The substantial increasing trend of binge drinking is a global alarm. Our aim was to undertake a systematic review and meta-analysis of cross-sectional studies to explore the association of current smoking with binge drinking among adults.via Q-test and I2 statistic. We assessed publication bias using a funnel plot, the Egger’s, and Begg’s tests.We systematically searched Web of Knowledge; PubMed; Scopus; Embase and Ovid  (from inception to 27 May 2020) databases to identify cross-sectional studies of the association between current smoking and binge drinking. Study screening, data extraction, and methodological quality assessment were all carried out by two independent authors. Adjusted odds ratio (AOR) was pooled with 95% confidence intervals (CI) using random effects model in the meta-analysis, followed by the investigation of the heterogeneity I2 = 90.5%). Subgroup analysis showed that this association among women, men, Caucasians, and Asians/Africans were , , , and , respectively. There was no evidence of publication bias.We identified 3,171 studies and included nine cross-sectional studies with 64,516 participants. A significant association was found between current smoking and binge drinking among both genders (AOR = 2.97; 95% CI = 1.98 to 4.45; Current smoking is associated with binge drinking and can be used for identifying and screening binge drinkers. Moreover, this association is stronger among men, and Asians/Africans. This meta-analysis estimation was limited to English-language studies, and the full text of about 3.5% of reports for retrieval was not found, then generalization of the results should be done with caution. Binge alcohol drinking in adults is a preventable major public health problem , 2. BingTherefore, many scientists have recommended that binge drinking behaviors be screened in adults to minimize harm . UnderstSmoking as an important variable in relation to binge drinking, is examined in different studies. Some cross-sectional studies have shown that in the adult population, current smokers are more likely to report binge drinking than non-smokers. However, the effect size of current smoking on binge drinking is contradictory in previous studies. While some studies have estimated the strength of the association between binge drinking and current smokers to be modest, other studies have estimated a 5–14 times higher chance of binge drinking among current smokers compared to non-smokers in the adult population –13.Although cross-sectional studies may not establish a causal or temporal relationship between current smoking and binge drinking, they are nevertheless important. Despite their shortcomings, cross-sectional studies can prove whether there is an association between current smoking and binge drinking and whether these associations are substantive enough to consider current smoking for screening purposes.Because of the inconsistency in the results of studies related to association of current smoking and binge drinking, we carried out a systematic review and meta-analysis of cross-sectional studies to explore this association among adult population.We followed the Meta-analyses Of Observational Studies in Epidemiology (MOOSE) Checklist for reporting this review. A copy of filled MOOSE checklist is attached in supporting information section .Cross-sectional studies investigating the association between current smoking and binge drinking among adults (18 years and over) were included despite gender, nationality, race, religion, or publication date. Papers published in non-English languages were excluded. Studies that were conducted in specific populations such as pregnant or breastfeeding women, or people with various diseases such as AIDS, metabolic disorders, etc., were also excluded. In addition, studies in which the effect of age was not adjusted were excluded from the study.Binge drinking is defined as “a pattern of drinking that brings a person’s blood alcohol concentration to 0.08 g/dl or above. This typically happens when men consume 5 or more drinks or women consume 4 or more drinks in about 2 h” . All stuThis study is part of a larger systematic review on the relationship between all types of smoking and alcohol consumption. The search strategy was a combination of the selected keyword sets within the titles, abstracts and keywords. All major electronic databases including Web of Knowledge; PubMed; Scopus; Embase and Ovid  were searched from database inception to 27 May 2020. Boolean operators and truncations were different according to the databases. Relevant MeSH and -Emtree terms were included when searching the PubMed and Embase databases, respectively. Details of all searches can be found in the supporting information section .To manage the search results of all databases, protocols for study screening, data extraction and quality assessment were first developed by the research team. All protocols were clear and concise and were refined during the pilot study. A training workshops was held for the research team members and screening of 20 studies was done on a trial basis. During study, meetings with members of the research team were repeated as necessary. All search results of databases were combined using Excel version 2016, and duplicates were deleted. Each of the retrieved studies were screened by two independent reviewers based on the title and abstract and were classified into three groups: related, unrelated and undetectable. Undetectable studies were re-reviewed by a senior reviewer. The full text of all selected studies was searched from databases, and when necessary, from other sources such as searching ResearchGate and emailing corresponding authors. The screened positive studies were assessed based on their full text to figure out eligible cross-sectional studies on the association current smoking and binge drinking. Five reviewers  were involved in finding eligible studies. Any discrepancies between reviewers at each step were resolved by discussion until consensus was reached, otherwise a senior reviewer judged the case.Data extraction was carried out by 8 authors  using a previously piloted excel sheet. The following key data were extracted: first author’s name, publication year, country, participant characteristics , sample size, type, and method of smoking and drinking measurement, smoking and alcohol definitions, and adjusted odds ratio (AOR) with 95% confidence interval (CI).The methodological quality of the included studies was explored by two independent authors. Five authors  did the quality assessment using the Newcastle-Ottawa Scale adapted for cross-sectional studies . This scQ-test (I2 statistic (Adjusted measures of effect were extracted from each study. Effect measures were extracted as adjusted odds ratios (AOR), with 95% confidence intervals (CI). Random-effects meta-analysis and the inverse variance weighting method were adopted to estimate the pooled measures of effect across studies. Heterogeneity was investigated using Q-test  and I2 statistic . Sensititatistic , and Begtatistic  tests, aThe systematic search of electronic databases retrieved 190,040 references until 27 May 2020, and after removing duplicate references, 56,718 studies remained. After reviewing the titles and abstracts, 53,547 studies that were not related to the association of smoking and alcohol drinking were excluded. For the 3,171 remained studies, full texts were reviewed and 2,692 studies were excluded for the following reasons: 2,243 studies were not related to the association between smoking and drinking, 205 studies were not in English, 123 studies did not report the effect size, and 120 studies’ full texts were not found. In general, 480 studies related to smoking and alcohol drinking were identified. Of these, 365 studies were excluded for the following reasons: in 220 studies smoking was outcome, in 127 studies, study population aged less than 18 years, and 18 studies were focused on patients  or individuals with specific conditions like pregnancy or breastfeeding.Among the remaining 115 studies, studies related to current smoking and binge drinking were selected, and 106 studies  among studies addressing association between current smoking and binge drinking. The result of the subgroup analysis of gender found that gender explains to some extent the high level of heterogeneity [Female: 3.68  vs. ] . Heterogeneity was assessed using the  73.1%)] .I2 = 47.4%), while it was 3.93  among Asians and Africans. So, nationality is another characteristic that could explain heterogeneity  and Begg’s test (P = 0.457) were statistically non-significant.The risk of bias assessment of the studies listed in In this systematic review and meta-analysis of cross-sectional studies, the association between current smoking and binge drinking among adults was significant with a pooled AOR of 2.97 (95% CI = 1.98 to 4.45). To the best of our knowledge, our study is one of the first attempts to provide a summary estimate of the effects size of the association between current smoking and binge drinking.The strong association between current smoking and binge drinking suggests that these behaviors may have common cause or that the use of a substance affects the use or initiation of another substance. This is particularly important in the old adults, as binge drinking in elderly is more easily missed in actual clinical practice than in other groups . AlthougIn limited previous studies, relationships between some sociodemographic factors such as age, gender, education and income with binge drinking have been observed –26. AlthI2 statistic, 73.1%, showed that the pooled AOR observed between current smoking and binge drinking was more stable in men. But the large heterogeneity in AOR reported in women, due to the study conducted in Hong Kong with AOR:12.30, may indicate the role of ethnicity or genetic in this stark difference. This is also evident in subgroup analysis based on nationality.Our results indicated a strong association between current smoking and binge alcohol in both genders. Female current smokers were approximately 4 times more, and male current smokers were about 3 times more odds of binge drink than non-smokers. Binge drinking is nearly twice as common among men than women . The resAs presented in the results, we found a strong positive association between current smoking and binge drinking among Asian or Africans. The effect size of the association in Asian or African nationalities was 3.93, while it was 1.36 among the Caucasian population. The Asian subgroup included people from Hong Kong, Korea, and Asian immigrants to the United States. The homogeneity of AORs reported in these populations may be related to the ethnic similarity of these individuals.There are many reports of the effect of genes related to subjective response on alcohol drinking . ResearcThere are limitations in this study that may be the source of biases and should be considered in the interpretation of the results and addressed in future systematic reviews. First, this systematic review and meta-analysis study focused on English-language studies and 205 studies published in other languages were excluded. Second, despite extensive efforts by the research team to access the full text of studies, emailing authors and searching ResearchGate, 120 studies remained without full text. It is important to note that the broad search strategy was to examine the overall association of smoking and drinking, not the current smoking and binge drinking, which is fully described in the Section “2. Materials and methods.” Third, gray literature, which are important sources to minimize the risk of omitting related sources, was not included in this study. Notwithstanding these shortcomings, in this study, an extensive search strategy was used on the important bibliography databases  and medical research platform Ovid  to find all relevant published studies.This systematic review and meta-analysis measured the association between current smoking and binge drinking. We found that current smokers are almost three folds more likely to report binge drinking than who never smoke. Subgroup analysis showed that the association was more than three and a half times greater among female current smokers and nearly fourfold among Asian/African current smokers. Therefore, it seems that current smoking can play an important role in identifying and screening binge drinkers.The original contributions presented in this study are included in the article/SM and LM presented the idea of this study, developed the search strategies, and performed a meta-analysis. LM, ZA, MG, HK, EJ, NG, FG, SS, MS, and VM performed data screening, data extraction, and critical appraisal of studies. LM drafted the manuscript. All authors discussed the results and contributed to the final manuscript.


