There remain controversies over the conclusion of different serum phosphate levels as prognostic predictors of sepsis patients. As such, this study investigated the association between different serum phosphate and the prognosis of sepsis.Data from PubMed, Embase, Cochrane Library, and Web of Science were systematically retrieved from the inception of databases to June 1, 2023 and independently screened and extracted by two authors. Binary variables in the study were estimated as relative risk ratio (RR) and 95% confidence interval (CI), and continuous variables were estimated as mean and standard deviation. The Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of the included studies, and subgroup analysis and sensitivity analysis were performed for all outcomes to explore the sources of heterogeneity.P = 0.000) and prolonged Intensive Care Unit (ICU) length of stay (LOS) . However, there was no significant difference in the in-hospital LOS . A low serum phosphate level was not significantly associated with the all-cause mortality risk , ICU LOS  and in-hospital LOS .Ten studies were included in this study including 38,320 patients with sepsis or septic shock. Against normal serum phosphate levels, a high serum phosphate level was associated with an elevated all-cause mortality risk (RR = 1.46; 95% CI [1.22–1.74]; Sepsis patients with high serum phosphate levels before therapeutic interventions were associated with a significant increase in the all-cause mortality risk, prolonged ICU LOS, and no significant difference in in-hospital LOS. Sepsis patients with low serum phosphate levels before interventions may have a reduced risk of all-cause mortality, shorter ICU LOS, and in-hospital LOS, but the results were not statistically significant. Sepsis is a common yet complex disease with high incidence and has been one of the leading causes of death worldwide . A reporPhosphate, as an essential element in the human body, is conducive to maintaining muscle contraction and cell integrity, delivering nerve stimulation, and keeping normal organ functions. Several studies have shown that phosphate is associated with clinical outcomes of various diseases, including malignancy, cardiovascular, and kidney diseases . Howeverhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=425450.This systematic review and meta-analysis complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement . The stuTwo authors (Sf-W and Yh-L) independently and systematically retrieved data from PubMed, Embase, Cochrane Library, and Web of Science from the inception of database to June 1, 2023. The retrieval terms included Sepsis, Mortality, Phosphate, Hyperphosphatemia, and Hypophosphatemia, and medical subject words and keywords were used for combined retrieval. The detailed retrieval strategy is provided in Studies eligible for inclusion were selected according to the PICOS principles:(1) Patients: Sepsis patients aged ≥18;(2) Exposure: Hyperphosphatemia or hypophosphatemia before sepsis intervention ;(3) Control group: Normal phosphate level before sepsis intervention;(4) Outcome: All-cause mortality, ICU LOS (length of stay), and in-hospital LOS;(5) Study type: Case-control, cohort, or cross-sectional study.Studies meeting any of the following criteria were excluded:(1) No clear report of defined hyperphosphatemia or hypophosphatemia;(2) Animal experiments;(3) Meta-analysis or review, case reports, letters, and meeting abstracts;(4) No prognostic outcomes or sufficient data.All retrieved studies were imported into EndNote, and duplicate publications were removed. Then two authors (Sf-W and Yh-L) screened the remaining studies by title, abstract, and full text. The following data were then extracted independently from the included studies: Author, Year, Country, Design, Sample size, Age, Gender, Adjusted variables, Follow-up, and Outcomes.The authors (Sf-W and Yh-L) independently used the Newcastle-Ottawa Scale (NOS) to assess the quality of the included nonrandomized studies in this meta-analysis . The NOS2 test. If I2 is ≥50% and P-value is <0.1, there is significant heterogeneity, and the random-effects model (REM) would be used. Otherwise, the fixed effects model (FEM) will be used. In the case of large heterogeneity, a subgroup analysis was conducted through the single-factor or multi-factor analysis method to explore the source of heterogeneity. Sensitivity analysis was carried out to explore the stability of the results by eliminating the literature one by one, and the publication bias was assessed for all the outcomes by Egger’s test and Begg’s test. A P-value ≤ 0.05 indicates a statistically significant difference. Stata SE 15.1  was used for the above analyses.Meta-analysis was performed for the outcomes from all included studies. Binary variable outcomes were expressed as Relative Risk (RR) with 95% confidence interval (CI), and the continuous variables were expressed by mean and standard deviation. The heterogeneity among studies was analyzed using the Q test