Vitamin D deficiency is a well-described preventable cause of many cancers; the association of vitamin D use with the development of head and neck cancer (HNC) is not clear. We aim to conduct a systematic review of the studies assessing the relation between vitamin D exposure and the prevention and prognosis of the HNC using meta-analysis.PubMed, EMBASE, Cochrane Library, Web of Science up to 1 January 2021, and reference lists of related studies were searched. We extracted observational studies reporting the association between vitamin D  and the outcomes of interest  in HNC patients aged 18 or older. Fixed effects models were used to calculate pooled effect sizes and 95% confidence intervals (CIs) by RevMan (version 5.3).Ff + FF or FF, the pooled odds ratio (OR) of participants with the genotype of ff was 0.77 (95% CI: 0.61 to 0.97) and 0.75 (0.58 to 0.97), respectively. A similar trend was noted when comparing tt with Tt + TT or TT, in which OR (95% CI) was 0.70 (0.55 to 0.90) and 0.72 (0.55 to 0.95). No significant association was identified between BsmI polymorphism and HNC. Furthermore, the OR of HNC incidence was 0.77 (0.65 to 0.92) for participants with vitamin D intake over the ones with a regular diet. High concentrations of circulated 25-hydroxyvitamin D (25-OHD) significantly decreased by 32% of HNC incidence (OR (95% CI): 0.68 (0.59 to 0.78)) and increased HNC survival  during a 4–5 years follow-up. High concentrations of circulating 25-OHD in patients with HNC led to a decreased risk of mortality to 0.75 (0.60 to 0.94) as the follow-up extends to 8–12 years.Sixteen studies with a total of 81,908 participants were enrolled in our meta-analysis. Based on the pooled genomic analysis, comparing with participants with the genotypes of Elevated activities of vitamin D by diet intake, genomic polymorphisms, or circulated 25-OHD may protect people from HNC and improve the prognosis of patients with HNC.https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=176002).PROSPERO, identifier CRD42020176002 ( Head and neck cancer (HNC) is the sixth most common cancer, with approximately >700,000 new cancer cases and 350,000 deaths worldwide annually; more than 90% of HNC are squamous epithelial cell carcinomas arising from the oral cavity, larynx, oropharynx, and hypopharynx –4. Cigar2D; 1,25(OH)2D is the main active form of vitamin D in circulation; its classic functions involves calcium transport and regulation of genomic transcriptions. 1,25(OH)2D binds to the vitamin D receptor (VDR) and then modulates the expression of numerous target genes, therefore, participates in the regulation of diverse cell behaviors including cell differentiation, proliferation, angiogenesis, metastasis, and immunity , located in the transcriptional initiation site of VDR gene, leads to the formation of a protein isoform and plays a vital role in the post-transcriptional modification (BsmI (rs1544410) and TaqI (rs731236) SNPs, located near the 3′ end of the VDR gene, do not change the amino acid sequence of the encoded protein but determines protein level via regulating the stability of VDR mRNA  and 1,25(OH)immunity . The singression , 17. It fication . BsmI  with the International Prospective Register of Systematic Reviews (PROSPERO). We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to design, analyze, and report our meta-analytic findings . We alsoVDR gene polymorphisms; 3) incidence, mortality, or survival data for patients with HNC were clear-defined; 4) the odds ratio (OR), relative risk (RR), and hazard ratio (HR) estimate with 95% confidence intervals (CIs)  of interest outcomes were also reported.Available studies including case–control, retrospective, and prospective cohorts were enrolled in our analysis once the following inclusion criteria were satisfied: 1) enrolled a clinical and histological diagnosis of adults (aged 18 or older) with HNC (including corresponding control groups); 2) information regarding vitamin D exposures was provided, such as dietary intake, additional supplements of vitamin D, 25-OHD, and We excluded studies based on the following rules: 1) Ecologic studies, case reports, case series, reviews, editorials, letters, conference papers, and articles available in an abstract form (where the authors could not be contacted); 2) Published in non-English; 3) Studies with insufficient information for data extraction.We conducted a systematic review of articles published before March 2020 from four databases, including PubMed, EMBASE, Web of Science, and Cochrane library. Moreover, ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform were searched to identify the ongoing or unpublished eligible trials. Medical Subject Headings (MeSH) including “Head and Neck Neoplasms” and “Vitamin D” was used to choose qualified studies, which was also combined with the keyword in headers and abstracts. Besides, manual searches of references cited in all selected studies and published reviews were also performed to identify additional relevant studies comprehensively. To assess the associations between vitamin D exposures and the outcomes of interest, we did not limit the publication date in our initial search strategy. We updated searches to 1 January 2021. Details of our search strategy were provided in Two investigators independently performed the initial screening of potentially eligible records. After the removal of the duplicates, studies with irrelevant titles or abstracts were also excluded. Consequently, full-text screening was performed in the remained eligible reports. All disagreements were resolved by consensus. Baseline characteristics and outcomes were extracted independently from the selected articles by two investigators and cross-checked to reach an agreement. The following information was recorded in detail: the last name of the first author, publication year, the country where the study was performed, study design, sex, age at baseline, study period, measure and range of exposure, sample size (cases and controls or cohort size), description of essential baseline confounders, primary cancer location, and outcomes of interest. Articles were categorized based on the results of interest: primary outcome (HNC incidence), secondary outcome . Articles reporting on multiple developments were included. If necessary, the primary authors were contacted to retrieve additional information.The quality of each study was independently assessed by two investigators using the Newcastle–Ottawa Scale, in which a star system was applied (with a maximum of nine stars) to evaluate a study in three domains: the selection of participants, comparability of study groups, and exposure. Finally, studies with a score of nine stars were at low risk of bias, studies with seven or eight stars were at medium risk, and those that scored six or less were at high risk of bias.VDR gene polymorphisms , concentrations of 25-OHD, vitamin D intake and HNC. Effect sizes  and 95% CIs were calculated to evaluate the associations between vitamin D exposures and HNC events. If available, multivariate models were given a priority for the accurate estimate for the effects of vitamin D. Comparison of the bottom versus the top of the baseline distribution of vitamin D exposure levels was selected in each study (the lowest exposure level as reference). If the highest exposure category was used as a reference in the original research, the effect size would be inverted or recalculated. If HRs and CIs were not available, Engauge Digitizer 10.9 was used to derive estimates from survival curves. The standard error of the natural logarithm (ln) of the effect sizes was calculated from the 95% CIs using the following formula: ln [upper limit of CI] − ln [lower limit of CI])/3.92. We assumed HR and OR to approximate the same measure of RR. When the incidence was low, HR, OR, and RR were like each other. If the effect sizes of subgroups were reported separately, different subgroups could be regarded as independent studies. If 25-OHD levels were quantified in ng/ml or vitamin D intake in ng/d, the values were uniformly converted into nmol/L or IU/d. The association between the three VDR SNPs and HNC risk was assessed under five genetic models: the allele model, the homozygous model, the heterozygous model, the recessive model, and the dominant model.We assessed the strength of associations between the P <0.05 was considered statistically significant. The Hardy–Weinberg equilibrium (HWE) in controls was tested using the goodness-of-fit χ2 statistic with one degree of freedom. Statistical heterogeneity among studies was evaluated with Q and 2I statistics. If Q-test reported a P-value <0.1 or 2I >50%, it would be defined as significant heterogeneity, which means the random effects model would be applied to pool the results. Otherwise, the fixed effects model would be applied. Subgroup analyses were performed based on geographic region, quality, cancer subsites, participant numbers, and study design of included studies to avoid the potential bias influence. Sensitivity analyses were performed by excluding each study or the studies with low quality to evaluate the stability of results. Where possible, we evaluated publication bias by plotting a funnel plot; publication bias was determined by the funnel plot with an asymmetrical shape  in selected studies. Radioimmunoassay, automated immunoassay, and chromatographic methods were used to detect the concentrations of 25-hydroxyvitamin D. All studies of vitamin D intake were investigated on food frequency questionnaires. Of these participants, 5272 HNC patients were enrolled, including 1,064 VDR gene polymorphism and the risk of HNC, all of which were case-control studies. Two studies focused on Asians, and the other two studies focused on Caucasians. The following four VDR SNPs were studied: TaqI , FokI , and BsmI . Three studies on FokI polymorphism included 1,000 patients and 1,119 controls, three studies on TaqI polymorphism included 893 patients and 1,030 controls, and two studies on BsmI polymorphism included 281 patients and 298 controls. Within the distribution of genotypes in the control groups, only 1 study deviated from HWE in the BsmI variant (P < 0.05). A total of four publications reported the association between VDR gene polymorphism except for FokI gene polymorphism. Eight articles had a low risk of bias (nine stars); the remaining eight articles had a moderate risk of bias (seven to eight stars). Newcastle-Ottawa Scale evaluated the selection of participants , comparability of study groups , and exposure . VDR gene polymorphism, five on circulating 25-OHD, and three on vitamin D intake). Consequently, we found significant inverse associations between HNC incidence and vitamin D exposures, including a circulated concentration of 25-OHD and vitamin D intake  in a comparison of the highest to the lowest vitamin D intake category. Stratified analyses were summarized in FokI polymorphism and HNC risk. The combined analyses revealed a significantly reduced risk of HNC incidence for this mutation in only two genetic models  . The subgroup analyses were reported in A total of three relevant studies were examined for the association between the 2 = 31%) Figure 3TaqI polymorphism was associated with HNC risk. A significant reduction in HNC risk was observed in the overall population , as well as among Caucasian populations   Figure 3BsmI polymorphism was associated with HNC risk. Overall, no significant associations were observed in all five models  based on a fixed-effects model that pooled populations with an 8-12 years’ follow-up Figure 4In this study, we comprehensively summarized the association between vitamin D exposures and HNC events across 16 individual reports. The primary findings indicate that elevated activities of vitamin D from diet intake, genomic polymorphisms, and circulated 25-OHD may protect people from HNC and improve the prognosis of HNC patients to some extent.VDR knockout, enhances the development and growth of MC-26 colon and breast cancer xenografts in Balb/c mice 2D3 influences gene transcription by binding to the promoter region of target genes, which also functions in a promoter-specific and cell-specific manner  cell proliferation, cell cycle as well as angiogenesis, associated with a higher sensitivity to chemotherapeutic agents , which involved in the metabolic process of vitamin D from nature to active substance. The cross-field validation in these three ways could consolidate our conclusions.Moreover, one of our results is mainly driven by the subgroup analysis in population more than 50 years old, which will bring significant meaning to the community because HNC is highly prevalent around 50 years old. Based on data from almost 81,908 participants across 11 nations, the general ability of our findings is relatively solidified. Suppose this can be confirmed in future random clinical trials or more extensive population studies. In that case, a recommendation of vitamin D for people whose age is more than 50 may achieve enormous progress in preventing HNC rate worldwide. Undoubtedly, the appropriate quantity of supplemental