaluate the relationship between the 3 polymorphisms and CRC in dominant, recessive, homozygous, heterozygous and additive models. We compared the relationship between the value of OR and 1.0 and whether the value 1.0 is in the 95% CI. If the 95% CI contains the value 1.0, then the results will be deemed insignificant.Q test and I-square to assess the level of primary studies’ heterogeneity. a P-value of less than 0.1 or an I-square greater than 50% for the Cochran Q test was defined as significant heterogeneity. Fixed-effects models were adopted to pooled ORs to estimate the relationship between respective models and CRC risk in case of insignificant heterogeneity; otherwise, random-effects models were adopted. We performed a Meta-regression analysis to probe the root of heterogeneity. We conducted subgroup analyses of included studies for ethnicity, sample, and source of control group to further probe the sources of heterogeneity.We used Cochran P-value of the Begg test and Egger test was less than .05.We employed contour-enhanced funnel plots, Begg test, and Egger test to evaluate the risk of publication bias. The publication bias existed if the funnel plot was asymmetric in the white region or the Since we included more than 10 studies in each polymorphism, the reliability of the results for single nucleotide polymorphisms could be assessed by the leave-1-out method. We sequentially excluded a case–control study, and the leftover studies were subjected to sensitivity analysis to examine whether there was a discrepancy between the results of the excluded options and the primitive overall result. Some studies may be considered for exclusion if the study statistics compromise the reliability of the results.P-value is less than .2. In addition, we also performed the test sequential analysis strictly according to the TSA user manual and using the latest software . All of them are available at www.ctu.dk/tsa. We set the probability of a type 1 error to 0.05, a power of 80%, and a conventional bound of 1.96 (Z = 1.96). The allele models for the 3 polymorphisms were analyzed, and we will consider the inclusion of sample size sufficient when the cumulative Z value crosses the monitor boundary or when the sample size is greater than the required information size.We employed the false-positive report probability (FPRP) method for statistical indicators of positivity, which detects the occurrence probability of type 1 errors caused by cumulative meta-analysis. We set the threshold for FPRP at 0.2, calculated statistical power at an odd ratio of 1.5, and allocated a prior probability of 0.1. Results will be considered significant if the FPRP calculated by statistical power, prior probability, and the https://cn.string-db.org/) to analyze SMAD7 concerning its human protein interactions, with data derived from high-throughput experimental data, computer genome prediction, and automated text mining data. In addition, it can also visualize the data into an intelligible gene co-expression network.We use an open-source data site STRING (https://david.ncifcrf.gov/) is a bioinformatics database that integrates biological data and analytical tools to provide systematic and comprehensive biofunctional annotation information for the large-scale gene or protein lists. We obtained functional annotation information of SMAD7 co-expressed proteins from it and visualized the data in the bioinformatics platform (https://www.bioinformatics.com.cn/). A false discovery rate less than 0.05 was statistically significant.The DAVID database , a totally of 62 case–control studies were subsequently incorporated, 37 of which focused specifically on the connection between the rs4939827 and the chance of CRC,P < .05), and the results were more convincing after removing studies that did not comply with HWE than those that did not; therefore, we excluded the data of these studies. Quality among studies was evaluated via The Newcastle-Ottawa scale; studies all scored more significant than 6, indicating that the contained studies in this article were of high quality.As shown in Table Table C allele of rs4939827  can reduced the overall CRC risk . All these 5 types of models were analyzed using random effects model because of the significant heterogeneity  compared to the small sample subgroup.C to T can increase CRC risk in Caucasian populations  but have no impact on Asian races. For control group source subgroup analysis, In the unknown origin group, it also revealed a relationship among rs4464148 and CRC , The correlation between the snp and CRC was also suggested in the population-based group . And the large sample group also suggested a remarkable connection between this gene and CRC , all outcomes of subgroup are shown in Table In this part, random effect model was utilized for the dominant and heterozygous model and fixed-effect models for the recessive, homozygous and additive model, and then the results significantly indicated that rs4464148  increased the CRC risk , for the control source subgroup analysis, we found that unknown source group are related to CRC. The same results can also be derived from the sample subgroup analysis that rs12953717 was regarded as important contributing factors in LARGE group , while no statistical meaningfulness was found in the SMALL group.As for this snp, After collecting and processing the data, we can drag a conclusion that rs12953717  polymorphism increased risk of CRC , for which we employed random effects model to pool ORs and perform subgroup analysis, this model is also used in dominant  and heterozygous model  of rs4464148 and rs12953717 for dominant , homozygous , heterozygous  and additive models , Instead, due to low heterogeneity, we applied fixed-effects models to subgroup analyses of the recessive , homozygous  and additive models  in rs4464148 and the recessive model  in rs12953717. Since the number of studies on these 3 polymorphisms