Colorectal cancer in adults 50 years old and younger is increasing in incidence worldwide. Diet may be a modifiable risk factor. The objective of this study was to examine evidence regarding the association between diet and the risk of developing early-onset colorectal cancer (EOCRC) and early-onset colorectal adenomas in young adults.PUBMED, Web of Science, and Embase were systematically searched for studies examining dietary intake as a risk factor for EOCRC and early-onset colorectal adenomas. Results were synthesized narratively due to the heterogeneity of the studies.Of the 415 studies identified, ten met the inclusion criteria. Of these ten studies, four provided data on dietary risk factors for early-onset colorectal adenomas and six provided data on dietary risk factors for EOCRC. The four studies that measured colorectal adenoma occurrence reported an increased incidence with high sugar sweetened beverage intake, a higher pro-inflammatory diet, a higher Western diet score and higher sulfur microbial diet score. A protective effect against early-onset colorectal adenomas was observed in those who had a higher Prudent diet score or higher adherence to other health dietary approaches . Those who consumed large amounts of deep-fried foods, refined foods, followed a high fat diet, consumed large amounts of sugary drinks and desserts, and had low folate and fiber consumption had a significantly higher occurrence of EOCRC. A protective effect against EOCRC was observed for those who consumed more fruits and vegetables, high amounts of micronutrients and those who adhered to a vegetarian diet.The results of this study reveal various dietary habits may be risk factors or protective against early-onset colorectal cancer and adenomas. Future research should focus on large prospective cohort studies with long-term follow-up to confirm published results and further examine whether differences in diet quality are associated with EOCRC risk. Colorectal cancer (CRC) is the 2nd leading cause of cancer deaths and 3rd most commonly diagnosed cancer globally . By 2030EOCRC occurs most often in the distal colon and rectum . EOCRC iOver 50% of CRC cases diagnosed after age 55 are attributable to modifiable risk factors . Known rIt is pertinent to understand the driving factors behind the increase of EOCRC cases, as it typically presents at a more advanced stage, with a greater risk of metastasis and less favorable prognosis . IdentifThe methodology follows the PRISMA  guidelines. Databases searched include PubMed and Web of Science. The databases were searched using the following key words: risk, early-onset colorectal cancer, diet, young-onset colorectal cancer, risk factors. “And” and “or” were used to combine the keywords listed and to minimize search duplications. There were no language restrictions on the searches. A backwards search was also conducted, i.e., references of accessed studies were evaluated for relevant studies that may have been missed through the database search. A gray literature search of Google was performed. Finally, the Embase database was searched for any articles missed from the above searches. No new articles were found in Embase. Searches were conducted between August 2021 and September 2021.The primary outcome of this review was the examination of dietary habits that may be risk factors or preventative factors for developing early-onset colorectal cancer and adenomas.The population, interventions, comparators, outcomes and study designs (PICOS) scheme was used for assessing eligibility . One revPotential sources were first screened by title and study type to match inclusion criteria. Sources that appeared to match inclusion criteria were then accessed and abstracts were screened. Full-text versions of any remaining articles fitting the inclusion criteria were accessed and assessed.One reviewer (K.C.) collected data from the included reports. All relevant data was compiled into a study characteristics table  and indeRelevant data included any measures that assessed EOCRC and early-onset adenoma risk with specific foods, dietary habits or specified diets. Additionally, data on alcoholic beverages alone was excluded; however, two studies included alcoholic beverages in their diet score , and therefore were not excluded. Data on BMI, weight and obesity levels were not included in this review. Data regarding participant recruitment methods, participant demographics and dietary assessment methods was assessed.p-values (when available) for exposure categories of all dietary factors assessed were extracted. Odds ratios that were adjusted for multi-variables such as age, sex or other risk factors of CRC were the preferred forms of data extracted. All of the extracted data was stored in an electronic table.The effect estimates such as odds ratios (OR) and hazard ratios (HR), 95% confidence intervals (CI) and As a result of the significant heterogeneity of the included studies with regard to study design, outcome measures and nutrition assessments, a quantitative synthesis was not possible.In total, 413 studies were identified using the keyword searches. All articles were found on PubMed. Web of Science did not provide any additional articles not already found on PubMed. Two additional studies were identified through backwards searching. After removing duplicates and articles excluded by study type, 301 articles remained for screening. Of these studies, 188 were excluded based on their abstract. From these studies, 113 were assessed for eligibility based on the inclusion and exclusion criteria previously described. One hundred and three of these studies were excluded for lacking inclusion criteria (no dietary assessment). Ultimately, ten articles were included in the final analysis .Of the ten studies included, five were prospective cohort studies –24 and fp = 0.044). Higher total fructose intake  during adolescence was associated with an increased risk of high-risk adenomas . No significant relationship was observed for artificially sweetened beverages or fruit juice during adolescence and adenoma risk, nor sugar and sugar sweetened beverages during adulthood. The positive associations with sugar intake and adenoma risk were stronger in women who had low fruit intake (<1.3 servings/day) during adolescence than women with high fruit intake. The second study compared dietary patterns of those under 50 years old to those over 50 years old with metachronous colorectal adenomas, defined as sequential adenomas that develop more than 6 months after the initial adenoma, to identify if any foods were significantly associated with a higher risk (p = 0.03), total fat (p < 0.00), monounsaturated fat (p = 0.001), polyunsaturated fat (p = 0.049), red meat (p = 0.001) and consume a more pro-inflammatory diet than those over 50 years old (p < 0.001). However, a multivariate logistic regression model stratified by age group showed no effect that a high red meat consumption (>511 g/week) was associated with risk of developing metachronous colorectal adenomas for those under 50 years old   .Two prospective cohort studies examined the relationship between diet quality and adenoma risk , 22, andp = 0.02)   had an increased risk of early-onset adenomas  . Adenomactively) .p < 0.001; OR = 0.68, CI = 0.49–0.94, p = 0.02; OR = 0.38, CI = 0.26–0.58, p < 0.001; OR = 0.59, CI = 0.40–0.86, p = 0.006, respectively) , as well as lower fiber consumption    and a trend toward higher risk was observed in a multivariable model   . Howeverctively) . Archamb = 0.08) .p = 0.01; OR = 3.9, CI = 1.4–10.7, p = 0.008, respectively)  (p = 0.07) (p = 0.54) in a study with only female participants (p = 0.006)  (p < 0.001) (Four studies explored how different dietary patterns were associated with EOCRC risk –29. In actively) . Greater28–4.04) . Consump = 0.07) . Two stuicipants . Two stu= 0.002) . A great< 0.001) ; however< 0.001) , 27, 29.p = 0.047) (p = 0.017)  . AdditioCurrently, there is extensive evidence pointing to an association between certain dietary factors and risk for developing older-onset colorectal cancer. However, there is much less known about the modifiable risk factors for developing early-onset colorectal cancer. As such, it has been difficult to identify groups of people at risk for EOCRC based on modifiable risk factors, such as dietary patterns, and flag them for early screening or other preventative actions. Unlike other published systematic reviews, this systematic review focused solely on diet as a risk factor for developing or preventing early-onset colorectal cancer and colorectal adenomas.Approximately 85% of early-onset colorectal cancer cases develop through the conventional adenoma-carcinoma sequence . TherefoOne study investigated how a diet which promotes sulfur-metabolizing bacteria influences early-onset adenoma risk. It was found that a high sulfur microbial diet score significantly increased the risk of developing a colorectal adenoma before age 50 . A higheRed meat and processed meat are well documented risk factors for colorectal cancer  due to tIt has been well established in Westernized countries but also globally over the past several decades that dietary patterns in younger generations are shifting toward more unhealthy diets, such as a Western diet . Diets aIn line with the findings that poor diet quality is a risk factor for EOCRC are studies reporting that a high-fat diet was associated with an increased risk for EOCRC , and comHealthy diets, as indicated by recommendation based dietary indices, have been shown to be associated with a lower risk of traditional CRC . AdherenIt is important to note alcohol consumption was considered when scoring both the sulfur microbial diet and the alternative Mediterranean diet , 22. ThiOther micronutrients shown to lower the risk for EOCRC include beta-carotene, vitamin, C, vitamin E and folate . A seconMany of the studies examined colorectal cancer and adenoma by subsite. The subdivisions of the colorectal area have different blood supplies, patterns of motility and physiological function . It has Listed in Of the ten included studies, four exclusively included women –22, 24, The strengths of this systematic review include reporting according to the PRISMA guidelines. Several limitations exist as well. While this review provides a summary of the most current evidence regarding diet and early-onset colorectal cancer, there were a limited number of studies included, and a meta-analysis could not be conducted due to the heterogeneity