and the IA total of 2,964 articles were retrieved from databases, of which 651 were duplicate publications. A total of 151 were preliminarily eligible by title and abstract. After a full-text review of the 151 studies, 141 were excluded. Finally, 10 studies  were incA total of 38,320 patients with sepsis or septic shock were involved in the included studies, with a minimum sample size of 197 and a maximum sample size of 11,658. The main characteristics of these patients are summarized in P = 0.000). Heterogeneity analysis showed I2 = 87.3% and P = 0.000. Therefore, the random effects model (REM) was adopted.Seven studies  reportedP = 0.003), multiple factor subgroup analysis results were . More details are shown in In order to explore potential sources of heterogeneity, a subgroup analysis was performed according to whether the data outcomes were derived from single or multiple factors, and it was found that high serum phosphate levels were associated with a higher mortality risk across all groups. The single factor subgroup analysis results were  (P = 0.588) . One study with a significant impact on the effect size of the outcome was eliminated from the combined analysis . Before = 0.001) . It was = 0.588) . It was P = 0.000)  . HeterogP = 0.001). Heterogeneity analysis showed I2 = 95.4% and P = 0.000. Therefore, the REM was adopted.Six included studies  reportedP = 0.394). Heterogeneity analysis showed I2 = 98.2% and P = 0.000. Therefore, the REM was adopted.Of the same six studies, 5,869 patients with low serum phosphate levels were involved in the comparison of ICU LOS between the low serum phosphate level group and the normal serum phosphate level group. The meta-analysis  showed tP = 0.609), without significant difference. Heterogeneity analysis showed I2 = 97.7% and P = 0.000. Therefore, the REM was adopted.Six studies  reportedP = 0.274). Heterogeneity analysis showed that I2 was 98.8% and the P-value was 0.000. Therefore, the REM was adopted.The same six studies reported in-hospital LOS between patients with low phosphate levels and patients with normal phosphate levels. The meta-analysis  showed tP-value in Begg’s test and Egger’s test was 0.548 and 0.199 , 1.000 and 0.239 , and 1.000 and 0.892 (Per-increased group) respectively. For ICU LOS, the P-value in Begg’s test and Egger’s test was 1.000 and 0.781 , and 1.000 and 0.921  respectively. In terms of in-hospital LOS, the P-value in Begg’s test and Egger’s test was 0.452 and 0.725 , and 1.000 and 0.821  respectively. These results and relevant tables and figures are shown in A sensitivity analysis was performed for all the outcomes above separately to investigate the stability of the outcomes by eliminating the literature one by one. In terms of the outcome of all-cause mortality between patients with low serum phosphate levels and normal serum phosphate levels, it was found that the study by This meta-analysis included ten studies involving nearly 40,000 patients with different serum phosphate levels. The current study is the first-ever systematic review and meta-analysis to investigate the impact of different phosphate levels on clinical prognosis outcomes of sepsis. Our final study evidence showed that patients with hyperphosphatemia before intervention were significantly associated with an increased risk of all-cause mortality and prolonged ICU LOS compared to patients with normal serum phosphate levels, while patients with hypophosphatemia before intervention were not significantly associated with an increased risk of mortality and prolonged LOS.vs normal phosphate level group showed that sepsis patients with high serum phosphate levels before intervention were positively correlated with an increased risk of all-cause mortality and prolonged ICU hospitalization, and possibly associated with prolonged in-hospital LOS with no statistically significant difference. In order to further verify this observation result, the studies using mortality of sepsis patients with the serum phosphate level as the continuous variable were included in the analysis of all-cause mortality, and it was found that elevated serum phosphate levels were associated with a higher mortality risk in sepsis patients. The findings were consistent with the results reported in a previous meta-analysis study on the relationship between high serum phosphate levels and all-cause mortality and ICU LOS in critically ill patients (The meta-analysis results from the hyperphosphatemia patients . HoweverIn our study, the mortality of sepsis patients with high serum phosphate levels was 34.6%. On the one hand, the high mortality may be associated with the fact that the sepsis patients enrolled had a mean age above 60 at baseline and were complicated with a previous history of long-term chronic diseases, because older patients were more closely associated with a high incidence of cardiovascular diseases and significantly decrease in somatic function , with poOur study showed that low phosphate levels were not associated