belonging to SMAD7 exceeded 10, we used meta-regression to probe the root of their heterogeneity, then we found that the heterogeneity of rs12953717 was mainly derived from ethnicity . Although we did not identify any significant sources of heterogeneity in the meta-regressions about rs4939827 and rs4464148, the overall high heterogeneity should not be ignored, so subsequently subgroup analysis by ethnicity, control group source and sample can reveal that the heterogeneity of rs4464148 polymorphism mainly originates from the Caucasian group and hospital-based group of control group source, all subgroups of rs4939827 showed highly heterogeneous.In data integration and analysis, we found that rs4939827 was highly heterogeneous  for these 3 gene polymorphisms, suggesting that the asymmetry in the funnel plot is caused by factors other than publication bias and most likely is caused by heterogeneity.The publication bias of the 5 models of rs4939827, rs4464148, and rs12953717 was evaluated separately using contour-enhanced funnel plots . It suggests that this study had a distinctive effect on the results, making the results destabilizing Fig. .Z curves for all 3 polymorphisms crossed the boundary curves, with cumulative Z values exceeding 1.96 (a = 0.05), and that the sample size exceeded the required information size. These results represent that our included sample size fulfills the sample size we need to draw factual conclusions, proving the reliability of our conclusions.The results of the false-positive report probability analysis are depicted in Table We imaged the SMAD7 gene co-expression network based on the STRING database Fig. A, which P-value, the smaller the P-value, the closer to red  and had problems with the calculation of the HWE, leading to the inclusion of some case–control studies that did not conform to the HWE. In addition, that article did not conduct meta-regression analysis and subgroup analysis to explore the sources of heterogeneity further. Our researchers were fully aware of these shortcomings. The present meta-analysis included as many articles that met the criteria as possible while excluding case–control studies that did not conform to the HWE, which can be said to be the most relevant study with the highest number of cases so far and included 5 more case–control studies than the previous 1 to increase the accuracy of the results. We also reduced selection bias and improved the accuracy of results by searching in Chinese databases and adding gray literature.A meta-analysis was written by Huang et al in 2016 also came to the non-contradictory conclusion,,51 The asymmetry of contour-enhanced funnel plots for the dominant, recessive, homozygous, heterozygous, and additive models may be associated with heterogeneity, and other results of Begg and Egger test did not find publication bias. For sensitivity analysis, we excluded each of the included studies 1 by 1 before combining effect sizes, and compared the new combined results with the results before the exclusion, and found no significant differences between the results of rs4464148 and rs4939827, which indicates that the results of the analysis of rs4464148 and rs4939827 in this article are robust and credible. In rs12953717, we found that the results changed after removing the Caucasian group of studies in the Kupfer et al study, which suggests that the results of the analysis with the removal of this study would be more credible.Moreover, we found that all of the 3 polymorphisms had heterogeneity in this analysis, so we employed a meta-regression analysis with subgroup analysis by ethnicity, control group source, and sample to find the specific sources of heterogeneity. We found that the heterogeneity of rs12953717 and rs4464148 was principally derived from ethnicity. We further discovered that heterogeneity existed mainly in studies on Caucasian populations; the reasons may be related to the socio-economic situation, food habits, and the wide distribution of ethnic groups, the source of heterogeneity of rs4939827 may be multifaceted, such as the genotyping method of case–control studies, the source of subject recruitment, environmental factors, and dietary habits.β1 signaling in specific pathogenic environments as an important direction for future research; this may pave the way for the development of strategies to modulate these disease processes to develop the most effective therapy plan better for CRC patients.It is worth noting that this meta-analysis also has inadequacies. For instance, we have only 1 study on the African population, and more studies may be needed in the future. The tumor we studied were also constrained to CRC; more research is needed in the future to explore the correlation between SMAD7 polymorphisms and cancer susceptibility further. Although smad7 has been extensively probed, the molecular mechanism of SMAD7 is not fully defined, so it cannot serve the clinic better. We also detected many co-expressed genes through bioinformatic analysis. We can further investigate the role of intracellular signaling pathways and gene co-expression, regarding the elucidation of the role of TGF-To sum up the above, our study is very relevant. The results of our meta-analysis certified the noticeable relationship of the rs4939827 (T > C) variant with reduced CRC risk. However, the rs4464148 (T > C) and rs12953717 (C > T) variants were significantly correlated with an increased risk of CRC.This study was supported by grants from the General Science and Technology Program of the Health Commission of Jiangxi Province (202210415).Conceptualization: Qiang Xiao, Guomin Zhu.Data curation: Jian Chen, Shukun Zeng.Formal analysis: Qiang Xiao, Jian Chen, Hu Cai.Funding acquisition: Guomin Zhu.Resources: Qiang Xiao, Shukun Zeng, Hu Cai.Software: Jian Chen.Visualization: Qiang Xiao.Writing – original draft: Qiang Xiao, Shukun Zeng.Writing – review & editing: Jian Chen, Jia Zhu, Hu Cai.