of the studies. A lack of dietary assessment of patients with EOCRC is a limitation of the published research. The age range of included participants is a limitation of this review. Currently, there is no clear or widely accepted consensus for a definition of age groups for EOCRC . This stThe rising incidence in early-onset colorectal cancer cases makes identifying risk factors imperative. More detailed studies on the differences in dietary index and CRC risk by anatomic sites in young adults are needed. Large prospective cohort studies with long follow-ups are needed to confirm results and to help screen for strategies that can be targeted at this sub-population. Elucidating modifiable risk factors for early-onset colorectal cancer, such as diet, is necessary to help slow the rising incidence and preserve life years for the population.This review demonstrated that various dietary habits, some of which are already confirmed risk factors for traditional colorectal cancer, may be risk factors or protective against early-onset colorectal cancer and adenomas. These results should be interpreted with caution, as a meta-analysis was not able to be conducted and the generalizability of the results is limited to the populations studied. The lack of knowledge on EOCRC risk factors make the associations identified in this review helpful starting points for dietary habits to be examined in future studies. By identifying modifiable risk factors for EOCRC, such as the dietary choices analyzed in this review, high-risk populations can be targeted for early intervention and prevention methods.The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.MG conceived of the work, contributed to the writing, and offered critical comments. KC performed data analysis and wrote the first draft of the manuscript. AF, MH, and EL provided critical revisions to the content. All authors contributed to the article and approved the submitted version.This material is based upon work that was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch/Multistate project Accession ALA044-1-18037 to MG. Research reported in this publication was supported by the National Center for Advancing Translational Research of the National Institutes of Health under award number UL1TR003096 to MG and EL.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Several 9p21.3 variants, such as rs1333049, rs4977574, rs10757274, rs10757278, and rs10811661, identified from recent genome-wide association studies (GWASs) are reported to be associated with coronary artery disease (CAD) susceptibility but independent of dyslipidemia. This study investigated whether these 9p21.3 variants influenced lipid profiles.By searching the PubMed and Cochrane databases, 101,099 individuals were included in the analysis. The consistent finding for the rs1333049 C allele on lipid profiles increased the triglyceride (TG) levels. Moreover, the rs4977574 G allele and the rs10757274 G allele, respectively, increased low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) levels. However, the rs10811661 C allele largely reduced LDL-C levels. Subgroup analyses indicated that the effects of the rs1333049 C allele, rs4977574 G allele, and rs10757274 G allele on lipid profiles were stronger in Whites compared with Asians. In contrast, the effect of the rs10811661 C allele on lipid profiles was stronger in Asians compared with Whites.The rs1333049 C allele, rs4977574 G allele, and rs10757274 G allele of lncRNA, and the rs10811661 G allele of CDKN2A/2B had a significant influence on lipid levels, which may help the understanding of the underlying mechanisms between 9p21.3 variants and CAD. The variant (mutation) of the 9p21.3 allele is prevalent in the general population at a rate of 50% . One copThe 9p21.3 allele contains a long non-coding RNA  and two protein-encoding genes (CDKN2A and CDKN2B). rs1333049, a genetic variant in lncRNA, is formed by a nucleotide substitution from guanine (G) to cytosine (C). In addition, rs4977574, rs10757274, and rs10757278, genetic variants in lncRNA, are formed by a nucleotide substitution from adenine (A) to guanine (G). Moreover, rs10811661, a genetic variant in CDKN2A/2B, is formed by a nucleotide substitution from thymine (T) to cytosine (C).A series of basic studies tested the effects of gene expression levels of lncRNA and CDKN2A/2B on lipid profiles, but the results were inconsistent. For instance, the knockdown of lncRNA inhibits lipid uptake and accumulation and promotes macrophage reverse cholesterol transport (mRCT) , while tIt has been well documented that rs1333049 C allele , rs10757Due to diverse constraints, most independent or single clinical trials are imperfect or flawed. For instance, the sample size is too small, the gender is not balanced, the coverage of the age group is too narrow, or it is impossible to obtain richer and more accurate experimental results due to the limitations of the examining technology or experimental condition –29. SincIn the past few decades, circulating TG levels have been widely reported to be associated with the occurrence, progress, and prognosis of CAD. For instance, a meta-analysis of the Asia-Pacific region indicated that TG was an independent predictor of CAD . This isHere, we systematically analyzed the effects of the rs1333049 C allele, rs4977574 G allele, rs10757274 G allele, rs10757278 G allele, and rs10811661 C allele in 9p21.3 on lipid profiles in 101,099 individuals by a meta-analysis.The present meta-analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) .A comprehensive search of the literature was executed from January 5, 2021 to February 15, 2022, by using the PubMed and Cochrane databases. The following keywords were used in the search: , , and .The inclusion criteria were as follows: (1) Articles that detected the effect of the rs1333049 C allele, rs4977574 G allele, rs10757274 G allele, rs10757278 G allele, or rs10811661 C allele on lipid profiles; (2) articles that provided at least one of the four parameters in lipid profiles ; (3) articles that provided genotype frequencies of variants of rs1333049, rs4977574, rs10757274, rs10757278, and rs1081166; (4) articles that offered mean lipid levels with standard deviation (SD) or standard errors (SE) by the genotypes; (5) the interventional studies that provided pre-intervention data; and (6) the language of eligible studies restricted to English and Chinese. The exclusion criteria were as follows: (1) articles not related to rs1333049, rs4977574, rs10757274, rs10757278, and rs10811661; (2) articles in which human subjects used lipid-lowering drugs; (3) articles that did not present genotype counts; (4) studies that provided invalid data; (5) pedigree articles; (6) overlapping articles; and (7) abstract, review, case report, meta-analysis, and animal articles.Subgroup analysis was conducted on ethnicity/race and disease status. Ethnicity/race includes White, Asian, and other ethnicities. Disease status includes CAD, type 2 diabetes mellitus (T2DM), and healthy subjects. In some studies, the subjects were divided into more than one subpopulation . Each subpopulation was regarded as an independent comparison in this study.Since data extraction and analysis, heterogeneity processing, sensitivity analysis, the risk bias test, and the publication bias test were adopted from previous methods, to avoid redundant descriptions, previous publication by Liu et al.  providesBy searching the PubMed and Cochrane databases, 4,307 articles were identified. After the screening, 4,131 articles were excluded by their title and abstract. Next, 55 articles were further estimated by their contents, of which 5 articles provided lipid data by the genotypes of rs1333049 , 40, rs4Characteristics of the included studies are presented in All the results stated below were statistically analyzed from the included studies that eliminated heterogeneity . However, the overall results showed a low risk of bias (75–90%) among the included studies . ConsequIn the present study, Begg’s test did not find any publication bias. This was confirmed by Egger’s regression test (as seen in In sharp contrast to previous GWAS studies –4, our sThe precise mechanisms underlying the effect of these five 9p21.3 variants on lipid profiles have not been clarified yet. However, several putative regulatory pathways could be proposed to interpret its mechanisms.  and in mIn the present study, the C allele of rs1333049 showed a statistical influence on TG and TC levels in patients with CAD , indicatThe G allele of rs10757274 was identified as a risk allele for CAD in the McPherson et al. , 69, andHowever, we did not observe the effects of the rs10757278 G allele on lipid profiles . Since tStrikingly, the C allele of rs10811661 substantially reduced the LDL-C and TC levels in Asians , indicatAccording to the JDSC study , TG was To the best of our knowledge, this is the first reliable evidence that demonstrates that the rs1333049 C allele, rs4977574 G allele, rs10757274 G allele, and rs10811661 C allele in 9p21.3 had a statistical influence on lipid profiles. Several strengths of the present study should be noted. For instance, the clinical lipid data of 101,099 individuals were included in the analysis, which increased the reliability of synthetic results due to high statistical power. Moreover, data analyses were performed after eliminating the studies with heterogeneity, which further advanced the preciseness of conclusions drawn in our study. Most importantly, our findings may help the understanding of the underlying mechanisms between variants of rs1333049, rs4977574, rs10757274, and rs10811661 in 9p21.3 and CAD. However, a large number of genes as well as some environmental factors are involved in dyslipidemia. Our study has not investigated the interaction of the 9p21.3 variant with other variant locus or environmental factors on lipid profiles due to the lack of original data from the included studies.The rs1333049 C allele, rs4977574 G allele, rs10757274 G allele of lncRNA and the rs10811661 G allele of CDKN2A/2B had a significant influence on lipid levels, which may help the understanding of the underlying mechanisms between 9p21.3 variants and CAD.The original contributions presented in this study are included in the article/ZL, BW, and YL conceived and designed this study as well as drafted the manuscript. HL and YP carried out the searches and collected the data. ZL performed the statistical analyses. All authors reviewed and approved the final manuscript.