vitamin D to avoid overdose-related side-effects needs further research.VDR genomic phenotypes, which could counteract the drawbacks in food frequency questionnaires. The data composition is inadequate to conduct in-depth subgroup analysis, but the stratified and sensitivity analyses ensure that our results are relatively stable. Because of a few studies, we did not perform publication bias. All included literature was searched based on English; thus, language bias may also exist. The non-classical role of vitamin D signaling in stimulating innate immunity and suppressing inflammatory responses has been extensively explored, further research is needed on the direct effects of T lymphocytes in adaptive immunity.We should be aware that available studies included in our study are observational investigations, which may lead to inevitable biases in the analysis. Observational reports of vitamin D intake cannot preclude the possibility that other confounding factors such as outdoor sun exposure and other physical conditions related to the bioavailability of 25-OHD may exist. Furthermore, these enrolled studies used food frequency questionnaires to assess dietary intake of vitamin D, which indicates that a potential bias from the inaccuracy induced by food frequency questionnaires. However, we can confirm the conclusion by the analysis from the circulating 25-OHD concentrations and VDR genomic polymorphisms. Further well-designed randomized controlled trials with larger sample sizes and different ethnic populations are required to clarify the present findings.Elevated activities of vitamin D by diet intake, genomic polymorphisms, and circulated 25-OHD may protect people from HNC events and improve the prognosis of HNC patients. The finding that exposures to high 25-OHD level is more associated with the risk and outcomes of HNC, with evidence most consistent and effect sizes largest for incidence and mortality of HNC compared with vitamin D intake and The original contributions presented in the study are included in the article/Conceptualization: YP, GZ, DH, YL, and XZ. Methodology: YP, GZ, YX, SZ, BT, and HH. Validation: YP, GZ, YX, SZ, BT, HH, and IW. Formal analysis: YP, GZ, and IW. Investigation: YP and GZ. Resources: IW, YL, and XZ. Data curation: YP, GZ, YX, SZ, BT, HH, and IW. Writing—original draft preparation: YP and GZ. Writing—review and editing: YX, SZ, BT, HH, and IW. Supervision: DH, YL, and XZ. Project administration: DH, YL, and XZ. Funding acquisition: DH, YL, and XZ. All authors contributed to the article and approved the submitted version.This work was supported by National Key Research and Development Project (Nos. 2020YFC1316900 and 2020YFC1316901), National Natural Science Foundation of China , Natural Science Foundation of Hunan Province , the Huxiang Young Talent Project (No. 2018RS3024), and the Project of Hunan Health Commission (B2019165).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.


MIF) -173G/C (rs755622) polymorphism and susceptibility to CAD based on a meta-analysis.Coronary artery disease (CAD) remains one of the major causes of death in humans. Genetic testing may allow early detection and prevention of this disease. This study aimed to investigate the association between the macrophage migration inhibitory factor (MIF -173G > C (rs755622) polymorphism and CAD risk published before July 30, 2019. Data were analyzed using the STATA software.We searched several databases to identify observational case-control studies investigating the association between the MIF polymorphisms, were included. The occurrence of CAD was found to be associated with the C allele of the MIF rs755622 SNP in the total population . Further, MIF –173G/C polymorphism was significantly associated with CAD under the allelic model in the Asian  and Caucasian  subgroups. The data showed that the risk of CAD was higher in the population carrying the C allele.Six studies, comprising a total of 1172 CAD cases and 1564 controls evaluated for MIF -173C/G and CAD susceptibility in the Asian and Caucasian populations.We found evidence of associations between  MIF) has been extensively studied in molecular functional and genetics studies. In 1966, MIF was identified as a soluble factor secreted by T cells that delayed hypersensitivity reactions and inhibited the random migration of macrophages [MIF is quite ubiquitously expressed and is an upstream immunomodulatory cytokine. It plays an important role in promoting inflammatory responses in CAD [MIF gene is located on chromosome 22q11.2, and two functional promoter polymorphisms have been studied [5–8 tetranucleotide repeat at − 794. The MIF − 173C allele creates a putative binding site for the transcription factor activating enhancer binding protein 4 and is associated with increased MIF gene expression and protein levels in a cell-type-dependent manner [Atherosclerosis is a chronic arterial wall inflammatory disease  associatrophages . Later srophages . MIF is s in CAD , diabetes in CAD , septices in CAD , psoriass in CAD , and oth studied . One is t manner .MIF − 173C/G is closely related to the production and expression of MIF, which causes the occurrence and development of CAD by promote the inflammatory response.However, according to current reports, MIF − 173C/G have found associations with CAD pathogenesis. To overcome the limitations and outcome bias of individual studies, and to address the inconsistencies in the findings among the various studies, we conducted a more comprehensive meta-analysis based on a systematic literature review to confirm whether MIF − 173C/G was associated with increased sensitivity and risk for CAD.Some studies comparing MIF − 173G/C (rs755622) polymorphism in the PubMed, Embase, WanFang, China National Knowledge Infrastructure databases using the search terms “macrophage migration inhibitory factors,” or “MIF” or “rs755622” or “-173G/C,” and “genetic polymorphism” or “gene polymorphism” and “coronary artery disease,” or “myocardial infarction” in various combinations to identify studies that had investigated the association between MIF -173G/C and CAD, with the last search being conducted on June 14, 2019. No language restrictions were applied. In addition, we reviewed all references cited in the obtained papers, to identify additional studies that were not included in the above-mentioned electronic databases.We searched for reports on the MIF -173 G > C and CAD risk, (2) case-control studies, and (3) sufficient genotype frequencies for calculating the odds ratio (OR) and 95% confidence interval (CI). (4) CAD was diagnosed according to the 1979 WHO criteria for CAD diagnosis: at least one major vessel with ≥50% stenosis in coronary angiography. Studies were excluded if they (1) were a duplication of a previous publication; (2) were comments, abstracts, overlapping studies, reviews, or editorial comments; (3) were family-based studies of pedigrees; (4) had no detailed genotype data and other information; and (5) had a cohort size of less than 100 subjects.Studies were included if they met the following criteria: (1) assessment of the association between We extracted the following information from the selected articles: author, year of publication, country/countries, ethnicity, number of cases and controls, and genotyping methods used. In addition, we determined whether data had been analyzed correctly.www.liebertpub.com/gtmb, Supplementary Fig. SWe used the Newcastle-Ottawa scale to evaluate the quality of the studies included  /Q) to assess the heterogeneity of the studies included [I2 is an index to evaluate the degree of inconsistency among the studies included and to test whether the percentage total variation among the studies was due to heterogeneity or by chance. I2 values range from 0 to 100%, and I2 values of 25, 50, and 75% were considered to indicate low, moderate, and high heterogeneity, respectively. When I2 is greater than 50%, heterogeneity cannot be ignored, and subgroup analysis is needed to evaluate the source of heterogeneity [MIF -173G/C and CAD under six genetic models: an allelic model (C vs. G), homozygote model (CC vs. GG), a heterozygote model (CG vs. CC), a recessive model (CC vs. CG + GG), a dominant model (GG vs. CG + CC), and an additive model (CG vs. CC + GG). To find ethnic effects, we divided patients into two subgroups, Asians and Caucasians, and we conducted a sensitivity analysis by successively omitting one of the six studies and assessing the effect thereof on the results. Begg’s funnel plots and Egger’s linear regression test were used to assess for publication bias across studies [We used Chi-squared tests to evaluate population genotype frequencies to test for the Hardy-Weinberg equilibrium (HWE), if eneities . Q-test ogeneity . We usedincluded . I2 is aogeneity . We asseMIF polymorphisms , by 123.2% under the homozygote model , and by 106.5% under the recessive model . The risk for CAD was reduced by 43.5% under the heterozygote model  and by 31.8% under the dominant model . The additive model  had no statistical significance , by 250.2% under the homozygote model , and by 263.2% under the recessive model , whereas the risk was reduced by 74.0% under the heterozygote model  and by 41.0% under the dominant model  , by 64.0% under the homozygote model , and by 33.1% under the additive model , and the risk was reduced by 26.6% under the dominant model . There was no significant effect under the recessive  and heterozygote  models , which we considered to be due to the fact that the sample size was not sufficiently large; however, this did not affect the results of the analysis . CAD risk was increased in the allelic, recessive, and homozygote models, whereas it was decreased in the dominant and heterozygote models. To identify and reduce the source of heterogeneity, we analyzed the Asian and Caucasian populations separately. We could conclude that people with MIF -173C were more likely to develop CAD, which might be related to increased MIF expression and production, which aggravated the inflammatory reaction, leading to the occurrence and development of CAD. There are several potential causes of the observed heterogeneity. First, study characteristics, including the source population for the case-control groups, race, research design, CAD subtypes, sample size, genotyping methods and specific typing can differ among studies and may explain the differences in subgroup analysis. Second, ethnic groups are genetically different, and clinical manifestations depend on factors such as age, sex, obesity, hypertension, and diabetes, which may be related to CAD heterogeneity [In our systematic meta-analysis, including six studies comprising approximately 2700 participants, ogeneity . Third, MIF -173C/G and CAD, which would allow a more accurate judgment of this gene polymorphism in the treatment of human CAD, had not been conducted to date. Second, we selected Chinese and foreign studies, including two different ethnicities, for which we conducted subgroup analyses, which allowed us to find the source of heterogeneity and further assess the risk of MIF -173C/G for CAD in these two populations. In contrast, our study had several limitations. First, it included only six studies. Therefore, additional information from large-cohort studies on MIF -173C/G and CAD is required to reduce the publication bias. Second, numerous factors can influence the occurrence and development of coronary heart disease, and we did not consider other polymorphisms in MIF, such as -794CATT5–8, or in other related genes. Third, despite the inclusion of different ethnic groups, populations may have different habits, including different eating and lifestyle habits, which should be considered more carefully in future studies. Fourth, more research is needed to confirm the relevance of -173 C/G to the risk of CAD and to clarify the underlying mechanism.Our meta-analysis had some strengths. First, a comprehensive meta-analysis to provide substantial evidence of the association between MIF -173C/G polymorphism was associated with CAD susceptibility. MIF -173C/G may regulate and increase the risk of CAD by increasing MIF secretion. Our findings may help to understand the effects of CAD-related genes in total the population and in different ethnic groups, and lay a foundation for the prevention of coronary heart disease in the future.Our meta-analysis demonstrated that Additional file 1 Supplementary Table S1. Scale for Methodological Quality Assessment.Additional file 2 Supplementary Figure S2 Forest plot of MIF -173C/G rs755622 in subgroup analysis for homozygote model comparison (CC vs.GG). Supplementary Figure S3 Forest plot of MIF -173C/G rs755622 in subgroup analysis for recessive model comparison (CC vs.CG + GG). Supplementary Figure S4 Forest plot of MIF -173C/G rs755622 in subgroup analysis for heterozygote model comparison (CG vs.CC). Supplementary Figure S5 Forest plot of MIF -173C/G rs755622 in subgroup analysis for dominant model comparison (GG vs.CG + CC). Supplementary Figure S6 Forest plot of MIF -173C/G rs755622 in subgroup analysis for additive model comparison (CG vs.CC + GG).