with sepsis mortality and were possibly associated with shortened ICU LOS and in-hospital LOS, but the results were not statistically significant. However, previous studies have reported that low phosphate levels are associated with the prognosis of sepsis patients . DiffereSeveral important limitations need to be considered in this meta-analysis. First of all, this review was limited by the inclusion of retrospective observational cohort studies, in which there may be unmeasurable confounding factors and recalling bias . HoweverIn conclusion, compared to sepsis patients with normal serum phosphate levels, sepsis patients with high serum phosphate levels had a significantly increased risk of all-cause mortality and prolonged ICU LOS, but there was no significant difference in in-hospital LOS. Sepsis patients with low serum phosphate levels were not associated with the risk of all-cause mortality, ICU LOS, and in-hospital LOS. These findings support early control of serum phosphate levels in patients diagnosed with sepsis complicated with hyperphosphatemia. Due to the small number of included studies and the large proportion of retrospective cohort studies, more high-quality, multicenter, large-sample prospective studies are warranted in the future.10.7717/peerj.16241/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.16241/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.16241/supp-3Supplemental Information 3Click here for additional data file.


Stratified analysis further revealed a significant increase in liver cancer risk for individuals with the C677T when combined with smoking , particularly among Asian smokers . Regarding the A1298C polymorphism, an elevated risk of cancer was observed in mixed populations alone , as well as when combined with smoking . In non-drinkers, C677T polymorphism was found to be associated with esophageal cancer risk  and colon cancer risk , but there was no clear link between this polymorphism and cancer risk among drinkers. The association between the C677T polymorphism and cancer risk among smokers was found to be significant, suggesting that the combination of tobacco and the C677T polymorphism may enhance the carcinogenic process, particularly in liver cancer. However, no similar relationship was observed for the A1298C polymorphism. Interestingly, significantly increased cancer risk was observed in individuals with C677T genetic variants who were nondrinkers, but not among drinkers. These findings highlight the potential role of the C677T polymorphism in modifying cancer risk in specific contexts, such as smoking and alcohol consumption.5,10-methylenetetrahydrofolate reductase (MTHFR) mutations play a significant role in various types of cancers, serving as crucial regulators of folate levels in this process. Several studies have examined the effects of smoking and drinking on MTHFR-related cancers, yielding inconsistent results. Therefore, the objective of this study was to evaluate the magnitude of the effects of gene-smoking or gene-drinking interactions on cancer development. We conducted a comprehensive literature search in PubMed, Web of Science, CNKI, and Wan Fang databases up until May 10th, 2022, to identify relevant articles that met our inclusion criteria. The extracted data from these studies were used to calculate the overall odds ratio (OR) and corresponding 95% confidence interval (95% CI) using either a fixed-effect or random-effect model in Stata version 11.2. Stratified analyses were performed based on ethnicity, control group origin, and cancer classification to assess the risk of cancers associated with gene-smoking or gene-drinking interactions. Sensitivity analyses were conducted to investigate potential sources of heterogeneity, and publication bias was assessed using the Begg’s test and Egger’s test. Additionally, regression analysis was employed to explore the influence of relevant variables on heterogeneity. To evaluate the statistical correlations, analytical methods such as the false-positive report probability and the Bayesian false discovery probability were applied to assess the reliability of the findings. In our meta-analysis, a total of 47 articles were included, comprising 13,701 cases and 21,995 controls for the C677T polymorphism and 5,149 cases and 8,450 controls for the A1298C polymorphism. The results indicated a significant association between C677T polymorphism and cancer risks when combined with smoking (CT + TT vs CC, OR [95% CI] = 1.225 [1.009–1.487],  Nowadays, increasing evidence suggests that cancer development is the result of the combined effect of environmental and genetic factors. Single nucleotide polymorphism (SNP) is the most common and stable genetic variants, and germline sequence variation could be discovered in more than 1% of the general population, which might account for 80% of the whole genome heterogeneity .Folic acid (vitamin B9) is a crucial micronutrient that cannot be synthesized by the body and is found in dark green leafy vegetables