Periodontal disease (PD) is a chronic inflammatory disease that leads to alveolar bone resorption and tooth loss. Many studies have reported the association between periodontal disease and various cancers including oral cancer, lung cancer, breast cancer and so on. However, there is still no specialized meta-analysis that assesses the association between periodontal disease and cancer incidence and mortality in-deepth. Thus, we conducted this meta-analysis.This meta-analysis was registered with PROSPERO: CRD42020183497. We searched five online databases for observational studies about the association between periodontal disease and breast, prostate, lung and bronchial, colorectal, and total cancers by July 2020. Then we evaluated quality of the included studies by the Newcastle-Ottawa scale. Risk ratios (HRs) and their 95% confidence intervals (CIs) were pooled to evaluate the strength of the association between periodontal disease and four cancers, total cancer incidence and mortality. In addition, we analyzed heterogeneity by subgroup analysis and sensitivity analysis. Finally, we inspected publication bias by Begg’s and Egger’s tests.I2 = 75.8%, P = 0.000), but also connected with total cancer mortality . Subgroup analyses showed that study population, study design, dental status, follow-up period, adjustment for smoking partially explained the heterogeneity between studies. The results of Begg’s test and Egger’s test were consistent and indicated that there is no publication bias in this study.None of the studies included in this meta-analysis were of poor quality. PD is not only related to breast cancer incidence (HR = 1.26,95%CI [1.11–1.43], In conclusion, this meta-analysis revealed a positive relationship between periodontal disease and breast cancer incidence and total cancer mortality. Further well-designed studies with specific inclusion and exclusion criteria are required to strengthen the conclusion of this meta-analysis. However, longer follow-up period, multi-center trials and even multinational studies are required to corroborate the results. Periodontal disease is a chronic inflammatory disease that eventually leads to tooth loss. The initial factor associated with periodontal disease is dental plaque, which attacks the first immune defense line of periodontal tissue, leading to inflammation and disease. Periodontitis has a range of clinical manifestations, including gingiva bleeding, periodontal pocket, alveolar bone resorption, and tooth loss. Periodontitis is the major cause of tooth loss in adults. According to a National Health and Nutrition Examination survey, approximately 42% of American adults aged 30 years or older had periodontitis, with 7.8% having severe periodontitis . In TurkPeriodontitis is not only related to the abovementioned diseases but also to cancers. In recent years, an increasing number of studies have revealed the relationship between periodontal disease and various cancers, particularly head and neck , esophagCancer is not only difficult to overcome but also a heavy economic burden. In China , lung caIn this context, we aimed to assess the correlations, in terms of incidence and mortality, between periodontal disease and cancers, including breast, prostate, lung and bronchial, colorectal, and total cancers, as well as the strength of these correlations. Furthermore, we aimed to preliminarily explore the factors that influence these correlations.http://www.crd.york.ac.uk/PROSPERO) before the research was begun (CRD 42020183497).This meta-analysis was reported according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. The protocol was registered in PROSPERO (The following criteria were applied: (1) studies published in English or Chinese; (2) studies on human subjects; (3) observational studies (including cohort and case-control studies)with a prospective or retrospective design; (4) studies with periodontal disease as the exposure and, the incidence or mortality associated with breast or prostate cancer, lung& bronchial or colorectal cancer, or total cancers as the outcome; and (5) studies providing relative risks (RRs), hazard ratios (HRs), or odds ratios (ORs) and corresponding 95% confidence intervals (CIs).Databases: PubMed, Embase, Web of Science, China National Knowledge Infrastructure [CNKI] and Wanfang.Search terms: (<Neoplasm= OR <Carcinoma= OR <cancer= OR <tumor= OR <tumour=) and .Time: by to July 2020.via a discussion or by consulting a third author (Zuomin Wang).First, two authors (Kaili Wang and Zheng Zhang) independently retrieved studies from the databases using specific search terms. Subsequently, a hand search was performed by reading abstracts and key words, and studies that were eligible for the inclusion criteria were selected. Finally, a consensus regarding the final studies to be included was reached Kaili Wang sorted out the information for the subsequent classification of the included studies: first author, publication date, country/region, study design type, numbers of samples, age range of the study population, diagnostic criteria for periodontal disease and cancer, cancer type and outcomes, follow-up period, whether adjustments were performed for smoking, adjusted variables, and multiple adjusted HRs and corresponding 95% CIs. Next, Zheng Zhang checked the information and supplemented it if necessary.We evaluated the quality of the included studies using the Newcastle-Ottawa scale. This evaluation system includes three aspects: selection, comparability and exposure. In the selection part, we evaluated the following four aspects: whether the exposed cohort could basically represent the average of the community population, whether the non-exposed cohort was from the same source as the exposure cohort, whether the selection of the exposed cohort was reliable based on records, and whether no outcome events occurred in the study subjects before the study began. In the comparability part, we assessed whether the exposed and non-exposed cohorts were matched in terms of age and other confounding factors. In the exposure part, we assessed the following three aspects: whether there were reliable data or records, such as examination or medical records, for the evaluation of outcome events; whether the follow-up period was equal to or longer than 5 years; and the completeness of follow-up through factors, such as the loss to follow-up rate.Based on the scores, the studies were defined as follows: <4 points, low quality; 4–6 points, moderate quality; and 7–9 points, high quality.First, the included studies were classified according to the study scope: breast, prostate, lung & bronchial, colon & Rectum, and total cancers. Next, according to the specific content and purpose of the studies, we divided them based on two aspects: cancer occurrence and cancer mortality. Of course, som studies involved both incidence and mortality.Q test  and I2 test (I 2 ≥ 50% indicated significant heterogeneity) and was represented using a forest plot.We used the HR with the 95% CI to assess the association between periodontal disease and the risk of cancer incidence and mortality. The data extracted from the studies were analyzed using STATA software . Heterogeneity was tested through the Subgroup analyses were conducted to explore the factors influencing heterogeneity. Subgroup analyses were stratified by study population, study design, dental status, follow-up period, and whether or not smoking was adjusted for. A sensitivity analysis was performed to test the stability of the results.P-value of > 0.05 was considered to indicate no publication bias..Begg’s and Egger’s tests were used for assessing publication bias. Begg’s test, also known as the rank correlation test, tests the correlation between effects and sample size. Egger’s test, also known as the linear regression method, establishes a regression equation based on the standard normal deviate and precision of each included study. The larger the intercept of the regression line, the higher the bias. A n = 13), repeat publication (n = 7), no available data (n = 22), and no full text (n = 3).The process of study selection is shown in I2 = 75.8%, PQ = 0.000). Similarly, we found a modest association between periodontal disease and prostate , lung & bronchus , colon & rectum , and total cancer incidence.The relationship between periodontal disease and cancer incidence is shown in I2 >50% and P < 0.1.Next, we explored the source of heterogeneity through subgroup analyses with As shown in The subgroup analysis results are presented in I2 = 0%, 95% CI [1.05–1.19], P = 0.001). Two studies were retrospective and showed an HR of 1.52 . The pooled HR in four studies in which the periodontal disease diagnosis was self-reported was 1.15 . Six studies with follow-up periods of more than 10 years showed an HR of 1.11. The pooled HR in seven studies in which smoking was adjusted for was 1.13 . The CIs were all on the right side. The results of the subgroup analyses were consistent with those of the full dataset analysis. We can state with certainty that periodontal disease increases the risk of breast cancer incidence.The following were the observations regarding the 11 studies that were conducted on periodontal disease and breast cancer incidence. Four studies were from North America and showed an HR of 1.12 . Six studies with follow-up periods of more than 10 years showed an HR of 1.16 .We found that periodontal disease increased the risk of prostate cancer incidence under certain conditions in the European people, dental examination diagnosis of periodontal disease, follow-up period of less than 10 years. However, the association was not affected by smoking.The following were the observations in the seven studies on periodontal disease and prostate cancer incidence. Three studies were from North America and showed an HR of 1.03 , and eight studies in which periodontal disease was diagnosed through dental examination showed an HR of 1.33 . Similar to prostrate cancer, we found that periodontal disease increased the risk of lung & bronchus cancer incidence under certain conditions in the North American population, self-reported diagnosis of periodontal disease , follow-up period of more than 10 years, and adjustments for smoking, but the association was not affected by study design type.Among the 14 studies on periodontal disease and lung and bronchial cancer incidence, eight studies were from North America and showed an HR of 1.34 , and five studies in which periodontal disease was diagnosed by dental examination showed an HR of 1.17 . We found that periodontal disease increased the risk of colorectal cancer incidence under certain conditions in retrospective study, self-reported diagnosis of periodontal disease , follow-up period of less than 10 years, adjustments for smoking, but the association was not affected by study design type.Among the 13 studies on periodontal disease and colorectal cancer incidence, seven studies were from North America and showed an HR of 1.08 , and eight studies with adjustments for smoking showed an HR of 1.13 . We concluded that periodontal disease increased the risk of total cancer incidence under certain conditions in the North American and European population, prospective study design, but the association was not affected by the diagnostic method for periodontal disease, follow-up period, adjustment for smoking.Among the 12 studies on periodontal disease and total cancers incidence, three studies were from Asia and showed an HR of 1.09 , indicating that the result is reliable. Although the results of current meta-analysis suggest that periodontal disease may increase the risk of breast , prostate , lung & bronchus, colon & rectum  cancer mortality, the overall estimate was not significant because of high levels of uncertainty or moderate heterogeneity. However, we did not perform a subgroup analysis because there were only two studies.We also analyzed the relationship between periodontal disease and cancer mortality . A relatP values of the test results after a continuity correction based on Kendall’s score in the remaining studies ranged from 0.133−1.000. All the P values were greater than 0.05, indicating that there was no publication bias. We also conducted Egger’s test in the case of missing items, the P values of the results of assessing whether the intercept of the remaining items was ranged from 0.147−0.860. All the P values were greater than 0.05, indicating no publication bias. The results of Begg’s and Egger’s tests were consistent, indicating that there is no publication bias in this meta-analysis.Finally, we performed Begg’s and Egger’s tests to evaluate publication bias. The results of the two tests are shown in So far, there are a few relevant meta-analyses assessing the association between periodontal disease and breast , prostatI2 = 17.6%, P = 0.30). This result is consistent with ours. I2 = 5.8%, P = 0.001); however, the results of the subgroup analysis showed that some of the 95% CIs fell on both sides. After 18 years of follow-up, I2 = 8.7%). Two studies , but the results of the subgroup analysis showed that some of the 95% CIs fell on both sides.On reviewing the 27 studies included in this meta-analysis, we preliminarily found that compared with healthy individuals, patients with periodontal disease were 1.14 times more susceptible to breast cancer, 1.26 times more susceptible to prostate cancers, 1.3 times more susceptible to lung and bronchial cancers, and 1.18 times more susceptible to colorectal cancer. Through a meta-analysis of eight studies,  studies  also obtI2 = 29.8%, P < 0.001), which is consistent with our result.This meta-analysis also concluded that there is a clear correlation between periodontal disease and total cancer mortality. Patients with periodontal disease have a 1.4 times higher risk of dying from total cancer than those without periodontal disease. I2 = 14.4%). Among the eight studies included in Tingting’s meta-analysis (I2 = 7.0%). Fourth, among the studies we included, the diagnosis of periodontal disease was self-reported in nine. In many of the previous studies, the diagnosis of periodontal disease was based on self-reported patient data or administrative data. Although this approach may sound unreliable, it can save time. In addition, the manpower and financial resources required for a periodontal examination can be saved. Moreover, self-reported diagnosis of periodontal disease has been proven to be acceptable, with a diagnostic OR of 1.4 (95% CI [0.9–2.2]) for the question on bleeding gums and of 11.7 (95% CI [4.1–33.4]) for the question on tooth mobility, it was also found to be suitable in large-scale epidemiological studies , this is consistent with our conclusion, and the values are close to ours. In a prospective study by P = 0.0267) was significantly higher than ours.Smoking is a risk factor of many diseases. A previous study has confirmed that smoking is an independent risk factor for periodontal and respiratory diseases, including lung cancer . TherefoThere are several limitations in this meta-analysis. First, although most confounding factors were adjusted for in the included studies, few studies adjusted for other oral health problems and stress, which may affect the results of these studies. Second, genetic factors play a very important role in the occurrence of cancer. While diagnosing the patients’ condition, few researchers noted whether they had family history of cancer, therefore, this important influencing factor was most likely ignored in the data analysis, which would also affect the final results.This meta-analysis revealed that periodontal disease is significantly associated with the risk of the incidence of breast cancer and that periodontal disease may increase the risk of total cancer mortality. Our results prompt the general public to pay attention to periodontal health and to receive periodontal treatment in a regular and timely manner. In conclusion, our results suggest that patients with periodontal disease should pay special attention to breast cancer screening during regular general health examinations. Apart from breast ultrasound, a mammography examination conducted once every 1–2 years would be helpful for the early detection and early treatment of breast cancer. Of course, attention should also be paid to other related cancers, such as lung, colorectal, and prostate cancers. However, well-designed studies, populations from diverse geographic regions, and adjustments for exact confounding factors are needed to confirm our findings and to further explore the relationship between periodontal disease and cancers incidence and mortality.10.7717/peerj.14320/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.14320/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.14320/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.14320/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.14320/supp-5Supplemental Information 5Click here for additional data file.