P=0.20, I2=54.4%), as well as the subgroup analysis according to ethnicity, control source, tumor locations, and HWE status of controls. In addition, heterogeneity, accumulative, sensitivity analysis, publication bias and trial sequential analysis (TSA) were conducted to test the statistical power. Overall, our results indicated that the pri-miR-26a-1 rs7372209 C>T polymorphism may not be a potential risk for cancer development.MiR-26 has been suggested to play a tumor-suppressive role in cancer development, which could be influenced by the mutate pri-miR-26ª-1. Molecular epidemiological studies have demonstrated some inconsistent associations between pri-miR-26ª-1 rs7372209 C>T polymorphism and cancer risk. We therefore performed this meta-analysis with multivariate statistic method to comprehensively evaluate the associations between rs7372209 C>T polymorphism and cancer risk. Eleven publications involving 6,709 patients and 6,514 controls were identified. Multivariate analysis indicated that the over-dominant genetic model was most likely. Pooled results indicated no significant association in the overall population (CC+TT vs. CT: OR=1.08, 95%CI=0.96-1.22,  Cancer is a leading cause of death worldwide . In 2012The aberrant expression of related genes in a cell causes abnormalities in cell proliferation and cancer development. The microRNA family comprises important small non-coding RNA molecules that have a length of 21-25 nucleotides and are characterized by double-stranded structures , which oMicroRNA (miRNA) can regulate their posttranscriptional repression by binding to 3′-untranslated region (3-UTR) of the target gene mRNAs with imperfect complementary sequences . The abnGene mutation in miRNA or pri-miRNA can affect miRNA function via several different biosynthetic pathways. Single nucleotide polymorphism (SNP) is one of the most common type of gene mutation, and the SNPs in pri-miRNA genes can change spatial structure, affect the miRNA–mRNA interaction network, activate the aberrant expression of target genes and increase the risk of cancer. For pri-miR-26a-1, rs7372209 C>T is the most common locus that has attracted more attentions. In 2008, Yang et al. published the first case-control study of Chinese population and results did not show any significant association between the pri-miR-26a-1 rs7372209 C>T polymorphism and bladder cancer . SubsequIn total, 252 articles were retrieved via a system search. Among these studies, 135 were excluded during the first step of article duplication and 97 during the abstract and full-text review . FinallyP=0.20, I2=54.4%) (P=0.04). Then, three studies that did not satisfy the HWE were excluded and the pooled analysis didn’t present any significant result with the remaining nine case-control studies   and other stratified analyses of hospital based control group and lung cancer subgroup (The estimated λ=-0.81 (95%CI=-3.85-2.24) and less than zero. Hence, the over-dominant genetic model could be used in the general population  . Heterog2=21.5%) . Moreove2=21.5%) . Howeversubgroup .A cumulative analysis of the publication date was conducted in the over-dominant model, and results showed that the pooled ORs were not qualitatively affected by the additional studies, indicating that the results were highly stable . SensitiP=0.18)  .TSA was conducted in the over-dominant model. Result showed that the cumulative Z-curve (blue line) did not cross the conventional P=0.05 boundary (red straight lines) and did not reach the required information sizes (n=52208). These data indicated that the cumulative evidence on the pri-miR-26a-1 rs7372209 C>T polymorphism was not adequate and more trials were required .MiRNAs belong to the family of non-coding small RNAs that comprise 22-25 nucleotides, which can regulate the target gene expression via the post-transcriptional pathway by binding to the 3'-UTRs . The abePri-miR-26a-1 is a novel, small RNA that involves several signaling pathways and acts as a tumor suppressor in tumorgenesis and cancer development by binding to Lin28B and Zcchc11 to suppress cancer development and metastasis , 32. TheP=0.38) in US [P=0.42; OR=1.03, 95% CI=0.87-1.21, P=0.73), indicating no significant risk for esophageal cancer. In contrast, Wang et al. reported that South Africans with rs7372209 C>T polymorphism had a significantly reduced risk for esophageal squamous cell carcinoma in the additive model  and the dominant genetic model  in the mixed ancestry group in 2013 [Yang et al. (2008) first analyzed the frequency of rs7372209 C>T polymorphism in individuals with bladder cancer and indicated less susceptibility in dominant model  in US . Thereaf8) in US  and Zhan8) in US  studied  in 2013 .P=0.01) [P=0.01) [In 2014, Li et al. investigated the association between rs7372209 C>T polymorphism and the risk of lung cancer and found that the subjects with T allele of rs7372209 C>T polymorphism had an increased risk of cancer development  . On the P=0.01) . In 2015P=0.01)  and YingP=0.01)  revealed[P=0.01) .The above mentioned controversy may be attributed to the following: (1) the populations assessed were of different ethnicities, (2) varying genotype methods could influence outcomes, (3) deviation from HWE could be observed in some studies, and (4) the design and procedure of each research were not similar, thereby reducing the consistency. Hence, we conducted a meta-analysis of 11 publications (12 independent case-control studies) involving 12,223 participants to assess the association between rs7372209 C>T polymorphism and cancer susceptibility.Based on our knowledge, the etiology and pathogenesis of cancer development remains unclear. Increasing evidences has shown that some miRNAs and the genetic polymorphisms of miRNAs are associated with cancer susceptibility. In the current meta-analysis, we comprehensively summarized data on the relationship between rs7372209 C>T polymorphism and the risk of cancer, and no significant association was found between rs7372209 C>T polymorphism and cancer in the whole population and in the subgroup with the finest genetic model. These results indicated that these genetic polymorphisms may not be the only factor affecting the development of cancer. Furthermore, some univariate analyses revealed that Chinese have increased risks of rs7372209 C>T polymorphism and cancer. The co-dominant and recessive models indicated that the TT mutant homozygote was associated with a 19% increased risk of cancer development in Chinese, but not in Caucasians. These differences were assumed maybe due to the number of relative studies (9 case-control studies on Chinese and 3 case-control studies on Caucasians) between two ethnicities. In general, tumor formation often involves a complex process, during which a variety of factors and proteins participate and of complex signal transduction network. Variations in a single gene and locus might not play a decisive role in tumorigenesis affecting the entire signaling pathway, so did the rs7372209 C>T polymorphism too. Nevertheless, a more scientific statistical method was used to select a better gene model through multiple regressions to analyze the mutation of this polymorphic site and the susceptibility of cancers in this study. Then, the analysis indicated that the over-dominant genetic model could be the most appropriate choice and the results revealed there was no significant association between rs7372209 C>T polymorphism and cancers in the general and subgroup analyses.To date, this study conducted the first meta-analysis on the association between rs7372209 C>T polymorphism and the risk of cancer. It has some advantages, which were as follows: (1) a more advanced method with multivariate meta analyses was used to select the genetic model; (2) more scientific search strategies and rigorous statistic methodologies were utilized; and (3) sensitivity, accumulation, and meta-regression analyses were conducted to identify the potential interfering factors that can contribute to the inconsistencies in the results; and (4) the TSA was conducted and indicated that the current data were not enough. The current study had some limitations that should be emphasized. First, only one SNP locus was examined in this meta-analysis, and the interaction mechanisms between gene-gene and gene-environment were not assessed due to the limited number of data. Second, heterogeneity was observed in the included studies, which might affect the current results. However, it was partially alleviated in the subsequent stratified analysis, such as that conducted in the Chinese population and the hospital-control design and colorectal cancer groups. Third, almost all studies included from Asians, thereby limiting the application of our results in the general population. Fourth, all summarized results were based on published papers, which might have distorted the actual effect due to publication bias even if there was no significant publication bias found using both Egger’s test and Begg’s funnel plot.In summary, the pri-miR-26a-1 rs7372209 C>T polymorphism may not be an independent risk factor for tumorigenesis and the development of cancer. Owing to the insufficient sample size, more high-quality studies with a large sample size must be conducted to validate the results of this study.The design and implementation of this meta-analysis were in accordance with the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA Compliant) statement . All incRelevant studies were searched in online databases  to investigate the relationship between the pri-miR-26a-1 rs7372209 C>T polymorphism and the risk of cancer from inception to June 1, 2019. The bibliographies of the relevant reviews and studies that were included were retrospectively assessed to identify more articles. The following search terms and strategy were used :#1 pri-miR-26a-1#2 microRNA-26a#3 miR-26a#4 miR-26a-1#5 rs7372209#6 #1 OR #2 OR #3 OR #4 OR #5#7 mutation#8 variant#9 polymorphism#10 #7 OR #8 OR #9#11 neoplasm#12 tumor#13 cancer#14 #11 OR #12 OR #13#15 #6 AND #10 AND #14The inclusion criteria were as follows: (1) case-control studies that investigated the association between the pri-miR-26a-1 rs7372209 C>T polymorphism and the risk of cancer; (2) those with a sufficient number of data on genotype distribution that can be utilized to examine the crude odds ratios (ORs) and 95% confidence intervals (CIs); (3) those written in English and Chinese only; and (4) those in which the largest or most recently sample data were adopted in cases of multiple publications with duplicate or overlapping data on the same theme. Meanwhile, the exclusion criteria were as follows: (1) case series, meta-analyses or reviews; (2) duplicate publications; (3) case-control studies that did not focus on pri-miR-26a-1 rs7372209 C>T locus; (4) unrelated studies; and (5) studies with insufficient data.Two independent authors conducted a quality assessment of all included studies using the modified Newcastle-Ottawa Quality Assessment Scale . Six depTwo authors (Hu and Jiang) reviewed and extracted the related information from the included studies independently. These data included the first author's name, year of publication, country or region where the study was conducted, control design, race, sample size in the case and control groups, number of data on each genotype, genotyping methods, HWE status in controls, and type of cancer.2 statistical method [2 value exceeded 40%, whereas the fixed-effect model was used then [P value<0.05 was considered as statistically significant.The ORs and 95% CIs were calculated to examine the relationship between the pri-miR-26a-1 rs7372209 C>T polymorphism and the risk of cancer. A more scientific statistical method was used in selecting the genetic models. The two pooled logORs of log(CT vs. CC) and log(TT vs. CC) for rs7372209 C>T were calculated first; then, the ratio λ of the two logORs was assessed using the following formula: λ=log(AG vs. AA)/log(GG vs. AA). The genetic model was inferred and calculated using the ratio λ when the value of λ is equal to 0, 0.5, and 1, which correspond to the recessive, co-dominant, and dominant models, respectively. Otherwise, when the ratio λ is <0 or >1, an over dominant model was considered appropriated , 36. Fursed then , 39. Subsed then . Finallysed then . STATA vSupplementary Table 1