and legumes . ThroughMTHFR is one of the most extensively studied genes, playing a crucial role in folate metabolism . MTHFR iTobacco smoke contains a substantial quantity of carcinogens and toxic substances that have the potential to promote the development of cancer and other diseases . These hAlcohol (ethanol) is also considered a carcinogen, and acetaldehyde, a metabolite of ethanol, can induce inflammation in the body, leading to the generation of reactive oxygen species and subsequent downstream effects. Moreover, acetaldehyde exhibits high reactivity with DNA and possesses various carcinogenic and genotoxic properties . Due to MTHFR polymorphisms, numerous studies have been carried out to explore the relationship between MTHFR polymorphisms and cancers. However, the specific interactions between these polymorphisms and smoking or drinking have not been thoroughly evaluated. Therefore, we conducted a comprehensive meta-analysis using the largest available sample size to investigate the impact of MTHFR SNPs on cancers in conjunction with smoking or drinking. To the best of our knowledge, no previous study has systematically examined the association between MTHFR variants, smoking or drinking, and various types of cancers. We anticipate that this meta-analysis will provide valuable insights into the field of cancer prevention.With a further understanding of 22.1The relevant medical literature was retrieved from PubMed, Web of Science, CNKI, and Wan Fang electronic databases using various combinations of search terms, including “smoking,” “tobacco,” “cigarette,” “drinking,” “alcohol,” “C677T,” “A1298C,” “rs1801133,” “1801131,” “MTHFR,” “Methylenetetrahydrofolate reductase,” and “cancer.” The search was conducted until May 10th, 2022. To ensure the inclusion of as many relevant studies as possible, we manually screened the references of other reviews, including meta-analyses. The search process was performed multiple times to ensure that no additional articles were missed. Both Chinese and English articles were considered in our analysis.2.2The selection criteria for eligible studies were as follows: (a) original and case-control studies; (b) examining the relationship between the C677T or A1298C polymorphism and cancer risk; (c) Articles were included in our study if they reported smoking and drinking status categorized as either “never” and “current/ever” or as “nonsmoker/nondrinker” and “smoker/drinker”; (d) providing original data for calculating the crude odds ratio (OR) and 95% confidence interval (CI) among smokers and drinkers; and (e) in cases where multiple articles reported the same primary data by the same author, only the most recent one was considered.MTHFR polymorphisms (C677T and A1298C); (e) The classification of smoking and drinking data did not meet our requirements: For example, if smoking was only classified by pack-years and alcohol consumption was only classified by the amount consumed, and if there was a lack of genetic typing data available for those with smoking or drinking status, then they were not included in the analysis.The articles excluded were based on the following criteria: (a) duplicate and overlapped studies; (b) case-only studies; (c) reviews , as well as meeting abstracts; (d) studies uncorrelated with one of 2.3The raw data were independently extracted from the included studies by two investigators: including the last name of the first author, year of publication, country, ethnicity, cancer types, control group origin, the sample size of genotypes among smokers and drinkers, and genotyping method. The extracted data were then reviewed by other researchers to ensure accuracy. In case of any discrepancies during the data extraction process, all authors discussed and reached a consensus. For subgroup analysis, the ethnicity was generally categorized into three groups: Asian, Caucasian, and Mixed. Control group origin was divided into two groups: hospital-based and population-based. Extractive studies that provided information on smoking or drinking classification  were used to further evaluate the impact of these variables on cancer in relation to the polymorphisms.2.4The association between C677T or A1298C polymorphism and cancer risks among smokers and drinkers was evaluated using crude ORs and 95% CIs. Various models were employed to calculate the overall OR in MTHFR polymorphisms, specifically homozygote comparison , heterozygote comparison , dominant model , and recessive model . Subgroup analyses were conducted to examine the effects of these polymorphisms based on ethnicity, source of control, and cancer types.I2 and chi-square p-value, were utilized, taking into account the variation in sample sizes. If I2 > 50% and chi-square p-value ≤0.05, indicating significant heterogeneity among studies, a random-effects model was used to estimate the combined OR and 95% CI. Otherwise, a fixed-effect model was employed.To assess heterogeneity across studies, two statistical indices, namely p-value below 