A consensus has not been made about the predictive value of blood vitamin D level in patients with coronary artery disease (CAD). This meta-analysis aimed to assess the association between blood 25-hydroxyvitamin D level and adverse outcomes in patients with CAD.post-hoc analysis randomized trials evaluating the value of 25-hydroxyvitamin D level in predicting cardiovascular or all-cause mortality, and major adverse cardiovascular events  were included.Two independent authors searched the articles indexed in PubMed and Embase databases until June 28, 2022. Cohort studies or The literature search identified 13 eligible studies for our analysis, including 17,892 patients with CAD. Meta-analysis showed that the pooled adjusted risk ratio (RR) was 1.60  for all-cause mortality, 1.48 (95% CI 1.28–1.71) for cardiovascular mortality, and 1.33 (95% CI 1.18–1.49) for MACEs. Leave-out one study sensitivity analysis suggested that the predictive values of blood 25-hydroxyvitamin D level were reliable.Low blood 25-hydroxyvitamin D level is possibly an independent predictor of cardiovascular or all-cause mortality and MACEs in patients with CAD. Baseline 25-hydroxyvitamin D level may provide useful information in CAD patients. Coronary artery disease (CAD) is the most common type of heart disease worldwide, which can be manifested as stable ischemic heart disease or acute coronary syndrome (ACS). Despite the improvement in medical therapy and surgical revascularization, CAD remains a major determinant of morbidity and premature death . A more Biomarkers play an important role in risk stratification and management of CAD , 3. VitaNo previous meta-analysis has systematically assessed the predictive association of Vitamin D deficiency with adverse outcomes in patients with CAD. Therefore, the current meta-analysis aimed to evaluate the predictive value of blood 25-hydroxyvitamin D level of patients with CAD in terms of cardiovascular death, all-cause mortality, and cardiovascular events.The current meta-analysis was carried out under the Preferred Reporting Items for Systematic Reviews and Meta-analysis guideline . Two indpost-hoc analysis randomized trials. When multiple articles were obtained from the same population, we selected the publication with the longest follow-up. The exclusion criteria are as follows: (1) studies reported the in-hospital outcomes; (2) studies provided risk summary by continuous 25-hydroxyvitamin D level; and (3) cross-sectional study or meeting abstract.The inclusion criteria are as follows: (1) population: patients were with CAD; (2) exposure: blood 25-hydroxyvitamin D level at baseline; (3) comparison: patients with the bottom vs. reference top 25-hydroxyvitamin D level; (4) outcome measures: cardiovascular or all-cause mortality, and major adverse cardiovascular events ; (5) reported multivariable adjusted risk estimate for the above mentioned outcomes; and (6) study design: retrospective or prospective cohort studies or The following data was abstracted by two authors independently: last name of the first author, publication year, origin of study, study design, subtype of CAD, number of patients, gender distribution, age of patients at enrollment, length of follow-up, cutoff value of vitamin D deficiency, definition of MACEs, endpoints, fully adjusted risk summary, and confounders included in the fully adjusted models. Two authors independently assessed the study quality according to the Newcastle-Ottawa Scale (NOS) for cohort studies (maximum score of 9 points) . StudiesI2 statistic (I2≥ 50% was considered significant). A random effect model was used for data analysis in the presence of statistically significant heterogeneity. A fixed-effect model was used in the absence of significant heterogeneity. To test the credibility of the pooling results, we conducted a leave-out one study sensitivity analysis to recalculate the risk estimates. Subgroup analyses were conducted to investigate the effect of the types of CAD, sample sizes, publication time, and length of follow-up. Begg's test, Egger's test, and funnel plot were used to investigate the publication bias. The certainty of evidence was summarized via the GRADE analysis.All data were analyzed using STATA 12.0 . To evaluate the association between blood 25-hydroxyvitamin D level and adverse outcomes, we poled the most fully adjusted risk ratios (RR) and 95% confidence intervals (CI) with the bottom vs. the reference top category of 25-hydroxyvitamin D level. Heterogeneity between studies was determined using the Cochran's Q statistic (p <0.10 was considered significant) and the A total of 1,114 records were identified from initial electronic database search. After excluding duplicates, 632 records were left. After reading the titles and abstracts, 597 obviously unrelated records were excluded. Thirty-five articles were retrieved for full-text assessment, and 13 studies , 20–23 sThe main features of the included studies are presented in I2 =60.1%; p = 0.007). Leave-out one study sensitivity analysis did not alter the statistical significance of the original risk estimate. In addition, the value of blood 25-hydroxyvitamin D level in predicting all-cause mortality was consistently found in each named subgroup (p = 1.000), Egger's test (p = 0.567), and symmetrical funnel plot . Sensitivity analysis confirmed the robustness of the originally pooling risk estimate. The Begg's test (p = 1.000), Egger's test (p = 0.567), and symmetrical funnel plot  was observed between studies. Leave-out one study sensitivity analysis did not change the originally statistical significance of the pooling risk estimate. No evidence of publication bias was found according to the results of the Begg's test (p = 0.902), Egger's test (p = 0.428), and symmetrical funnel plot  than in all CAD patients (pooled RR 1.64). Considering the lack of sufficient data, whether the predictive role of 25-hydroxyvitamin D level was affected by ACS subtypes was not determined. In addition, the predictive role of 25-hydroxyvitamin D level was weakened with the lengthening of follow-up in the subgroup analysis.Several potential mechanisms may be implicated into the association of vitamin D deficiency with adverse outcomes in patients with CAD. First, low vitamin D can activate the activity of the renin-angiotensin-aldosterone system ; Second,A recent meta-analysis of four randomized clinical trials suggested that vitamin D supplementation is associated with improvements in diastolic blood pressure and parathyroid hormone in patients with CAD having vitamin D deficiency . HoweverSeveral potential limitations should be addressed in this meta-analysis. Firstly, blood 25-hydroxyvitamin D level was only detected once rather than dynamic measurement, possibly causing classification bias. Secondly, the cut-off values of lower 25-hydroxyvitamin D level, which were used for predicting adverse outcomes, varied across studies, thus making it hard for clinicians to identify patients that need supplementation of vitamin D. Thirdly, significant heterogeneity was found for all-cause mortality. The different cut-off values of low 25-hydroxyvitamin D level, types of the CAD, or length of follow-up may contribute to the existing heterogeneity. Fourthly, this meta-analysis did not analyze the predictive role of 25-hydroxyvitamin D level by continuous data analysis because of the lack of sufficient data. Fifth, when a U-shaped association of 25-hydroxyvitamin D level with worse outcomes is observed , 33, theLow 25-hydroxyvitamin D level may be an independent predictor of MACEs, cardiovascular and all-cause mortality in patients with CAD. Baseline 25-hydroxyvitamin D level may provide important prognostic information in CAD patients.The original contributions presented in the study are included in the article/Study conception/design and interpretation of data: YF and XW. Literature search, data extraction, and quality assessment: HZ and PW. Statistical analysis: YJ and YS. Writing the manuscript: HZ. All the authors approved the version of the manuscript.This work is supported by (1) Suqian Science and Technology Support Project Fund (K201907), (2) Jiangsu 333 Talent Fund (BRA2020016), and (3) Zhenjiang Key Research and Development Fund (SH2021038).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Phenolic compounds are the most abundant antioxidants in the human diet. There are about eight thousand types of phenols, but the main classes are flavonoids, phenolic acids, stilbenes, lignans, and other polyphenols. These compounds have anticarcinogenic properties and may exert a protective effect against several cancers, including Gastric Cancer (GC). However, previous studies investigating GC have focused on flavonoids and the results are controversial. Our systematic review with meta-analysis is the first to report the association between total polyphenol intake, as well as the consumption of more than two classes of polyphenols concomitantly, and GC risk. Polyphenol consumption decreased the risk of GC in both sexes, but to a greater extent in females. The risk reduction was greater in studies carried out in Europe and Asia, therefore further studies in the Latin American population are warranted. Considering the high incidence rates of GC worldwide and the fact modifiable risk factors, such as diet, are amenable to intervention, the findings from this systematic review and meta-analysis can help strengthen strategies to encourage the consumption of foods rich in polyphenols and reduce the incidence of GC.2 = 60.5%); while flavonoid intake decreased GC risk by 28% , similar to the reduction fort other classes . Protective effects against GC were observed in both sexes  and for intestinal subtype . By continent, polyphenol consumption reduced GC risk in both Europe  and Asia . Conclusions: Dietary polyphenol intake decreased GC risk. The reduction was greatest in females. Most previous studies were carried out in Europe and Asia. Further studies investigating polyphenol consumption and GC in Latin American populations are warranted.Background: Phenolic compound consumption may have a protective effect against gastric cancer (GC). Most GC studies focus on the flavonoids class, but results are conflicting and knowledge gaps remain for other classes and total polyphenol intake. This study aimed to assess the association between polyphenol intake  and GC. Methods: In this systematic review and meta-analysis, the