It has been shown that miR-192 is abnormally expressed in a variety of cancer types and participates in different kinds of signaling pathways. The role of miR-192 in the diagnosis and prognosis of cancer has not been verified. This article is aimed at exploring the diagnostic and prognostic value of miR-192 through a systematic review and meta-analysis.  A systematic search was performed through PubMed, Embase, Web of Science, and Cochrane Library databases up to June 16, 2020. A total of 16 studies were enrolled in the meta-analyses, of which 11 articles were used for diagnostic meta-analysis and 5 articles were used for prognostic meta-analysis. The values of sensitivity and specificity using miR-192 expression as a diagnostic tool were pooled in the diagnostic meta-analysis. The hazard ratios (HRs) of overall survival (OS) with 95 confidence intervals (CIs) were extracted from the studies, and pooled HRs were evaluated in the prognostic meta-analysis. Eleven studies including 667 cancer patients and 514 controls met the eligibility criteria for the diagnostic meta-analysis. Five studies including 166 patients with high miR-192 expression and 236 patients with low miR-192 expression met the eligibility criteria for the prognostic meta-analysis. p = 0.020).  The overall diagnostic accuracy was as follows: sensitivity 0.79 (95%CI = 0.75-0.82), specificity 0.74 (95%CI = 0.64-0.82), positive likelihood ratio 3.03 (95%CI = 2.11-4.34), negative likelihood ratio 0.29 (95%CI = 0.23-0.37), diagnostic odds ratio 10.50 (95%CI = 5.89-18.73), and area under the curve ratio (AUC) 0.82 (95%CI = 0.78-0.85). The overall prognostic analysis showed that high expression of miR-192 in patients was associated with positive survival (HR = 0.62, 95%CI : 0.41-0.93,  Our results revealed that miR-192 was a potential biomarker with good sensitivity and specificity in cancers. Moreover, highly expressed miR-192 predicted a good prognosis for patients. Cancer is threatening human health and shorting human life. Around 1.8 million new cancer cases and 60 thousands of cancer deaths occurred in the United States based on the cancer statistics 2020 . TherefoMicroRNA-192 was firstly confirmed by Lim et al. in 2003 . It is rA systematic literature search was carried out in PubMed, Embase, Web of Science, and Cochrane Library databases up to June 2020. The first part was to screen articles that explored the diagnostic value of miR-192 in cancers. Both MeSH terms and free-text words were used in the search strategy. The following search keywords were used in combination: “neoplasms” or “tumor” or “cancer”, “diagnosis”, “ROC curve”, “sensitivity and specificity”, and “microRNA-192”. The second part was to screen articles that explored the prognostic value of miR-192 in cancers. The keywords were as follows: “neoplasms” or “tumor” or “cancer”, “survival”, “prognosis”, “recurrence”, and “microRNA-192”.For diagnostic meta-analysis, studies were included for further evaluation if they meet the following criteria: (1) any types of cancers concerning miR-192, (2) inclusion of a diagnostic standard, (3) sufficient data  for calculating the sensitivity and specificity, (4) studies based on humans, and (5) studies published in English. Exclusion criteria were as follows: (1) non-English articles; (2) other types of articles such as conference abstracts, reviews, meta-analysis, patents, case reports, comments, and letters; and (3) insufficient data for calculating the sensitivity and specificity.For prognostic meta-analysis, studies were included for further evaluation if they meet the following criteria: (1) any types of cancers concerning miR-192, (2) inclusion of a diagnostic standard, (3) associations between the expression of miR-192 and prognosis of patients being determined, (4) hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) being evaluated, and (5) English publications. Exclusion criteria were as follows: (1) non-English articles; (2) other types of articles such as conference abstracts, reviews, meta-analysis, patents, case reports, comments, and letters; (3) insufficient data to calculate the HRs and 95% CIs; and (4) the prognostic data based on TCGA dataset.All studies were independently selected by two investigators (Lili Wang and Yuhan Liu), and uncertain data were reviewed by a third author (Chen Lyu). The following information was collected in diagnostic analysis: first author's name, publication year, nationality, ethnicity, cancer type, sample type, test method, cut-off, case number, sensitivity, and specificity. For the prognostic analysis, the following information was collected: first author's name, publication year, nationality, cancer type, cases of high expression of miR-192, cases of low expression of miR-192, the endpoint of follow-up, and HRs along with their corresponding 95% CIs.The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) tool  was usedQ test and Higgins I-squared statistic. That I2 > 50%, and p < 0.10 indicated heterogeneity among studies. Publication bias was evaluated by funnel plots and by Begg's and Deeks' tests. p < 0.05 suggests the existence of publication bias in studies. For the prognostic meta-analysis, the pooled HRs and 95% CIs were determined using the Z-test, with p < 0.05 defined as significant. HR > 1 indicated poor prognosis for patients with miR-192, while HR < 1 meant a protective effect for the prognosis of highly expressed miR-192. The methods for the assessment of heterogeneity and publication bias were the same as those for the diagnostic meta-analysis.All data analyses were performed using Stata MP 16.0 software . For the diagnostic meta-analysis, the pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were generated through bivariate meta-analysis. The summary receiver operator characteristic (SROC) curve and the area under the curve (AUC) were calculated to evaluate the overall diagnostic value of miR-192 in cancers. The heterogeneity test was conducted using the chi-square-based n = 2, NSCLC), cholangiocarcinoma , hepatocellular carcinoma , pancreatic ductal adenocarcinoma , pancreatic cancer , cervical cancer , bladder cancer , and acute myeloid leukemia . The expression of miR-192 was evaluated through qRT-PCR in the tissue (n = 3), serum (n = 6), and urine (n = 2).A total of 387 articles were searched using the search strategy, of which 11 articles , 19–26 mn = 1, GC), colon cancer , small-cell lung cancer , hepatocellular carcinoma , and acute myeloid leukemia . The expression of miR-192 was assessed through qRT-PCR using plasma (n = 1), tissue (n = 3), and serum (n = 1).For the prognostic meta-analysis, 301 articles were obtained from four databases, and only 5 articles , 27–30) –30 27–30The quality of diagnostic meta-analysis was assessed using the QUADAS-2 tool. All the studies were scored between 4 and 6 points which represented moderate or high quality . For theI2 = 9.63%, 95%CI = 0-61.53%), but significant heterogeneity in the specificity . Overall, the sensitivity and specificity for the pooled data were 0.79 (95%CI = 0.75-0.82) and 0.74 (95%CI = 0.64-0.82). In addition, the pooled PLR was 3.03 (95%CI = 2.11-4.34), and the NLR was 0.29 (95%CI = 0.23-0.37) as shown in The sensitivity and specificity of 11 studies are presented in the forest plots as shown in The goodness-of-fit and bivariate normality Figures  analysesp = 0.82, Deeks' funnel plot asymmetry test suggested that there was no significant publication bias (p = 0.258), also indicating no threshold effect existing. The Galbraith radial plot showed that all the studies were in the 95% CI region suggesting no heterogeneity , so a random effects model was used. The pooled HR was 0.62 , suggesting that a high level of miR-192 was associated with positive patients' survival. The funnel plot was symmetrical, and Begg's test (p = 0.806) also indicated that there was no publication bias , sensitivity 0.79 (95%CI = 0.75-0.82), and specificity 0.74 (95%CI = 0.64-0.82), demonstrating that miR-192 might be used as a novel biomarker for the detection of cancers. The pooled DOR was 10.50 (95%CI = 5.89-18.73) suggesting that miR-192 is reliably used in cancer diagnosis.The pooled PLR was 3.03 (95%CI = 2.11-4.34), and NLR was 0.29 (95%CI = 0.23-0.37), meaning that cancer patients had a higher 3.03-fold probability of being miR-192 positive compared to control patients, and the probability of a negative result in patients was 0.29 times that in nonpatients. Fagan's nomogram revealed that when a pretest probability of 50% was specified, the positive posttest probability would increase to 75%, and the negative posttest probability would decrease to 22%. The results suggest that miR-192 is reliable for the detection and diagnosis in NSCLC, CCA, HCC, PDAC, PC, CC, BC, and AML.p = 0.020), suggesting that a high level of miR-192 was associated with positive patients' survival in GC, CoC, HCC, SCLC, and AML.The pooled HR was 0.62 , but there was significant heterogeneity in the specificity . One reason for the heterogeneity perhaps was that the ethnicity of patients in most studies was Asian, which may result in the bias. Secondly, the cut-off values in studies were different and some of them were not mentioned. Thirdly, different sample types might contribute to the heterogeneity. However, the ROC plane represented a nontypical shoulder arm-like appearance, and Spearman's correlation coefficient was -0.374 (p = 0.258), suggesting that there was no threshold effect. Therefore, the threshold effect was not a major cause of heterogeneity.In the diagnostic meta-analysis, the sensitivity had no heterogeneity . However, meta-regression analyses and subgroup analysis cannot be performed because of insufficient study numbers.For the prognostic meta-analysis, there was also heterogeneity (The present study has several limitations: firstly, the number of studies available for meta-analysis was small; secondly, the kind of ethnicity was monotonous; thirdly, the values of cut-off in the studies were partial and different; finally, it is difficult to conduct subgroup analysis, such as the influence of gender and tumor stage on the results due to the limited data of original articles.In conclusion, this study demonstrates that miR-192 has a moderate diagnostic value to distinguish cancer patients from controls and also can be a promising positive prognostic biomarker in some types of cancer.