Through synthesizing studies regarding neurobehavioral impairment of pediatric brain tumor survivors (PBTS) in the past decade, this meta-analysis found that PBTS are at higher risk of attention problems, emotional difficulties and psychosocial problems compared to the healthy population. Future studies should focus on exploring potential interventions for PBTS at risk of neurobehavioral impairment to improve the long-term psychological outcomes.Purpose: The neurocognitive outcomes of pediatric brain tumor survivors have been extensively studied but the risk and predictors for neurobehavioral impairment are less clearly defined. We systematically analyzed the rates of emotional, psychosocial, and attention problems in pediatric brain tumor survivors. Methods: PubMed, Web of Science, Embase, Scopus, and Cochrane were searched for articles published between January 2012 to April 2022. Eligible studies reported neurobehavioral outcomes for PBTS aged 2 to <23 years with a brain tumor diagnosis before 18 years of age. A random-effect meta-analysis was performed in R. Results: The search yielded 1187 unique publications, of which 50 were included in the quantitative analysis. The estimated risk of having emotional, psychosocial, and attention problems were 15% (95%CI 10–20%), 12% (95%CI 9–16%), and 12% (95%CI 9–16%), respectively. PBTS were more likely to have emotional difficulties (Hedge’s g = 0.43 [95%CI 0.34–0.52]), psychosocial problems (Hedge’s g = 0.46 [95%CI 0.33–0.58]), and attention problems (Hedge’s g = 0.48 [95%CI 0.34–0.63]) compared to normal/healthy control subjects. There was no significant difference in the rates of neurobehavioral impairment between children with and without history of cranial radiotherapy. Conclusions: PBTS are at elevated risk of neurobehavioral impairment. Neurobehavioral monitoring should be considered as the standard of care for PBTS. Brain tumors are the most common solid tumors affecting children and adolescents, accounting for approximately 27% of pediatric cancers and affecting approximately 3000 children per year in the United States . The proNeurobehavioral disorders are very common in children and adolescents, affecting 4.4–9.8% of the general pediatric population . HoweverGiven the increased survival in PBTS, there needs to be more efforts to understand and improve the long-term outcomes , particuThis meta-analysis was conducted to examine the risk of emotional, psychosocial, and attention problems in PBTS by focusing on studies in the past decade. The study also aimed to identify the risk factors pre-disposing PBTS to poorer neurobehavioral outcomes.We searched PubMed, Scopus Embase, Web of Science, and Cochrane in April 2022 for articles published from 1 January 2012 to 20 April 2022. The following string was used to search the databases [“CNS tumor” OR “brain tumor” OR “brain Oncology” or neuro-oncology OR medulloblastomas OR “pilocytic astrocytoma” OR craniopharyngiomas OR “germ cell tumors” OR glioma OR ependymal OR glioneuronal OR embryonal in Title Abstract Keyword] AND [children OR pediatric OR adolescent OR toddler OR preschool OR teen OR teenager OR childhood in Title Abstract Keyword] AND [“social difficulties” OR “social outcome” OR “social problems” OR “social deficits” OR “emotional difficulties” OR “emotional problems” OR “attention deficits” OR “attention problems” OR ADHD OR “attention deficit hyperactivity disorder” OR “autism spectrum disorder” OR autism OR “developmental outcomes” OR “behavioral difficulties” OR neurobehavior OR neuropsychological OR psychiatric OR psychosocial OR depression OR anxiety OR internalizing OR externalizing in Title Abstract Keyword]. Word variations were also searched. References from the identified studies and relevant reviews were also retrieved and searched. See Assessed articles are screened by two independent reviewers according to the following inclusion and exclusion criteria:The inclusion criteria were as follows: (1) participants diagnosed with brain tumor before the age of 18 years; (2) assessed participants between the age of two and 23; (3) assessed at least one of the three aspects of neurobehavioral impairment by validated standard scales: (a) autistic features/psychosocial problems/psychosocial outcomes; (b) emotional problems/internalizing problem/externalizing problem; (c) attention deficits/attention problems; (4) reported original research data; and (5) studies published in English.The exclusion criteria were as follows: (1) case study, conference abstract and papers; (2) no validated standard scales measuring neurobehavioral impairment; (3) norm/clinical cut-off or healthy control scores were not provided for the scale; (4) data not retrievable for calculating either the absolute risk or the standard mean difference  of the psychosocial/emotion/attention problems in PBT