PubMed, Embase, Scopus, LILACS, Web of Science, and OpenGrey databases were searched for studies published up to 20 March 2022. Case–control and cohort studies analyzing the association between polyphenol intake and GC were included. For the meta-analysis, pooled summary estimates were calculated using a random-effects model, and the estimates extracted adjusted for most variables. Subgroup analyses were performed for subclass , sex, geographical area, study design, anatomical subtype, histological subtype, family history of GC and fruit and/or vegetable intake. The study was registered with PROSPERO (#CRD42022306014). Findings: The search identified 2752 records, of which 19 studies published during the period 1999–2021 including a total of 1,197,857 subjects were eligible. Polyphenol consumption reduced GC risk by 29% (RR = 0.71; 95% CI: 0.62–0.81; I H. pylori. Therefore, the ingestion of polyphenols might be associated with the inhibition of cancers of the digestive tract. Since 1999, studies have suggested that flavonoids exert a protective effect against gastric cancer, but results are inconsistent. There are about 8000 phenols that can be categorized into various classes and subclasses, with flavonoids, phenolic acids, lignans, stilbenes, coumarins, and tannins being the most common. Despite this complexity, most studies have focused on investigating the association of only one of these polyphenol classes (flavonoids), while comprehensive analyses of the effect of total polyphenol intake, as well as its subclasses, on gastric cancer risk are lacking.Polyphenols have anticarcinogenic, anti-inflammatory, and antimicrobial properties and act on cellular proliferation pathways to inhibit the growth of To the best of our knowledge, this systematic review with meta-analysis is the first to report the association between total polyphenol intake, as well as the consumption of more than two classes of polyphenols concomitantly, and gastric cancer risk. We identified inverse associations between dietary polyphenol intake  and gastric cancer. Subgroup analyses by sex, study population, study design, and Lauren histological classification were also performed.Guidelines recommend a high consumption of fruits and vegetables to prevent against cancer. This dietary advice may be related to the presence of polyphenols in these foods, whose ingestion reduces the risk of gastric cancer, regardless of sex. Considering the high incidence rates of gastric cancer worldwide and the fact modifiable risk factors, such as diet, are amenable to intervention, the findings from this systematic review and meta-analysis can help strengthen strategies to encourage the consumption of foods rich in polyphenols and reduce the incidence of gastric cancer.Gastric cancer (GC) ranks fifth in incidence and fourth in lethality among all cancers. Estimates suggest there were over one million new cases in 2020, representing 5.6% of all cancer cases and around 769,000 deaths . Among tPolyphenols have shown specific and nonspecific anticarcinogenic properties and may exert a protective effect against several cancers, including GC . These cPrevious studies investigating GC have focused on specific polyphenol classes ,9,10,11.This systematic review and meta-analysis followed the PRISMA guidelines for the reporting of meta-analyses . The eleTwo authors (MAF and ARCS) independently extracted the following information from all eligible studies: (1) last name of the first author; (2) year of publication; (3) country; (4) study design; (5) period of study; (6) total number of participants, numbers of cases and controls; (7) polyphenol assessment method; (8) food source of polyphenols; (9) classes of polyphenols studied; (10) relative risk (RR)/odds ratio (OR) and 95% confidence interval (CI) indicating the highest versus the lowest categories of dietary polyphenol intake where estimates extracted were adjusted for most variables; (11) intake comparison; and (12) adjustment variables (family history of GC and fruit and/or vegetable intake).The most adjusted OR (highest versus lowest intake of polyphenols) was considered to be an approximation of the RR, and the summary results were reported as RR for simplicity. Random-effects meta-analysis was used to assess the association between dietary polyphenol intake, including the main subclasses (exposure), and GC risk (outcome), with pooled ORs calculated together with their 95% CIs.2 test were used to quantify the heterogeneity of the studies where, for p < 0.05 and/or I2 > 50%, substantial heterogeneity existed among studies [Cochran’s chi-squared test and the I studies ,21. The p < 0.05 was considered a statistically significant difference for all tests used. All statistical analyses were conducted using the software STATA, version 15.0 . This study was registered with PROSPERO (#CRD42022306014).The Newcastle–Ottawa Scale  was usedThe literature search led to the retrieval of 2752 records, of which 637 were excluded as duplicates and a further 2096 excluded after initial screening of titles and abstracts. Two additional articles were later identified in the references of the screened articles ,24. A ton = 2; Italy, n = 1; Greece, n = 1; Sweden, n = 2; Finland, n = 2; and Spain, n = 3), five studies were conducted in Asia , and only 3 studies were conducted in North America . Over half the studies were published after 2010 (n = 12). Twelve studies analyzed the flavonoid class only, whereas two investigated 3 classes of polyphenols. A total of 16 studies used food-frequency questionnaires to measure polyphenol intake. The confounders used by the studies were: age, sex, education, total energy intake, body mass index, physical activity, smoking, alcohol intake, and total fruit and vegetable consumption. All variables for each statistical model are shown in The main characteristics of the included studies are summarized in 2 = 60.5%). The analysis of flavonoid consumption and risk of GC showed that the intake of total flavonoids or some types of flavonoids had an inverse association with GC  (2 = 72.0%). Other data combinations were also made to assess the effects of sex  and anatomical subtype (cardia or noncardia), and the meta-analysis showed a significant inverse association between polyphenol intake and GC risk (p = 0.316).The pooled RRs with 95%CIs (highest versus lowest categories of dietary polyphenol intake) were calculated to assess the association between dietary polyphenol intake and risk of GC. As shown in = 64.3%) . Likewis GC risk . Heterog GC risk , and Egg2 = 31.6%; female, RR = 0.65; 95% CI: 0.48–0.87, 7 studies, P for heterogeneity = 0.064, I2 = 49.7%) and intestinal histological type . When the analysis was stratified by geographical area, an inverse association between polyphenol intake and GC was observed in both Europe  and Asia . Regardless of whether the studies were adjusted for a family history of GC or fruit/vegetable intake, the protective effect of polyphenol intake against GC was observed (On subgroup analyses, the protective effects of polyphenol intake against GC were observed in both sexes (male, RR = 0.79; 95% CI: 0.67–0.94, 8 studies, P for heterogeneity = 0.176, Iobserved .This systematic review and meta-analysis showed an inverse association between polyphenol consumption and GC, for the intake of total polyphenols and of the main classes, including flavonoids, lignans, phenolic acids, stilbenes, and other polyphenols. Previous studies report conflicting results regarding the relationship between polyphenol intake and GC risk. Multicenter case–control studies carried out in Europe and the USA have found that individuals who consume greater amounts of polyphenols have a lower risk of developing GC ,5,15,31.On the current subgroup analysis by geographic location, an inverse association between polyphenol intake and GC was identified in Europe and Asia but not in North America. The results of other meta-analyses also indicate an association in European populations only ,33, wherH. pylori [Flavonoids are the most-studied polyphenol class included in systematic reviews and meta-analysis studies ,37,38,39. pylori ,41,42. F. pylori ,44.In the present study, subgroup analysis by study design was also conducted, revealing lower GC risk in case–control studies but not for cohort studies. Bo et al.  and You The analysis of the association between polyphenol intake and GC risk by sex revealed a significant risk reduction for both men and women. This finding differs from the results observed by other meta-analyses, in which either no association was found for males and females  or an inHowever, no association was found between polyphenol intake and reduced risk of noncardia gastric adenocarcinoma or gastric cardia adenocarcinoma. These findings are similar to the results of Yang et al. . In contThe subgroup analyses also revealed an association between polyphenol intake and GC risk, irrespective of adjustments for family history of cancer or fruit and vegetable intake. Polyphenols are considered mediators of the protective effects of vegetables and fruit against various forms of cancer and chronic diseases. However, as these foods contain other compounds, it is important to identify which compound mediates the preventive potential of fruit and vegetables. To this end, some studies have used fruit and vegetable intake in statistical models to assess whether the association between polyphenol intake and GC remains significant ,10,15. GThe present study has several strengths. First, a large sample drawing on a satisfactory number of studies was analyzed. A total of 19 studies were included, allowing a subgroup analyses to be carried out. Limitations of the meta-analysis included that some studies stratified results by sex and anatomical localization, while most investigations on the topic addressed only one class or subclass of polyphenols, hampering comparison with other studies.In conclusions, the current study provided evidence for an inverse association between dietary polyphenol intake and GC risk, for total polyphenol intake as well as for various polyphenol classes, in a representative sample. Polyphenol consumption decreased the risk of GC in both sexes, but to a greater extent in females. Moreover, the risk reduction was greater in studies carried out in Europe and Asia. Further studies investigating the association of polyphenol consumption with GC in the Latin American population are warranted.