A high prevalence of cardiovascular risk factors including age, male sex, hypertension, diabetes, and tobacco use, has been reported in patients with Coronavirus disease 2019 (COVID-19) who experienced adverse outcome. The aim of this study was to investigate the relationship between cardiovascular risk factors and in-hospital mortality in patients with COVID-19.MEDLINE, Cochrane, Web of Sciences, and SCOPUS were searched for retrospective or prospective observational studies reporting data on cardiovascular risk factors and in-hospital mortality in patients with COVID-19.Univariable and multivariable age-adjusted analyses were conducted to evaluate the association between cardiovascular risk factors and the occurrence of in-hospital death.The analysis included 45 studies enrolling 18,300 patients. The pooled estimate of in-hospital mortality was 12% (95% CI 9–15%). The univariable meta-regression analysis showed a significant association between age , diabetes  and hypertension  with in-hospital death. Male sex and smoking did not significantly affect mortality. At multivariable age-adjusted meta-regression analysis, diabetes was significantly associated with in-hospital mortality ; conversely, hypertension was no longer significant after adjustment for age . A significant association between age and in-hospital mortality was confirmed in all multivariable models.This meta-analysis suggests that older age and diabetes are associated with higher risk of in-hospital mortality in patients infected by SARS-CoV-2. Conversely, male sex, hypertension, and smoking did not independently correlate with fatal outcome. Coronavirus disease 2019 (COVID-19) is a recently recognized infective disease caused by a new betacoronavirus, which has sparked in Hubei province, China, and has spread rapidly worldwide taking on pandemic proportions.  OR “COVID 19”[All Fields] OR “severe acute respiratory syndrome coronavirus 2”[All Fields] OR “2019-nCoV”[All Fields] OR “SARS-CoV-2”[All Fields]) AND ; Cochrane Library, Web of Science and SCOPUS—“COVID-19” OR “COVID 19” OR “SARS-CoV-2” OR “severe acute respiratory syndrome coronavirus 2” OR “2019-nCoV”. Search was conducted by using the Thomson Reuters EndNote X7 software.Citations were screened on the title and abstract level by three independent reviewers , and potentially eligible reports were retrieved and scrutinized in full text. Divergences were resolved by discussion and consultation with a fourth investigator (G.G.). The full-size articles published in peer-reviewed journals were considered for this meta-analysis.Prospective and retrospective observational studies were included if they met the following pre-specified criteria: (I) inclusion of patients hospitalized for COVID-19; (II) data on in-hospital mortality; (III) data on baseline cardiovascular risk factors. Studies reporting only surrogate outcome measures or with largely incomplete data on in-hospital outcome were excluded. Studies reporting data on special populations  were excluded. For papers collecting overlapping data, only studies with the largest number of patients were selected. In some doubtful cases, corresponding authors were contacted for requests for clarifications.Two investigators (A.S. and L.E.) independently extracted data by using an agreed predefined spreadsheets reporting first author, journal, year of publication, study design, region and country, period of enrollment, sample size, in-hospital mortality, demographic and clinical cardiovascular risk factors . Data on the severity of the disease expressed by the percentage of acute respiratory distress syndrome (ARDS) and of invasive mechanical ventilation (IMV) use, as well as data on clinical setting expressed by the percentage of admission in intensive care unit (ICU) were collected. Disagreements were resolved by consensus among all the investigators.Two unmasked reviewers  evaluated the quality of the studies on pre-specified electronic forms according to the Newcastle–Ottawa scale items. The reviewers independently appraised study selection, comparability, and outcome of each report, and divergences were resolved after consensus.The study outcome measure was the occurrence of death during hospitalization.The meta-analysis was performed by estimating the mean in-hospital mortality over all studies using random effects models with restricted maximum-likelihood estimator. Random-effects model was preferred for estimating the average effect and its precision, which would give a more conservative estimate of the 95% confidence interval (CI), due to the heterogeneity within and between studies. Studies with larger sample size and therefore a smaller standard error received more weight when calculating the mean survival proportions. The individual study proportions of outcomes were converted using the Freeman–Tukey double arcsine transformation method before the pooled analysis. The summarized proportions in the original scales were calculated as the back-transformation of the arcsine transformed estimates. Raw data on the prevalence of cardiovascular risk factors were collected for each study included in this meta-analysis.Multiple univariable meta-regression analyses were performed to appraise the possible association between the proportion of single cardiovascular risk factors and the risk of death, as well as the degree of heterogeneity among studies. In order to assess whether the associations resulted at univariable analyses were age-independent, data on each cardiovascular risk factor were entered in age-adjusted multivariable meta-regression models.These analyses were performed using the logarithmic transformation of the proportions, then back transformed through the exponential function.To appraise for the influence of clinical setting on the study outcome, we conducted a subgroup analysis for studies including only ICU patients versus studies enrolling mixed population (both ward and ICU) and tested any interaction between subgroups.The hypothesis of statistical heterogeneity was tested by means of Cochran Q statistic and the null hypothesis of statistical homogeneity was refused if p values were less than 0.10. I  values <Of 12,038 reports initially identified, we retrieved 8,514 studies through merging of data from independent searches and removing duplicates. Sixteen studies have been excluded because of overlapping populations. During screening and eligibility assessment, we identified 45 full-size articles enrolling 18,300 patients. , 15–54 T2: 96.5%; p < 0.001; Fig. The pooled estimate of in-hospital mortality was 12% (95% CI 9–15%) although affected by a high heterogeneity degree among studies (Iinteraction = 0.004).Data on clinical setting were available in 19 studies Fig. . Seven sThe univariable meta-regression analyses between cardiovascular risk factors and in-hospital mortality are displayed in Fig. At multivariable age-adjusted meta-regression analysis, diabetes was significantly associated with in-hospital mortality ; conversely, hypertension was no longer significant after adjustment for age , suggesting that in-hospital mortality did not depend on the size of the studies  studies, and selective reports from special populations. .By including 45 studies and 18,300 patients, this is the largest meta-analysis investigating the effect of cardiovascular risk factors on in-hospital mortality in COVID-19, by using crude and multivariable meta-regression models, available so far. The main findings of this study can be summarized as follows: (I) COVID-19 was associated to a high risk of in-hospital death, which occurred in about one patient in 8; (II) studies with high percentage of ARDS and IMV use, two indexes of disease severity, as well as of ICU admission, reported the highest risk of death during hospitalization; (III) age and diabetes were independent predictors of mortality; (IV) after adjustment for age, hypertension did not show any significant association with the risk of in-hospital death.The mortality estimate of COVID-19 in the general population depends on the number of deaths relative to the number of confirmed cases of infection, which is not representative of the actual death rate, and may be substantially overestimated. , 57 RealThe pooled mortality estimate in our analysis was affected by a wide inconsistency between patient cohorts. There are many reasons for the effect variability detected across observational studies including clinical setting , the prevalence of in-hospital complications (e.g. ARDS) and the need of invasive mechanical supportive measures, which may play as effect modifiers. We tried to account for this variability by performing exploratory analyses of the relationships between the rate of mortality and the proportion of ARDS and IMV use, which are indexes of disease severity. As expected, the higher the percentage of ARDS/IMV among patients enrolled, themm higher was the rate of death during in-hospital course. In addition, the subgroup including only studies conducted in ICU, compared to the mixed group, showed a significantly higher risk of death. These analyses were still affected by high residual heterogeneity suggesting that these variables, although able to stratify prognosis, could not account for the differences among the studies included in this meta-analysis. Our analysis could not account for multiple variables as well as for concealed confounders such as the availability of health-care resources, in-hospital paths, healthcare systems and strategies adopted in the context of pandemic between centers or countries.  ActuallyThe association of age with mortality is an expected finding; noteworthy, this significant correlation persisted in multiple adjusted meta-regression models including other cardiovascular risk factors. This result underlies the importance of individual preventive and protective measures during COVID-19 public health crisis and of dedicated healthcare strategies for elderly patients during hospitalization.Diabetes is the second most common comorbidity (after hypertension) in hospitalized patients with COVID-19, and its prevalence increase with age. , 26, 60 SARS-CoV-2 binds to the zinc peptidase angiotensin-converting enzyme 2 (ACE2), a surface molecule expressed by endothelial cells of arteries and veins, arterial smooth muscle, epithelial cells, and immune cells.  