participants; (5) researched on paediatric cancer survivor cohort while CNS paediatric cancer survivor’s data are not provided separately; (6) assessed overall psychological/neurobehavioral impairment while psychosocial/emotion/attention scores are not provided separately.Titles and abstracts of assessed papers were first screened by the two reviewers (YW and WWYT) for potentially eligible studies. Those identified studies were then reviewed in full text. In each step, disagreement was solved through consensus by the two reviewers. The inter-rater reliability is calculated in the inclusion process.Data  required to calculate the standard mean difference and absolute risk for neurobehavioral impairments in PBTS were retrieved from each study. The assessment results at baseline and at all follow-up time points were also retrieved from the studies. For studies containing more than one independent cohort, the data of these cohorts were recorded separately. For studies reporting more than one measurement in one aspect of the neurobehavioral impairment , the pooled standard mean difference was calculated . The ris2 statistics, with I2 ≥ 50% indicating substantial heterogeneity; and the significance of heterogeneity was examined by an χ2 test. For pooling the absolute risk and standard mean differences, self-reported data was used for children aged 12 and above, whereas parent-reported data was used for children below the age of 12. Subgroup analysis was conducted to examine categorical moderating factors, including reporting methods , comparison groups , and treatments (with or without a history of radio therapy). Peters’ Regression Test [p-value < 0.05 was considered to be statistically significant. All analyses were conducted in R 4.1.1 using the ‘meta’ and ‘esc’ packages [A meta-analysis was conducted to synthesize the findings on the risk of neurobehavioral problems in PBTS in the following two aspects: (1) the absolute risk: the proportion of PBTS who were below the clinical cut-offs for psychosocial, emotional, and attention problems from each identified study; and (2) the standard mean difference: the psychosocial, emotional, and attention problems in PBTS compared to the population norm and healthy controls. A random-effect model was used to pool the results from the different studies. The standard mean difference was measured by Hedge’s g. The heterogeneity across studies was evaluated by Iion Test  and Eggeion Test  were usepackages .This meta-analysis follows the PRISMA guidelines  and is rThe database searches yielded 3360 results, of which 1387 unique publications were further reviewed, and 50 studies were included in the final meta-analysis see . The Cohn = 1251)  and no significant publication bias was identified t (15) = 0.36, p = 0.72, The proportion of PBTS whose attention problems were below the clinical cut-off was reported in 14 studies ( = 1251) a. The pon = 1257) . No significant publication bias was observed t (22) = −0.47, p = 0.646  b. The po = 0.646 .n = 1699) (p < 0.01). Publication bias was not significant t (20) = 0.12, p = 0.908  c. The po = 0.908 . 2 = 67%, p < 0.01). The publication bias was not significant, as revealed by Egger’s test t (18) = 0.92, p = 0.369 . Notably, there was insignificant heterogeneity in the comparison with healthy controls (I2 = 31%), whereas the heterogeneity remained high in the subgroup that was compared with the population norm (I2 = 69%). No significant publication bias was observed, t (29) = −0.16, p = 0.877 . No significant publication bias was identified t (31) = 0.35, p = 0.730 , The included studies were separated into subgroups according to the reporting method . No significant differences were observed for attention problems and emotional difficulties regarding both their absolute risk and standard mean difference . For psyTen studies exclusively reported PBTS with a history of RT (RT-only) and three studies exclusively reported PBTS without a history of RT (no-RT). Thirty-seven studies reported a heterogenous sample including participants that both underwent RT and those that did not (mix-RT). p > 0.3 in all regression models). A trend was identified whereby the follow-up time was associated with the standard mean difference , although it did not reach the significant level.A meta-regression was conducted with the standard mean difference and absolute risk as the criteria, and age at assessment, age at diagnosis, and follow-up time as the predictors, respectively. Three different aspects of neurobehavioral impairment  were pooled together to increase the standard mean difference. Age at assessment and age at diagnosis were not significant predictors of either absolute risk or standard mean difference of neurobehavioral impairment in PBTS (n < 30) and/or were rated as having a ‘high’ risk of bias. The result revealed that there