0.05 was considered statistically significant, and all p-values were two-sided.Meta-regression analyses were conducted to investigate potential sources of heterogeneity that could influence the results, taking into account the year of publication, ethnicity, and control group origin. Sensitivity analyses were carried out to assess the robustness of the findings by systematically removing individual studies and examining their impact on the overall results. Publication bias was assessed using the Begg funnel plot, which plots the standard error against the log (OR), and the Egger regression asymmetry test. All statistical analyses were performed using Stata software (version 11.2). A To assess the credibility of significant associations, we employed the false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) as calculation methods. We set a pre-established threshold of 0.2 for FPRP and considered values below this threshold as noteworthy. Additionally, we used prior probabilities of 0.25, 0.1, 0.01, 0.001, and 0.0001 to determine the association between an odds ratio (OR) of 1.5 and cancer risk. Furthermore, we set a threshold of 0.8 for BFDP, and considered values below this threshold as noteworthy. Prior probabilities of 0.01, 0.001, and 0.00001 were used in the BFDP calculations. Similarly, we set 0.8 as the thresholds of BFDP and took 0.01, 0.001, 0.00001 as the prior probability of BFDP. It is important to note that FPRP values below 0.2 and BFDP values below 0.8 were considered significant and deserving of attention ,19.33.1As depicted in In the final analysis, 36 articles investigated the relationship between C677T polymorphism and cancers among smokers, while 27 articles focused on the relationship between C677T polymorphism and cancers among drinkers. As for the A1298C gene, 19 articles were relevant, with 16 of them exploring the association between A1298C polymorphism and cancers among smokers and 12 articles examining the association between A1298C polymorphism and cancers among drinkers.3.1.1Among the 36 smoking-related literatures, there were 5 studies focused on lung cancer, 6 studies for gastric cancer, 6 studies for esophageal cancer, 3 studies for colorectal cancer, 2 studies for pancreatic cancer, 2 studies for liver cancer, and 2 studies for bladder cancer. The remaining types of cancers, such as breast cancer and thyroid cancer, did not have enough studies for subgroup analysis and were represented by less than one article each. In terms of control group source, 17 studies were hospital-based, and 19 studies were population-based. Regarding ethnicity, 28 studies included Asian population, 4 studies included Caucasian population, and 4 studies included mixed population.Among the 27 alcohol-related literature, there were 4 studies focused on lung cancer, 3 studies on pancreatic cancer, 3 studies on colorectal cancer, 4 studies on gastric cancer, 2 studies on liver cancer, 2 studies on esophageal cancer, 2 studies on colon cancer, and 2 studies on rectal cancer. In terms of control group source, 16 studies were hospital-based and 11 studies were population-based. Regarding ethnicity, 20 studies included Asian population, 2 studies included Caucasian population, and 5 studies included mixed population. 3.1.2Among the 15 smoking-related studies, there were 3 studies focused on lung cancer, 3 studies on colorectal cancer, and 2 studies on bladder cancer. For other types of cancer such as colon cancer, head and neck cancer, and liver cancer, there were fewer than 2 studies conducted for each, thus subgroup analysis was not performed. In terms of control group source, 7 studies were hospital-based and 8 studies were population-based. Regarding ethnicity, 8 studies included Asian population, 4 studies included Caucasian population, and 3 studies included mixed population.For the 13 alcohol-related studies, there were 3 studies on colon cancer, 2 studies on colorectal cancer, 2 studies on rectal cancer, and others. Concerning the control group source, 7 studies were hospital-based and 6 studies were population-based. Regarding ethnicity, 10 studies included Asian population and 2 studies included mixed population. 3.23.2.1I2 = 83.20%, CT + TT vs CC, OR [95% CI] = 1.225 [1.009–1.487], p = 0.041), However, no significant association was observed among non-smokers. In subgroup analyses, Asian smokers were to have that elevated risk of cancer with 1.292-fold in the dominant model, whereas Asian non-smokers were not. No association was observed among Caucasian smokers or non-smokers. Liver cancer risk was elevated among smokers by 1.564-fold, compared to non-smokers. Furthermore, smokers had a 1.564-fold increased risk of liver cancer compared to non-smokers. The risk of esophageal cancer was significantly increased in both smokers and non-smokers. However, no significant difference was found between smokers and non-smokers in terms of the association between the C677T polymorphism and other types of cancer such as lung cancer and gastric