Some autOur study demonstrates that the association between hypertension and mortality in hospitalized patients with COVID-19 reflect largely the older age of these patients. In fact, the significant correlation observed at the univariable meta-regression model was not confirmed after adjustment for age. Preliminary studies suggested that hypertension was a risk factor for in-hospital outcome in patients with COVID-19. , 26, 60 The association between smoking and mortality in COVID-19, though plausible, is still debated , 66. A rThe recent onset and the variable dissemination pattern of the outbreak make difficult to draw firm conclusions on the clinical characteristics and epidemiology of COVID-19. Our data indicate that elderly and diabetic patients are higher-risk populations, and suggest taking utmost care in clinical management of these patients during hospitalization.Continuous surveillance, with reporting of patient characteristics worldwide, are required to confirm our findings and more deeply understand the relationship between cardiovascular risk factors and outcome of patients infected by SARS-CoV-2.Some limitations of our study should be acknowledged. Although we included 45 studies enrolling 18,300 patients, results of meta-analyses are hypothesis-generating and should be interpreted accordingly.The observational nature of the studies included might have contributed to the heterogeneity observed in this analysis. We tried to manage this issue by performing univariable meta-regressions for ARDS and IMV as well as a subgroup analysis for ICU vs ICU/ward. Although these analyses showed significant and clinically valuable results, they were still affected by a substantial residual heterogeneity.Owing to the intrinsic limitations of study-level analyses, we could not account for multiple potential confounders and we adjusted only for age, considered the most important confounding factor in this clinical setting. Moreover, we could not adjust for hidden confounders as well as for patient characteristics non-systematically or rarely reported.Many authors reported incomplete clinical and instrumental information  due to factors such as critically ill patients, operator’s fear of contagion, and in-hospital paths. We may hypothesize that difficulties in data collection/storage and limited feasibility/repeatability of instrumental exams may have affected the completion and granularity of data.To meet the urgent need of clinical reports on COVID-19, many studies encompassed a relatively short follow-up time as compared to the course of the disease, and some of them ended before the discharge or death of each patients enrolled. Although we tried to manage this issue by excluding the studies with higher number of open cases at the end, a certain underestimation of mortality is likely. We do not claim to provide the exact estimate of in-hospital mortality in COVID-19 pandemic, but to explore the potential association between cardiovascular risk factors and outcome. Since the number of pandemic-focused studies is increasing, and clinical observation of these patients is ongoing, the current mortality pattern might change to some extent in the next weeks or months.The majority of studies included in this analysis reported data from Chinese populations, and only ten reports were from other countries (3 from Europe and 7 from US). This issue might have affected the generalizability of our findings, and requires confirmation by large worldwide studies.Among the cardiovascular risk factors, we did not analyze unfrequently reported conditions such as obesity, dyslipidemia, and family history of cardiovascular disease. Indeed, these data were seldom reported in the items selected for this meta-analysis, and were not sufficient for inference analysis.This study suggests that older age and diabetes are associated to higher risk of in-hospital mortality in patients infected by SARS-CoV-2. Conversely, hypertension, male sex and smoking did not independently correlate with fatal outcome at multivariable meta-regression analysis.Although difficult to realize in a pandemic scenario, large multicenter cross-national studies are warranted to improve our understanding on the association between cardiovascular risk factors and mortality in COVID-19.Additional file 1: Main characteristics of the studies included in the analysis.Additional file 2: Quality assessment of the studies based on the Newcastle–Ottawa scale.


We further used in silico tools to investigate this correlation.We performed an updated analysis utilizing data from electronic databases to obtain a more accurate estimation of the relationship between Pheterogeneity = 0.001, P = .212); nevertheless, the XPC rs2228001 A/C variant was associated with PCa risk in Asian descendants in the subgroup analysis . In silico tools showed that more than 20 proteins can participate in the protein crosstalk with XPC. The expression of XPC was down‐regulated in all Gleason scores of prostate cancer.Totally, 5,305 PCa cases and 6,499 control subjects were evaluated. When all studies pooled together, we detected no positive result (recessive genetic model: OR = 1.14, 95% CI = 0.93‐1.40, XPC rs2228001 A/C variant may be associated with elevated PCa risk in Asian patients.The present study indicated that the  In Asian descendants, the PCa incidence and mortality rates were increasing extensively in recent years.Prostate cancer (PCa) is the most common malignant tumor among males all over the world. Previous publications reported that PCa is the second and third leading cause of male death in the United States and Europe, respectively.XPC gene located on c3p25 of homo sapiens.XPC can alter the capacity of NER and lead to carcinoma of human.Studies have shown that genetic factors may play a crucial role in the development of PCa. Down‐regulation of DNA repair is a pivotal factor in the progression of PCa.XPC rs2228001 A/C variant may be associated with increased risk for colorectal, bladder, breast, and lung cancer.XPC variant and PCa likelihood was previously assessed.XPC rs2228001 A/C polymorphism and PCa susceptibility in different case‐controlled studies. Hence, a systematic analysis based on all eligible studies was conducted to further investigate the correlation between the XPC rs2228001 A/C polymorphism and PCa risk.Previous publications demonstrated that the 22.1XPC rs2228001 A/C polymorphism and PCa susceptibility. The search terms were as follows: “XPC OR xeroderma pigmentosum group C,” “polymorphism OR single nucleotide polymorphism OR mutation OR variant,” and “carcinoma OR tumor OR adenocarcinoma OR cancer.” The last search was updated on April 10, 2020. We further screened the supplementary material of accept articles to maximize the search.We performed a comprehensive literature search on electronic databases including Web of Science, Cochrane Library, Google Scholar, PubMed, EMBASE, and Chinese Biomedical Database to retrieve all publications on the 2.2XPC rs2228001 A/C polymorphism and PCa risk; (b) including available genotype frequencies to calculate odds ratio; and (c) using a case‐control design.Two investigators independently searched the studies according to inclusion criteria. The inclusion criteria were as follows: (a) evaluating the association between the 2.3XPC rs2228001 A/C polymorphism; (c) review articles; and (d) duplication with overlapping data from the same authors.The exclusion criteria were as follows: (a) Data of control were not available; (b) with no available genotype frequency for the 2.4XPC rs2228001 A/C variant, and P‐value of Hardy‐Weinberg equilibrium (HWE) for case and control. Any disagreement should be addressed by discussion with a third investigator to achieve a final decision.For every included study, the following information was extracted: name of author, year of publication, control source, ethnicity, genotyping method, PSA level (ng/mL), age range, sample size of case and control, genotyping data of the 2.5XPC rs2228001 A/C polymorphism and PCa risk. Four genetic models were employed in the current analysis: allelic comparison , heterozygous contrast (CA vs AA), dominant genetic model (CC + CA vs AA), and recessive model (CC vs CA + AA). P‐value of heterogeneity was calculated by the Q test. If P‐value for Q tests more than .005, a fixed‐effect model (Mantel‐Haenszel method) was applied. On the other hand, a random‐effect model (DerSimonian‐Laird method) was conducted. Publication bias was checked by Egger's test and Begg's plot. Moreover, sensitivity analysis was applied to examine the impact of each study on the combined OR P‐value of HWE was detected by chi‐square test. P‐value more than 0.05 indicates an HWE balance. The subgroup analysis included ethnic types and source of control. The above analyses were conducted utilizing Stata software .Odds ratio and 95% confidence interval were adopted to evaluate the correlation between the 2.6XPC in PCa tissues and control . A total of 497 PCa participants and 52 controls were included for investigating the XPC expression. The Cancer Genome Atlas (TCGA) samples were also employed to assess the effect of XPC expression in PCa based on patients’ Gleason score. Furthermore, we adopt the online String server (http://string‐db.org/) to explore the protein‐protein correlation regarding XPC. Protein Variation Effect Analyzer  was employed to evaluate the mutation of the XPC rs2228001 A/C variant in human (http://provean.jcvi.org/seq_submit.php). Gene‐gene interaction of XPC was also investigated by TCGA samples .Online gene expression database was applied to further investigate the expression of 33.1XPC rs2228001 A/C polymorphism were retrieved in our analysis. Finally, 5305 PCa patients and 6,499 control subjects were included in the present study. Moreover, we checked the minor allele frequencies (MAF) of XPC reported in the genome aggregation database : for global population, 0.367; Europeans, 0.391; Asians, 0.356; Americans, 0.294; Africans, 0.270; Ashkenazi Jewish, 0.472; and others, 0.396. Therefore, in the subgroup analysis by race, a total of seven studies were based on Asian populations, three studies were based on European populations, two analyzed African descendants, and the remaining was on Arabians. In the subgroup analysis by the source of control, there were six hospital‐based studies, and the rest seven studies focused on population‐based controls. The classic genotyping method, PCR‐restriction fragment length polymorphism (RFLP), was conducted in seven of the studies.As described in Table 3.2Pheterogeneity = 0.058, P = .708; heterozygous contrast, OR = 0.95, 95% CI = 0.87 ‐ 1.03, P‐value for heterogeneity = 0.994, P = .194; dominant genetic model, OR = 0.96, 95% CI = 0.89 ‐ 1.04, P‐value for heterogeneity = 0.837, P = .343; recessive model, OR = 1.14, 95% CI = 0.93 ‐ 1.40, Pheterogeneity = 0.001, P = .212). In a stratified analysis by ethnicity, a considerable increased risk was observed in Asian populations . Additionally, no positive association was identified in African individuals . Moreover, in the subgroup analysis according to the source of control, no positive association of this XPC polymorphism was found in population‐based studies .When all the studies pooled together Table , no posi3.3XPC in 497 primary tumors and 52 normal tissues. XPC expression was lower in PCa tissues than in the control . In order to investigate whether the rs2228001 A/C variant could have an impact on the expression of XPC, we adopted the Protein Variation Effect Analyzer  to predict the mutation of XPC. Sensitivity and specificity at different PROVEAN score cutoffs are shown in Figure XPC rs2228001 A/C variant is 1.667, which indicates that this variant is neutral , RBM9 , and BRPF1 (bromodomain and PHD finger containing 1) gene are the top three related genes. Results from TCGA samples indicated a significant correlation between XPC and AKAP10 in prostate cancer .XPC rs2228001 A/C polymorphism confers the risk of PCa, but with controversial results.XPC rs2228001 A/C polymorphism might be a risk factor for PCa.XPC rs2228001 A/C variant and PCa susceptibility.et al indicated elevated colorectal, lung, and bladder cancer susceptibility correlated with this polymorphism.The pathogenesis of PCa remains complex. Previous research showed that genetic variants of XPC rs2228001 A/C variant in PCa susceptibility. When all studies pooled together, no positive result was observed . However, we found that the XPC rs2228001 A/C variant is associated with PCa risk in Asian populations . Our finding is in line with the conclusions