In meta‐analyses, it is critical to assess the extent to which publication bias might have compromised the results. Classical methods based on the funnel plot, including Egger's test and Trim‐and‐Fill, have become the de facto default methods to do so, with a large majority of recent meta‐analyses in top medical journals (85%) assessing for publication bias exclusively using these methods. However, these classical funnel plot methods have important limitations when used as the sole means of assessing publication bias: they essentially assume that the publication process favors large point estimates for small studies and does not affect the largest studies, and they can perform poorly when effects are heterogeneous. In light of these limitations, we recommend that meta‐analyses routinely apply other publication bias methods in addition to or instead of classical funnel plot methods. To this end, we describe how to use and interpret selection models. These methods make the often more realistic assumption that publication bias favors “statistically significant” results, and the methods also directly accommodate effect heterogeneity. Selection models have been established for decades in the statistics literature and are supported by user‐friendly software, yet remain rarely reported in many disciplines. We use a previously published meta‐analysis to demonstrate that selection models can yield insights that extend beyond those provided by funnel plot methods, suggesting the importance of establishing more comprehensive reporting practices for publication bias assessment. The funnel plot is among the most popular tools to assess evidence for the presence of publication bias and the sensitivity of results to publication bias , reviewing the meta‐analyses reverse‐chronologically from 2019 back to 2017. (More details about the methodology and results of the review are available in the Supporting Information.) Among these meta‐analyses, 55% did not assess publication bias at all. Of the 45% that did assess publication bias, 85% did so using classical methods based on the funnel plot, such as visual inspection of funnel plots, Egger's regression, or Trim‐and‐Fill. The remaining 15% used methods such as the fail‐safe N  is in fact a strong influence and likely stronger than selection for point estimate size  with estimated heterogeneity τ^=0.15  and I2 = 76% .The differing assumptions of funnel plots versus selection models are not merely a point of statistical pedantry but rather can lead the methods to provide differing insights when applied to published meta‐analyses. For example, Toosi et al.  meta‐ana[CI]: 0.0, 0.12, pR code to conduct this analysis this can be found in code excerpt (χ2(2)=11.82,p=0.003. Accordingly, the estimated mean after adjusting for publication bias is smaller and has a larger p‐value, r=0.04 . As noted above, these differing results could occur if, for example, there is little correlation between studies' estimates and standard errors (as detected by Egger's regression), yet there is an apparent overrepresentation of “significant” studies in either direction (as detected by the selection model). This example illustrates that using selection models to accommodate a more realistic mechanism of publication bias  and effect heterogeneity can result in different insights from those provided by funnel plot methods.We reanalyze the data with a simple selection model that assumes that “significant” studies, regardless of effect direction, are more likely to be published than “nonsignificant” studies. The  excerpt , which w5weightr includes a function to fit a selection model as follows  and (2)  to allow for the possibility of selection for both positive and negative “significant” results. If too few studies fall into one of the three categories , the function will issue a warning, in which case we would recommend then fitting the simpler model (1) after coding point estimates' signs such that the hypothesized effect direction is positive.weightfunct reports the results of a standard random‐effects meta‐analysis without correction for publication bias, followed by analogous estimates after adjustment for publication bias. For example, for the meta‐analysis on interracial dyads, we used the R code in code excerpt . This p‐value corresponds to a test of the pooled estimate versus an effect size of 0 in the model adjusted for publication bias. The function also estimates “weights” for each interval of p‐values defined by the cutoffs. For the meta‐analysis on interracial dyads, for example, the estimated weight for the interval 0.025<p+<0.975 is 0.19. Because one‐tailed p‐values in this interval correspond to two‐tailed p‐values greater than 0.05 and with estimates in either direction, this estimated weight indicates that “nonsignificant” two‐tailed p‐values are estimated to be only 19% as likely to be published compared to “significant” two‐tailed p‐values with point estimates in the expected positive direction. For the interval 0.975<p+<1 , the estimated weight is 1.05, indicating that studies that are “significant” but with point estimates in the unexpected negative direction are approximately as likely to be published as studies that are “significant” and positive. However, this estimate has considerable uncertainty because only six studies were “significant” and negative. Finally, the function provides a likelihood ratio test assessing for the presence of publication bias. We would suggest that meta‐analysts characterize the presence of publication bias in terms of the p‐value of this test and the severity of publication bias (assuming it is present) in terms of the estimated weights themselves, as we illustrate above. Other software packages are available for fitting similar selection models  or, inversely, fail to detect publication bias when it does exist (Type II error) , but as we have discussed, empirical evidence suggests that the assumed model of publication bias often holds well in practice. Also, selection models perform best in large meta‐analyses and might fail to converge or provide imprecise estimates if there are few studies in one or more of the p‐value intervals  consider the results of selection models, as one reasonable alternative. These more comprehensive reporting practices would considerably improve our understanding of publication bias in meta‐analyses. We have provided concrete guidance on how to fit and interpret selection models using existing user‐friendly software, and we demonstrated that they can provide additional insights beyond those provided by funnel plot methods alone. In doing so, we hope to open the door to more widespread adoption.This study was supported by NIH grant R01 LM013866 and R01 CA222147; the NIH‐funded Biostatistics, Epidemiology and Research Design (BERD) Shared Resource of Stanford University's Clinical and Translational Education and Research (UL1TR003142); the Biostatistics Shared Resource (BSR) of the NIH‐funded Stanford Cancer Institute (P30CA124435); and the Quantitative Sciences Unit through the Stanford Diabetes Research Center (P30DK116074).https://osf.io/37y9f/.All data and code required to reproduce the applied examples is publicly available:


Background: The relationship of TP53 codons 72, IVS3 16 bp, and IVS6+62A > G polymorphisms with breast cancer (BC) risk has been analyzed in seventeen published meta-analyses. However, the credibility of statistically significant associations was ignored and many new studies have been reported on these themes.Objectives: To explore whether TP53 codons 72, IVS3 16 bp, and IVS6+62A > G polymorphisms are associated with BC risk and the clinical phenomena.Methods: To comprehensively search the data , we provided a clear search strategy and reviewed the references of published meta-analyses. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were used.Results: The current meta-analysis had a larger sample size than the previous ones: 99 studies with 43,951 BC and 48,479 controls for TP53 codon 72 polymorphism, 35 studies with 8,705 BC and 7,516 controls for IVS3 16 bp polymorphism, and 25 studies with 12,222 BC and 12,895 controls for IVS6+62A > G polymorphism. Five gene models were used to explore the association between the three polymorphisms and BC risk, and partial positive results were similar to published meta-analyses results. However, a large number of significant results were considered to be unreliable after correcting with Bayesian false-discovery probability (BFDP), except for the association between TP53 IVS3 16 bp polymorphism and BC risk in overall analysis (GG vs. CC: BFDP = 0.738), matched studies , and tumor size below 2 cm . These unreliable results were confirmed again without new solid results emerging in further sensitivity analysis .Conclusion: After considering the quality of the included studies and the reliability of the results, the present meta-analysis suggested that TP53 codons 72, IVS3 16 bp, and IVS6+62A > G polymorphisms were not significantly associated with the BC risk. Those results which prove that these three polymorphisms increase BC risk are more likely to be false-positive results due to various confounding factors. Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) are currently recognized as biomarkers affecting treatment decisions in BC patients  of the World Health Organization, the number of new cases of BC in the world has surpassed lung cancer as the most commonly diagnosed cancer with 2.26 million  , IVS3 16 bp (rs17878362), and IVS6+62A > G (rs1625895) for this study. Codon 72 polymorphism is the variant encoding a proline rather than an arginine residue  of tumor-suppressor gene ty of BC , explori residue , IVS3 16 residue , and IVS residue . Althoug residue  have beeAll processes for the current systematic review and meta-analysis were based on the PRISMA guidelines.TP53,” “polymorphism, genetic,” “breast,” “arg72pro,” “IVS3 16 bp,” “IVS6+62A>G.” The full search strategy was available in TP53-specific databases were also used: the International Agency for Research on Cancer TP53 database (http://www-p53.iarc.fr/) and the p53 website (http://p53.free.fr/), and the search process for both databases followed the annotated bibliography lists provided by the database itself. There were no language restrictions for eligible studies here. Meanwhile, additional studies were screened out from the references of published reviews and meta-analyses. All qualified studies were determined by reading the title, abstract, and full text of the literature. In addition, if necessary, we contacted the corresponding authors for more information by e-mail. All searches were updated to October 25, 2021.We conducted a systematic literature search using PubMed, China National Knowledge Infrastructure (CNKI), and Wanfang Database. Combinations of the following keywords and their synonyms were used: “database  (http:// website  (http://TP53 codon 72 (rs1042522), IVS3 16 bp (rs17878362), or IVS6+62A > G (rs1625895) polymorphisms and BC risk; 4) studies population were female.Studies were included if only they met the following criteria: 1) case-control, nested case-control, or cohort studies; 2) genotype frequency or odds ratios (ORs) and 95% confidence intervals (CIs) were available; 3) studies discussed the association between In the case of multiple overlapping research populations, we only included the latest study with the largest sample in the