cancer. The detailed results are presented in The analysis of the included articles revealed that the C677T polymorphism significantly increased overall cancer susceptibility among smokers in the dominant model , compared with drinkers. Subgroup analyses found that there was no significant difference between drinkers and non-drinkers in Asians, as well as a mixed population. Additionally, non-drinkers had a 1.544-fold increased risk of esophageal cancer and a 1.877-fold increased risk of colon cancer compared to drinkers. The detailed results are presented in The analysis revealed that the overall risk of cancer was higher among non-drinkers in the dominant model . For A1298C polymorphism .Possible publication bias was examined based on the result of the calculation of Begg’s test and Egger’s test. For C677T polymorphism, some results showed publication bias based on Egger’s test values  and reduced levels of folate in their serum compared to those with the CT and CC genotypes . These mMoreover, previous studies have demonstrated that hydrocarbons in tobacco reduce the bioactivity of vitamin B12 and folic acid. Smokers in the National Center for Health Statistics study also had lower levels of red blood cell folate compared to non-smokers . SimilarFurthermore, a significantly elevated risk of carriers harboring the C677T variant was observed in Asian smokers while not in Caucasian smokers, which is consistent with a previous study . This coTherefore, it is possible that the combined effects of tobacco and C677T on cancers disrupt DNA methylation pathways through folic acid metabolism. However, some researchers have found that the cancer-promoting effect of MTHFR polymorphism may not be influenced by smoking ,71.Our study revealed varying combined effects of the C677T polymorphism and smoking on different types of cancer. Interestingly, the role of smoking habits in promoting esophageal cancer risk was similar among both smokers and non-smokers, suggesting that smoking may not be as significant of a factor in esophageal cancer as previously believed. However, it remains an independent factor, as the presence of the C677T polymorphism increased the risk of esophageal cancer in our study, as well as in the meta-analysis conducted by Langevin et al. . ConsistMHTFR variants may be due to ignoring the interaction between folic acid intake and individual MTHFR variants. Adequate folate intake could offset the lower enzymatic activity of MTHFR that may increase the MTHFR and promote DNA synthesis, while the adequate provision of methyl donors could still be ensured [MHTFR polymorphisms and smoking-folic acid associations or drinking-folic acid associations with cancers. In mixed populations, we observed a lower risk of cancer among drinkers with the C677T variant. For the A1298C polymorphism, we only observed a decreased overall cancer risk in the dominant model. In brief, alcohol consumption may act as a protective factor for cancer incidence in individuals with MTHFR variants. The protective effect appears to be organ-specific and race-specific for the C677T polymorphism, particularly under conditions of adequate folate levels.Alcohol is known to act as a folic acid antagonist, and excessive consumption can lead to folate deficiency due to reduced intake of food rich in micronutrients, impaired in intestinal absorption, and changes in metabolic pathways . Thus, w ensured . Plenty  ensured ,82,83. HWhen interpreting the results of our meta-analysis, it is important to acknowledge several limitations. First, we focused on studying the individual associations of the C677T and A1298C polymorphisms with cancer risk, without considering their combined effects or the influence of smoking and drinking. However, the available data on the combined effects and interactions between these polymorphisms, as well as smoking and drinking, were insufficient for further analysis. Second, due to limitations in the available data, we were unable to categorize smoking and alcohol consumption into detailed subgroups based on intensity (light/medium/heavy). Instead, we defined individuals as current/ever smokers or non-smokers, as well as drinkers or non-drinkers. This simplified classification may not fully capture the potential nuances of smoking and alcohol consumption patterns.In conclusion, our study highlights the significant influence of smoking and drinking on the relationship between MTHFR polymorphisms and cancer development. The interaction between smoking and the C677T mutation was associated with an increased risk of cancers, particularly liver cancer, and this effect was most prominent in Asian populations. However, the A1298C polymorphism did not show a significant association with cancer risk, even in the presence of tobacco exposure. Conversely, a negative association was observed between alcohol consumption and cancer risk among individuals with either the C677T or A1298C mutation. Future studies with larger sample sizes are needed to further explore the combined effects of tobacco or alcohol and MTHFR polymorphisms at varying folate levels in cancer development .