reported by He et alXPC in different grade of PCa. It showed evidence that XPC expression was down‐regulated in all Gleason scores of prostate cancer. We also evaluated whether the XPC expression influenced the overall survival probability of PCa cases; however, no positive correlation was indicated.In this study, 5305 cases and 6,499 control subjects were finally included to evaluate the effect of the XPC rs2228001 A/C polymorphism and these factors. Finally, other factors including gene‐gene and gene‐environment interactions are warranted to be considered. As shown in Figure XPC may have the connection of twenty other proteins. Furthermore, TCGA samples have shown that more than 25 genes can participate in the connection of XPC. The AKAP10 gene is the most related gene. There is a significant correlation between XPC and AKAP10 in prostate cancer. However, there is a few research on the further mechanism of this gene, which is warranted to be evaluated in the future studies. Said et al found that XPC rs2228001 A/C variant was not correlated with PCa risk individually; however, combined analysis of rs2228001 A/C and XPC‐PAT variants showed that XPC (A/C + PAT D/D) genotypes were associated with susceptibility of PCa.XPC rs2228001 A/C polymorphism and PCa risk. The statistical power of the current analysis has been strengthened considerably. Second, no evidence of publication bias was identified in both Begg's funnel plot and Egger's test, indicating that conclusions of our study were stable and trustworthy.It is necessary to mention the limitations of the current analysis. First, the sample size of included studies in the current study was relatively small, especially for subgroup analyses. Second, some covariates such as age, tumor stage and grade, and smoking exposure should be added into stratification analysis. However, raw data of the included studies were not available to further evaluate the association between the XPC rs2228001 A/C variant might contribute to elevated PCa risk in Asian patients. The expression of XPC was down‐regulated in PCa with different Gleason scores. In future, more large‐scale and well‐designed studies are warranted to confirm our conclusions in more detail.In conclusion, our study suggested that the The authors declare no competing interests.Not applicable.


Materials and Methods. We searched the PubMed, Web of Science, Embase, ScienceDirect, and Chinese National Knowledge Infrastructure for relevant studies up to December 2019. Pooled odd ratios (ORs) with 95% confidence intervals (CIs) were used to estimate the effect exposure to famine on MetS using a random-effects model, and the I2 was used to evaluate the heterogeneity.  Emerging studies have explored the association between the famine exposure during early life and the risk of the metabolic syndrome, and the results remain controversial. This meta-analysis was performed to summarize the famine effects on the prevalence of metabolic syndrome (MetS) in adulthood.  The analyses included 39 studies from 10 articles with a total of 81504 participants. Fourteen studies from 10 articles for fetal famine exposure, 20 studies from 7 articles for childhood famine exposure, and 5 studies from 3 articles for adolescence/adult famine exposure were included in this meta-analysis. Compared with a nonexposed group, famine exposure significantly increased the risk of MetS for early life famine exposure , fetal famine exposure , and childhood famine exposure . Subgroup analyses showed that the result was consistent regardless of the study designs, definitions of MetS, and causes of famine, with or without adjustment for age, smoking, drinking, and physical activity.  This meta-analysis suggests that exposure to famine during early life may increase the risk of MetS in adulthood. Metabolic syndrome (MetS) refers to the pathological state that the metabolic abnormalities gathered and mutually connected, such as hypertension, hyperglycemia, elevated triglycerides, low high-density lipoprotein cholesterol, and central obesity, and these metabolic derangements increase the risk of type 2 diabetes mellitus, cardiovascular disease, chronic kidney disease, some cancers, and all-cause mortality among the adult population , 2. ReceStudies have demonstrated that the prevalence of MetS is increasing worldwide. According to the National Health and Nutrition Examination Survey (NHANES) 2003-2012, the prevalence of MetS in the United States had increased from 32.9% in 2003-2004 to 34.7% in 2011-2012 . And theIn recent years, a few studies have been performed to investigate the relationship between famine exposure during early life and the risk of MetS. However, these results are controversial, which may be for the reason of different study designs, races of participants, causes of famine, and diagnostic criteria. Therefore, we conducted this meta-analysis to summarize the effect of famine exposure during early life on MetS.We referred to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines to carry out this meta-analysis.We searched the PubMed, Web of Science, Embase, ScienceDirect, and Chinese National Knowledge Infrastructure up to December 2019 for articles that explored the association between famine exposure during early life and the MetS in adulthood. The keywords were searched as follows: “famine OR starvation OR hunger OR undernutrition OR malnutrition” AND “metabolic syndrome OR MetS.” In addition, we searched the reference lists of retrieved articles manually.Studies were included when the following criteria were met: (1) published as original articles; (2) the exposure of interest was famine; (3) the outcome of interest was MetS; (4) odds ratios (ORs) or relative risks (RRs) or hazard ratios (HRs) with 95% confidence intervals (CIs) were available; and (5) the most recent study was selected if data from the same population had been published more than once.Two authors reviewed titles and abstracts independently, followed by full texts, to assess eligibility for inclusion, and any disagreements were solved by discussion.We extracted following data regarding the characteristics of the studies: name of the first author, year of publication, study design, age range or mean age, definition of MetS, sample size and number of cases, famine duration periods, causes of famine, and covariates adjusted for in each study.The quality of the studies was assessed by the Newcastle-Ottawa Scale (NOS)  on 3 aspI2 statistics and chi-squared test were used to estimate the heterogeneity between the studies. The I2 values of 0, 25, 50, and 75% represent no, low, moderate, and high heterogeneity, respectively [P value of chi‐square statistics < 0.05 represents significant heterogeneity. When I2 > 50% or P value of chi‐square statistics < 0.05, the random-effects model was used; otherwise, the fixed-effects model was used [Statistical analysis was performed using the command meta-analysis in Stata 12. Pooled OR with 95% CI was determined to assess the strength of association between famine exposure and the risk of MetS. The ectively , while twas used , 21. Subwas used . PublicaA total of 1510 articles were retrieved based on the search strategy. 1498 potential articles were included after duplicates were removed, and 12 articles retrieved for more detailed evaluation after titles and abstracts were screened. Finally, 39 studies of 10 articles were included in the present meta-analysis   , with mo's study , the resP values from univariate metaregression with the covariates of study design, gender, exposure type, definition of MetS, causes of famine, adjustment status of age, smoking, drinking, and physical activity were 0.977, 0.318, 0.916, 0.531, 0.865, 0.859, 0.696, 0.676, and 0.871, respectively. The results showed that no covariate contributed a significant impact on between-study heterogeneity.The The results suggested the association between famine exposure and MetS was stable. By omitting one study sequentially, the pooled ORs ranged from 1.22 (95% CI: 1.02-1.46) to 1.29 (95% CI: 1.06-1.57). To further find the potential source of between-study heterogeneity, we also used the leave-one-out method. No study was found to contribute to between-study heterogeneity.P = 0.981), and Egger's test (P = 0.150)  .In recent decades, there has been an ongoing discussion about the relationship between the famine exposure during early life and the risk of MetS in adulthood, which has showed inconclusive results. To the best of our knowledge, this is the first meta-analysis exploring the relationship between famine exposure and the risk of MetS in adulthood. Current results combined ORs of 39 studies from 10 articles suggested that famine exposure was associated with an increased risk of MetS. Furtherly, the relationship remained consistent in subgroup analyses conducted by study design, definition of MetS, causes of famine, adjustment status for age, smoking, drinking, and physical activity. Thus, this meta-analysis may represent the best available evidence on the consistency and strength of the association between famine exposure during early life and the risk of MetS in adulthood. We think this finding is important for it provides a new approach for prevention of MetS in adulthood.Subgroup analysis conducted by gender suggested that there was not a significant increase in MetS in men. Reasons might be male fetuses' and infants' susceptivity to adverse environmental conditions , which cSubgroup analysis conducted by exposure type suggested that exposure to famine during fetal life and childhood was associated with higher risk of MetS. The following aspects may partially explain it. Firstly, catch-up growth may compensate it when undernutrition emerges during early life development. Interventional studies using animal models have reported that adaptive responses for stabilizing conceptus growth and enhancing postnatal fitness are related to undernutrition of preimplantational embryos, leading to postnatal metabolic disease . Catch-uA few studies have compared different diagnosis criteria for MetS applied in different populations –49. StudHowever, 1 article included in our research suggested that the CDS definition is superior to the other definitions for determining the association between famine exposure and MetS, because the results showed that adolescence/adult famine exposure was significantly associated with MetS risk only for the CDS definitions . But in This meta-analysis has several potential limitations. Firstly, due to lack of available data from original articles, this meta-analysis could not analyze the severity of famine exposure and the risk of MetS. Secondly, most of the included studies were cross-sectional studies, which may suffer from bias and low comparability unavoidably. Thirdly, only published studies were included in this meta-analysis, so publication bias may have occurred despite no publication bias was identified from funnel plots, Begg's test, or Egger's test.In conclusion, this meta-analysis indicates that famine exposure during early life is associated with an increased risk of MetS in adulthood. The result suggests that maternal nutritional state during gestation periods and children's nutritional state should be given particular attention. Interventions are needed to prevent undernutrition during early life for reducing the prevalence of MetS. Future research studies, especially well-designed cohort studies, are needed to confirm the conclusion.