was no significant difference compared to the main analysis, see A sensitivity analysis was conducted through excluding studies with small sample size (As the survival of children with brain tumors has improved with advancements in cancer treatment, it becomes essential for healthcare professionals and childcare workers to have a better understanding of the long-term neurobehavioral sequelae of PBTS. This meta-analysis is one of the first to synthesize the recent evidence on the prevalence of neurobehavioral impairment in PBTS. The analysis showed that PBTS have a higher risk of neurobehavioral impairments compared to healthy subjects or the population norm. 18.9% and 15% of PBTS were found to have emotional difficulties and attention problems, respectively, when compared to a rate of 5.1% and 4.4% of the pediatric population with emotional problems and symptoms of inattention/hyperactivity according to a recent U.S. National Health Interview Survey .14.4% ofDespite the well-reported detrimental effects of cranial radiotherapy on cognition and memory in PBTS, our study did not find significant differences in the rates of neurobehavioral impairments between children with or without cranial radiotherapy treatment, although these inconsistent findings might be related to the small sample sizes and high heterogeneity among studies. The impact of radiotherapy could vary due to irradiation dosage , tumor lFor the long-term monitoring of neurobehavioral function in PBTS, the screening of attention problems and emotional difficulties could be achieved using self-reported and/or parent/proxy-reported questionnaires , as our In order to monitor the trajectory of neurobehavioral problems among PBTS, we propose that all children newly diagnosed with brain tumors should have comprehensive neurocognitive and behavioral evaluation by healthcare professionals. The initial assessment should include diagnostic interviews conducted by healthcare professionals as well as using parent and self-report questionnaires. All PBTS should have regular monitoring for neurobehavioral impairment using parent and self-report questionnaires . For parThis study had several limitations that need to be considered. There was significant heterogeneity among the included studies due to variations in patient characteristics and types of treatments across studies. High heterogeneity was also reported by Schulte et al., 2019  in a sysIn conclusion, neurobehavioral impairments, including emotional, psychosocial, and attention problems, are more common in PBTS. Survivor-reported or proxy-reported questionnaires might serve as good screening tools for PBTS at risk of neurobehavioral problems. Survivorship programs should offer long-term monitoring of neurobehavioral function in PBTS. Future studies should focus on exploring potential interventions for PBTS at risk of neurobehavioral impairment.


Currently, there is limited information about the relationship between manganese superoxide dismutase (sod2) c47t polymorphism and susceptibility to noise-induced hearing loss (NIHL).The aim of this meta-analysis was to clarify the association between SOD2 C47T polymorphism and NIHL.A search in PubMed and Web of Science was performed to collect data. All full-text, English-written studies containing sufficient and complete case-and-control data about the relationship between SOD2 C47T polymorphism and NIHL were included. Three eligible studies, comprising 1094 subjects, were identified. pooled odds ratios (ORs) and 95% confidence intervals (CI) were calculated to evaluate the strength of the association between SOD2 C47T polymorphism and NIHL.vs. C ; TT vs. CC ; CT vs. CC ; TT vs. CC + CT ; CC vs. TT + TC . However, in subgroup analysis, a significant association was found for TT vs. CC + CT  in the Chinese population.No significant association between C47T polymorphism and risk of NIHL was found with the following combinations: T The present meta-analysis suggests that SOD2 C47T polymorphism is significantly associated with increased risk of NIHL in the Chinese population. Further large and well-designed studies are needed to confirm this association. Noise-induced hearing loss (NIHL), one of the most common occupational diseases, is a form of sensorineural hearing impairment caused by the interaction between environmental factors (such as prolonged exposure to high levels of noise) and genetic factors.Currently, little is known about gene polymorphisms that may be involved in the susceptibility to NIHL. Ohlemiller et al.SOD2 is a homotetramer located within the mitochondrion and is an enzyme involved in the conversion of superoxide radicals to hydrogen peroxide.p-value of more than 0.05 was observed, the control group genotypes were consistent with HWE.Articles investigating SOD2 and NIHL that were published in PubMed and Web of Science