The purpose of this study was to comprehensively evaluate the lipid profiles in patients with juvenile idiopathic arthritis (JIA).The literature and relevant reviews were searched for published clinical studies on the relationship between JIA and blood lipid levels. The Newcastle–Ottawa scale (NOS) was applied to evaluate the risk and methodological value of the included case‒control and cohort studies. Standardized mean differences (SMDs) and 95% confidence intervals were derived for all variables with adequate unprocessed data. This meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.P = 0.026], high-density lipoprotein cholesterol , and apolipoprotein A1  in JIA patients were statistically lower than those observed in healthy controls. The level of low-density lipoprotein cholesterol  was significantly higher in JIA patients than in healthy controls. In JIA patients, body mass index , high-density lipoprotein , total cholesterol  and apolipoprotein B levels  were not significantly different from those in healthy controls.In total, 16 studies were incorporated through screening. The analysis findings revealed that the levels of very low-density lipoprotein cholesterol [SMD=-0.411, 95% CI (-0.774~-0.048), The outcomes of this meta-analysis suggest that dyslipidemia is common in JIA patients compared to healthy controls. Patients with JIA have a significantly increased risk of atherosclerosis and cardiovascular disease later in life. Juvenile idiopathic arthritis (JIA) is a long-term rheumatic disorder that is mainly characterized by joint damage, which can be accompanied by multiple systemic systems . The onsMuch research evidence shows that long-term chronic inflammation affects lipid metabolism , 6. The This analysis was carried out in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) regulations . The proThe criteria for inclusion were as follows: (1) cohort studies, case‒control studies, or cross-sectional studies evaluating the relationship between serum lipid levels and JIA. The diagnosis of JIA was made according to the consensus conference of the International League of Associations for Rheumatology (ILAR) in 2001 or the American College of Rheumatology (ACR) in 1986. The control group was composed of healthy children. (2) Quantitative measurements of blood lipids and the total number of cases were provided in the article. (3) Studies were published in either Chinese or English.The exclusion criteria were as follows: (1) duplicate studies; (2) research papers or conference abstracts that could not be procured online; and (3) reviews and case series.Before designing the search strategy, the opinions of literature search experts were sought. From database establishment to July 15, 2023, under English and Chinese language restrictions, the MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, and Web of Science databases were systematically searched. The MEDLINE search strategy  back to back to ensure the quality of data entry. Conflicting literature or data that were difficult to determine were resolved by consultation or with the assistance of a third researcher (C.-F.L).The Newcastle–Ottawa scale (NOS) was applied to evaluate the risk and methodological value of the included case‒control and cohort studies . The sca2 value [P > 0.1 and I2 < 50%, there was no statistical heterogeneity among the studies, and the fixed effect model method was used to calculate the SMD value. Conversely, when P ≤ 0.1 or I2 ≥ 50%, the presence of statistical heterogeneity necessitates the employment of a random effect model for calculating the SMD value. Begg’s test and Egger’s test were used to test publication bias. Sensitivity analysis was performed by recombining and analyzing individual studies one by one.The statistical software Stata version 14.2) was utilized for synthesizing data and statistical interpretation .2 was ut. A rando2 value . When P The literature search obtained 1894 unique database records. Most of the studies 1739) were eliminated during the initial screening process based on their titles and summaries. Out of the 155 full-text studies that were scrutinized, only 16 studies 39 were e satisfieThe incorporated papers exhibited varying degrees of quality, with scores ranging from five to eight. The scores were frequently downgraded due to the absence of independent verification of case status and insufficient follow-up measures Tables , 4 and 5P = 0.000, I2 = 92.9%) showed that there was a significant level of heterogeneity in the research literature, and the random effects model was employed for combined statistics. The results indicated a pooled SMD of -0.189, a 95% CI of -0.690 ~ 0.311, and a Z score of 0.74 (P = 0.459), suggesting no significant differences in BMI between JIA patients and healthy controls. To further analyze the sources of heterogeneity, sensitivity analysis was used to eliminate the studies