To quantitatively evaluate associations between exposure to triclosan during pregnancy and maternal thyroid hormone levels.The databases of PubMed, Embase, Web of Science and Cochrane Library were systematically searched to identify relevant studies on the relationship between prenatal exposure to triclosan and maternal levels of serum thyroid hormone published before October 22, 2019. Stata 12.0 was used to examine the heterogeneity among the eligible studies.P = 0.00) or TSH levels . Although the results were statistically insignificant, with the increase of urine TCS concentration, maternal FT4 levels exhibited a tendency to increase while TSH levels had a tendency to decrease during pregnancy.Seven studies involving a total of 4,136 participants were included. Overall, descriptive analysis provided no indication that exposure to TCS during pregnancy was related to either maternal FT4 levels (ES = 0.01, 95% CI: −0.03 to 0.05, The results indicated that exposure to triclosan during pregnancy has no significant influence on maternal levels of thyroid hormone. On account of the inconsistency of existing research designs and study locations, further studies and replication are necessary to confirm these findings. Triclosan (TCS) is one of synthetic antibacterial chemical, which used widely in daily toiletries. About 96% of TCS is disposed of down residential drains . AlthougAs a common environmental endocrine disrupting chemical (EDC), TCS might affect immune responses, ROS production, and cardiovascular functions . What isIn our research, we systematically evaluated the relationship between prenatal exposure to TCS and maternal FT4 as well as TSH, in order to elucidate the association between TCS and maternal thyroid hormone levels and provide epidemiological evidence for reducing the incidence of thyroid disease during pregnancy.In our study, relevant articles were retrieved from PubMed, Embase, Web of Science and Cochrane Library on October 22, 2019 using the following search terms:#1:  or  or (pregnancy) or (pregnant women)#2: (triclosan) or (TCS) or  or (endocrine disrupter)#3: (thyroid hormone levels) or (FT4) or (TSH) or (thyroid dysfunction) or (hypothyroidism) or (hyperthyroidism)#4: #1 AND #2 AND #3Furthermore, all references of relevant studies were tracked back manually to avoid oversights. Therefore, relevant research information is comprehensive.The inclusion criteria for the studies were:Epidemiological studies based on human observation were selected, including descriptive studies, case-control studies, cohort studies and cross-sectional studies.The research objects were pregnant women;Prenatal exposure factor was triclosan;Changes in the level of serum FT4 and TSH were measured as outcomes for study;Data on the association between the risk of TCS exposure and the corresponding 95% CI was provided in the primitive study.The exclusion criteria for the studies were:Not conform to the research topic;Animal studies, conference abstract, lecture literature, editorial materials or comments and so on;Studies had design defects and poor quality;The level of maternal thyroid hormones besides FT4 or TSH was measured;Raw data was unavailable;In light of the inclusion and exclusion criteria, we selected eligible articles by reviewing their titles and abstracts. In addition, the full text was reviewed for further confirmation. Relevant characteristics were extracted from selected original studies including the first author’s name, published year, research design, sample size, research time, area, correction method of TCS concentrations, outcome and 95% CI. Excel was used to record the data.Quality assessment of the eligible literature was made by referring to the Newcastle Ottawa Scale (NOS). An article is judged by NOS on three broad perspectives including the selection of the study subjects, comparability, exposure assessment and outcome . There aData analysis was performed using the software Stata 12.0. We extracted relevant data from eligible articles and recorded them in Excel. Statistical analysis was conducted using the meta-analysis module in Stata 12.0. The adjusted β value presented in the relevant studies was taken as the effect value, which was shown as ES (effect size).Specific steps were as follows: (1) Heterogeneity test: Heterogeneity test was performed and it indicated a great heterogeneity among literatures. Random-effect model was used to calculate the combined effect value . Forest 1 and Q3, so we did not make a complete transformation.At first, 452 studies were included by searching PubMed, Embase, Web of Science and Cochrane Library. After duplicate checking, 310 records were received. Titles and abstracts were reviewed, and 285 records were excluded on account of uncorrelated exposure factors or outcomes. 14 further records were excluded because they were not epidemiological studies. Ultimately, seven articles were included in our meta-analysis after reviewing of full-text articles , 36–38, P = 0.000. As Among them, urinary creatinine was used in three studies for correction. Only one article indicated that exposure to TCS during pregnancy may lead to the increase of maternal FT4 , while o2 = 0.0%, P = 0.609, ES = −0.00 (95% CI: −0.01 to 0.00), P>0.05.Specific gravity was used to correct urinary biomarker concentrations in Aker et al.’s studies and Berger et al.’s study. In the article published by Aker et al. in 2018, they suggested that maternal TCS exposure was associated with an increase of maternal FT4 , howeverThe same seven articles were combined to determine whether prenatal exposure to TCS is associated with maternal TSH levels. Similarly, studies were divided into two groups according to the method of correction.2 = 0.0%, P = 0.461, ES = −0.03 (95% CI: −0.11 to 0.05), P>0.05. The difference was not statistically significant.Urinary creatinine was used to standardize for urinary dilution in three studies. We used random-effect model due to remaining heterogeneity among these three studies. Meta-analysis forest plot was shown in 2 = 17.9%, P = 0.301, ES = 0.54 (95% CI: −0.52 to 1.59), P>0.05. The result indicated that there was no association between TCS and TSH.The remaining articles were corrected using specific gravity. Only one article identified a positive relationship between TCS and TSH . Meta-anIn our study, sensitivity analysis was performed by excluding each individual article one by one. The results did not show evident differences when we removed any other studies, which suggested the credibility of studies included in our meta-analysis Figure 8Our study is the first meta-analysis reviewing the current evidence to investigate whether exposure to TCS during pregnancy can affect maternal thyroid hormone levels. This meta-analysis included seven studies and 4,136 participants. As the performed sensitivity analysis shown, the results were fairly consistent before and after we excluded articles one by one. In our meta-analysis, maternal FT4 levels exhibited a tendency to increase while levels of TSH had a tendency to decrease with higher urine TCS concentration. As evidence shows in Andersen et al.’s study, abnormal maternal thyroid function in early pregnancy was associated with epilepsy, ASD, and ADHD in the child , which wWe performed subgroup analysis to reduce the significant heterogeneity in our study, which can mainly be attributed to differences in calibration methods of urinary TCS concentrations, control of potential confounders, and timing of TCS concentration and thyroid hormone measurements. Above all, the correction methods of TCS concentrations in maternal urine were different among the included articles. Urinary creatinine was used in three studies to standardize for urinary dilution , 31, 33.Significant associations were shown in two articles. In Wang et al.’s study, they suggested a significant association between maternal exposure to TCS and prenatal FT4. It is the only article measuring TCS concentration in urine during the third trimester. Therefore, we hypothesize that pregnant women are more sensitive to TCS in the third trimester, and more measurements during different trimesters should be taken. In addition, this study is the only one which was performed in Asia. As a result, we suggested that different races may have different sensitivity levels to TCS, and more studies on identifying populations sensitive to TCS should be performed by simulating toxicokinetic variability . The artIn animal tests, exposure to TCS during pregnancy resulted in significant FT4 reduction but TSH levels were not obviously changed –27, 41. As the results illustrated, exposure to TCS during pregnancy was not associated with either maternal FT4 or maternal TSH. However, considering the diversity of methods used in different studies and limitations in the quantity of current research, the results should be treated with caution. Therefore, experimental design methods should be optimized, and further studies are needed to investigate the relationship between exposure to TCS during pregnancy and maternal thyroid hormone levels.In our meta-analysis, we concluded that there was no association between exposure to TCS during pregnancy and maternal thyroid hormone levels. Most of the included articles showed insignificant connections, but there were still a few articles that indicated that exposure to TCS during pregnancy may lead to the increase of maternal FT4 and TSH. Consequently, we recommend that larger-scale and more extensive cohort studies should be done to determine the relationship between prenatal exposure to TCS and maternal thyroid hormone levels.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.WL and ZS conceived the study. DC collected and organized the data. JL and WY drafted the manuscript. KF and YX helped refine the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China  and Six talent peaks project in Jiangsu Province (WSW-121).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.