present analysis, and excluded data from other overlapping reports. Overlapping characteristics of study populations were determined by comparing authors, study centers, demographic characteristics, and recruitment periods. We did not consider the studies that the population was a mix of men and women. And studies with significant heterogeneity, such as cases and controls that were not in the same continent, were excluded. Eventually, editorials, narrative reviews, or other manuscripts that do not report major research findings were excluded.TP53 genotyping material of case (tumor tissue or other DNA sources), type of controls, whether cases and controls were matched (case-control studies), whether genotyping was done blindly and/or quality controlled, whether the association between genotypes and BC was assessed with appropriate statistics and adjustment for confounders, and genotype distribution.Based on the inclusion and exclusion criteria listed above, the two authors (Zhao and Yin) independently screened the abstracts and full texts and carefully extracted information from all the eligible studies searched. The following data were collected from each study: first author, year of publication, sample country, geographic region and ethnicity, sample size, source of controls, source of cases, with what technique to ascertain cancers and controls, source of p-value was less than 0.05  following the han 0.05 . The higTP53 codon 72, IVS3 16 bp and IVS6+62A > G polymorphisms, and the susceptibility of BC. We performed ORs with the corresponding 95% CIs following five genetic models: 1) heterozygote model (CG vs. CC), 2) homozygote model (GG vs. CC), 3) dominant model (CG + GG vs. CC), 4) recessive model (GG vs. CC + CG), and 5) allele model (G vs. C). The C allele was the major or wild allele, and the G allele was the rare or mutant allele.Crude ORs and 95% CIs were pooled to evaluate the association between Q-test , and Begg’s funnel plots were symmetrical by visualizing. If a significant publication bias existed, we might use the nonparametric “trim and fill” method to correct and identify funnel plot asymmetry caused by publication bias, and meanwhile estimate the true value of the quantitative synthesis  on IVS3 16 bp polymorphism, and 25 studies  belong to IVS6+62A > G polymorphism. TP53 polymorphisms based on the clinicopathological characteristics of BC, and the cells with red color indicated HWE in violation in these tables.TP53 codon 72 and IVS3 16 bp polymorphisms.According to the evaluation criteria in TP53 codon 72 polymorphism and BC risk did not have a strong link in overall analysis. In subgroup analyses, the quantitative syntheses of HWE-compliant studies  and HWE in violation studies  showed opposite conclusions. In both subgroup analyses of matched studies and subgroup analyses of controls with blood donors or volunteers (BV) source, the results showed increased risk of BC. In the analysis of clinical presentations, the expression of TP53 codon 72 polymorphism was increased in subgroups of tumor grade I, premenopausal status, distant metastases negative, distant metastases positive, while the expression of TP53 codon 72 polymorphism was decreased in the subgroups of PR-negative, tumor stage II, patients younger than 50 years and right localization.The results of pooled analyses and ethnicity distribution are shown in p53 codon 72 polymorphism . In other subgroup analyses  and final sensitivity analyses . The source of heterogeneity was only found in the geographic region of analyses , we founnel plot .TP53 IVS3 16 bp polymorphism and BC risk and the distribution of this polymorphism in different ethnic groups. It is indicated that TP53 IVS3 16 bp polymorphism increased BC risk in overall population , matched studies , and tumor size below 2 cm . No source of heterogeneity was found in the 13 items mentioned above by meta-regression analysis. Then, in sensitivity analyses , an assoTP53 IVS6+62A > G polymorphism and BC risk and the distribution of this polymorphism in different ethnic groups. The quantitative syntheses showed that IVS6 + 62 polymorphism was not associated with BC risk in all analyses, except in controls of BV source subgroup , which the correction results showed BFDP >0.8. In the analysis of relevant clinical features, some significant results emerged, such as ER negative, ER positive, and premenopausal status, but the quality of these pooled studies makes it hard to trust the statistical results of their data. The results of meta-regression analysis showed that the source of heterogeneity did not come from the 13 items (mentioned above), and Egger’s test and Begg’s funnel plot showed no publication bias here , with I2 > 75% in all five genetic models, which indicated that quantitative synthesis mixed with low-quality data would affect the credibility of the final result. In overall analysis, TP53 IVS3 16 bp polymorphism significantly increased BC risk, especially in Caucasians, Indians, and women living in Asia and Europe. Additionally, in stratified analyses of the subgroups, matched studies, neither blinding nor quality control, blinding and/or quality control, HWE-compliant studies, controls of PB source, controls of BV source, and controls of NR source once again proved the association between IVS3 16 bp polymorphism and BC risk. In further sensitivity analysis, IVS3 16 bp polymorphism was again found to be associated with BC risk in the overall analysis as well as Caucasians and women in European subgroups. For TP53 IVS6+62A > G polymorphism, there were no significant results to demonstrate an association between IVS6+62A > G polymorphism and BC risk, except that a significantly increased BC risk was found in controls of BV source subgroup analysis.In total, when analyzing TP53 polymorphisms on the clinical characteristics of BC , matched studies subgroup , and tumor size below 2 cm . However, further correcting the significant results of the sensitivity analysis with BFDP, there was no significant correlation in overall analysis and any subgroup analyses. On account of the limitation of sufficient number of studies, we could not carry out the sensitivity analysis on clinical characteristics and the results should only be interpreted as an indication that is ,the results of TP53 codon 72, IVS3 16 bp and IVS6+62A > G polymorphisms on BC clinical presentations. Hence, there are no reliable results to prove the association between TP53 codon 72, IVS3 16 bp, and IVS6+62A > G polymorphisms and BC risk.Given the vast amount of genomic data currently being generated, Wakefield. (2007) proposed an accurate Bayesian approach to measure false-positive reports in genetic epidemiology studies. Using BFDP for the correction, of all the significant results we found above, only the association between TP53 codon 72, IVS3 16 bp and IVS6+62A > G polymorphisms and BC risk. Published meta-analyses  and IVS3 16 bp , and in 2011 for IVS6+62A > G  with BC risk (Published meta-analyses with largest sample size were performed in 2013 to detect the relationship of  BC risk . The num BC risk  that est BC risk  did not  BC risk  excluded BC risk  checked  BC risk  did not  BC risk . Finally BC risk .TP53 codon 72, IVS3 16 bp and IVS6+62A > G polymorphisms and BC risk. In the current meta-analysis, we used a larger sample size. In addition, we carried out a quality assessment of the relevant studies and considered the epidemiological characteristics of the included studies in this meta-analysis (Therefore, we performed an updated meta-analysis to further explore the association between analysis . MoreoveTP53 codon 72 polymorphism and BC risk in African and only three studies on IVS3 16 bp polymorphism and BC risk in Asian, and there was only one study on IVS6+62A > G polymorphism and BC risk in African and Asian, respectively. In addition, high-quality studies were inadequate for sensitivity analysis of clinical presentations in this study. Third, the rating scales of research characteristics (Although multiple strategies were used to ameliorate the issues of previous studies, there were still some limitations in this study. First, only published articles were browsed, so the omission of some research results may be inevitable. Second, there were less studies involved in some subgroup analyses, for example, there are only two studies for eristics  that wereristics , this raTP53 codon 72, IVS3 16 bp and IVS6+62A > G polymorphisms and BC risk. Other evidence about the increased BC risk associated with these three polymorphisms may most likely be due to false-positive results. Significant associations should be explained with caution and it is crucial that future analyses should be based on the quality of studies to effectively identify the impact of genetic variants on BC risk, particularly for the combined effects, such as gene–body status and gene–environment. The clinical findings presented in this meta-analysis are suggestive simply for the clinic, and more reliable and meaningful conclusions will depend on the development of more high-quality original studies and the statistical analysis for additional data in the future.In summary, there are no robust significant results to confirm the association between


In a population-based cohort study , Dong etP < 0.05 was considered as statistical significance. Data analyses were conducted using Stata/MP (Version 16.0).This meta-analysis was performed on the basis of the statement of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) . We searP =0.02; P =0.63; P =0.06; P < 0.01; P = 0.26; P = 0.08; PEgger ranged from 0.208 to 0.900).After preliminary screening we identified 18 cohort studies –19 whichThis meta-analysis yielded three main findings. First, our meta-analysis confirmed the findings regarding to HF and stroke in Dong et al.' study : SGLT2isTo our knowledge, this is the first meta-analysis which evaluated the comparative effectiveness of SGLT2is vs. GLP-1RAs on several important cardiovascular/cerebrovascular outcomes in T2D patients according to baseline CVD status. Its findings suggest that SGLT2is might be preferred to GLP-1RAs in reducing CVM, ACM and MI in T2D patients with CVD; whereas GLP-1RAs might be preferred to SGLT2is in reducing MACE and MI in those without CVD. After being confirmed by future randomized trials, these findings would help to select between SGLT2is and GLP-1RAs in specific clinical settings. On the contrary, we only compared risk of total stroke between SGLT2is and GLP-1RAs, but failed to compare risks of stroke subtypes, i.e., ischemic stroke and hemorrhagic stroke, due to the limited data. Further studies are needed to address this issue. Moreover, the mechanisms by which the relative effectiveness of SGLT2is vs. GLP-1RAs varies in T2D patients with/without CVD are required to be further investigated.In conclusion, our meta-analysis validated the findings regarding to HF and stroke in Dong et al.' study . MoreoveIn a population-based cohort study , Dong etDesign: LD. Conduct/data collection: PL, HH, and WC. Analysis: PL. Writing manuscript: LD and ZL. All authors approved the manuscript.This work was supported by the Key Laboratory of Neuroimaging, Longhua District, Shenzhen [Shen Long Hua Ke Chuang Ke Ji Zi (2022) No. 7] and Shenzhen Fundamental Research Program , General Program for Fundamental Research (Grant No. JCYJ20210324142404012).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.