before December 2014 were included in this meta-analysis. The following search terms were used: superoxide dismutase, SOD2, polymorphism, polymorphisms, variation, variations, genotype, noise induced hearing loss, noise-induced hearing loss, and NIHL. Studies that met the following criteria were included: (1) full-text, English-written studies; (2) complete case-and-control data about the relationship between SOD2 polymorphism and NIHL; (3) sufficient data to infer the results; and (4) control group genotypes in Hardy–Weinberg Equilibrium (HWE). HWE was tested by the chi-squared test, and when a In this study, two investigators independently collected data from each eligible article. The data comprised first author, year of the publication, origin country, ethnicity, number of cases, and number of controls. Through checking between the two investigators, a final set of data was determined.Study quality was evaluated by the Newcastle-Ottawa Quality Assessment Scale for case–control studies,vs. C), a co-dominant model (TT vs. CC and CT vs. CC), a dominant model (TT + CT vs. CC), and a recessive model (TT vs. CT + CC).The association between C47T polymorphism in SOD2 gene and NIHL susceptibility was estimated under all genetic models. Five comparison models for C47T polymorphism were evaluated: an allele model  and 95% confidence intervals (CIs) were calculated using a fixed effects model or random effects model. The chosen model was based on the results of a heterogeneity test, which employed a previously described, p-value lower than 0.05, a publication bias likely existed.Publication bias was tested using Begg's funnel plot and Egger's test.All of analyses were performed using Stata version 12.0 software .The final search, which took place on December 31, 2014, resulted in the retrieval of 33 articles. The majority of the articles were excluded due to the fact that the study was about an unrelated topic, the articles were not in English, or the article was a duplicate, review, or commentary article, resulting in a total of four included articles. After a study which was a meeting abstract was omitted, three articles remained. Thus, three articles were finally includedThe NOS for assessing the quality of case–control studies was shown in vs. C, OR = 0.83, 95% CI = 0.63–1.09; dominant model: CC vs. TT + TC, OR = 0.49, 95% CI = 0.23–1.04; co-dominant model: TT vs. CC, OR = 0.49, 95% CI = 0.22–1.09; CT vs. CC, OR = 0.54, 95% CI = 0.25–1.17; recessive model: TT vs. CC + CT, OR = 0.82, 95% CI = 0.50–1.32; vs. CC + CT, OR = 0.77, 95% CI = 0.42–1.41) in Chinese subjects , dominant model , co-dominant model , or recessive model .The results of Begg's funnel plot  and EggeReactive oxygen species (ROS) play a key role in the underlying mechanisms of cochlear damage induction under various pathological conditions. Superoxide, which can form the highly toxic peroxynitrite, is readily generated in the inner ear following acoustic overstimulation.vs. CC + CT, OR = 0.77, 95% CI = 0.42–1.41) in the Chinese population. There was no significant association in any other genetic models in the Chinese population. To the best of the author's knowledge, this was the first meta-analysis investigating the association between the SOD2 C47T polymorphism and NIHL susceptibility.The present study analyzed the data from three studies that included a total of 407 NIHL cases and 687 controls. No significant associations between C47T polymorphism and NIHL were observed in all models. However, when subgroup analysis based on ethnicity was performed, a significant association was observed between the SOD2 C47T polymorphism and NIHL in a recessive model (TT Moreover, fixed-effects or random-effects models were used in the analysis of the studies based on heterogeneity testing. Two study exhibits a substantial heterogeneity for the overall analysis. However, according to subgroup analysis based on ethnicity, no significant heterogeneity was observed. Therefore, further exploration of the risk factors for this condition is needed.The present study has some limitations. For instance, the sample size used in this meta-analysis was insufficient, especially for the subgroup analysis based on ethnicity. Moreover, there was a lack of case–control data adjustment according to detailed individual information, such as age, sex, and lifestyle. The third limitation is that the exact molecular basis of the association between SOD2 C47T polymorphism and NIHL risk is still not clear at present and requires further investigation.Despite these limitations, the present meta-analysis suggested that SOD2 C47T polymorphism is significantly associated with an increased risk of NIHL in the Chinese population. Nevertheless, additional, larger and well-designed studies are needed to confirm this association.The authors declare no conflicts of interest.