one by one, and it was found that the analysis results were relatively robust. Subgroup analysis was conducted on potential regulatory variables. Subgroup analyses were performed according to the study design, and none of the results changed  showed that there was a significant level of heterogeneity in the research literature, and the random effect model was employed for combined statistics. The results indicated a pooled SMD of -1.235, a 95% CI of -2.845 ~ 0.374, and a Z score of 1.50 (P = 0.133), suggesting no significant differences in HDL cholesterol between JIA patients and healthy controls. To further analyze the sources of heterogeneity, sensitivity analysis was used to eliminate the studies one by one, and it was found that the analysis results were relatively robust. Subgroup analyses were performed according to the study design, and none of the results changed  shows that there was a significant level of heterogeneity in the research literature, and the random effect model was utilized for combined analysis. The results indicated a pooled SMD of 0.616, a 95% CI of -0.813 ~ 2.046, and a Z score of 0.84 (P = 0.398), suggesting no significant differences in LDL cholesterol levels between JIA patients and healthy controls. To further analyze the sources of heterogeneity, sensitivity analysis was used to eliminate the studies one by one, and it was found that the analysis results were relatively robust. Subgroup analyses were performed according to the study design, and none of the results changed  showed that there was some homogeneity in the research literature, and the random effect model was implemented for combined statistics. The results indicated a pooled SMD of -0.411, a 95% CI of -0.774~-0.048, and a Z score of 2.22 (P = 0.026), suggesting that the VLDL cholesterol level of JIA patients was statistically less than that of healthy controls  showed that there was some homogeneity in the research literature, and the random effect model was employed for combined statistics. The results indicated a pooled SMD of 0.278, a 95% CI of -0.182 ~ 0.738, and a Z score of 1.18 (P = 0.236), suggesting no significant differences in TG levels between JIA patients and healthy controls. To further explore the potential sources of heterogeneity, subgroup analysis was conducted on potential regulatory variables. Subgroup analyses were performed according to the study design. Subgroup analyses were performed according to the study design. The results found significant differences in the case‒control study and no differences in the other types  showed that there was some homogeneity in the research literature, and the random effect model was utilized for combined statistics. The results indicated a pooled SMD of -0.073, a 95% CI of -0.438 ~ 0.293, and a Z score of 0.39 (P = 0.696), suggesting no significant differences in TC levels between JIA patients and healthy controls. To further explore the potential sources of heterogeneity, subgroup analysis was conducted on potential regulatory variables. Subgroup analyses were performed according to the study design. The results found significant differences in the case‒control study and no differences in the other types  showed that there was some homogeneity in the research literature, and the random effect model was implemented for combined statistics. The results indicated a pooled SMD of -0.528, a 95% CI of -0.976~-0.079, and a Z score of 2.31 (P = 0.021), suggesting that the HDL-C level of JIA patients was statistically lower than that of healthy controls. To further explore the potential sources of heterogeneity, subgroup analysis was conducted on potential regulatory variables. Subgroup analyses were performed according to the study design. The results found significant differences in the cohort studies and no differences in the other types  showed that there was little homogeneity in the research literature, and the fixed effect model was utilized for combined statistics. The results indicated a pooled SMD of 0.202, a 95% CI of 0.003 ~ 0.400, and a Z score of 1.99 (P = 0.046), suggesting that the LDL-C level of JIA patients was statistically higher than that of healthy controls. To further explore the potential sources of heterogeneity, subgroup analysis was conducted on potential regulatory variables. Subgroup analyses were performed according to the study design. The results found significant differences in the case‒control study and no differences in the other types  showed that there was little homogeneity in the research literature, and the fixed effect model was employed for combined statistics. The results indicated a pooled SMD of -1.050, a 95% CI of -1.452~-0.647, and a Z score of 5.11 (P = 0.000), suggesting that the Apo-A1 level of JIA patients was statistically inferior to that of healthy controls. To further explore the potential sources of heterogeneity, subgroup analysis was conducted on potential regulatory variables. Subgroup analyses were performed according to the study design, and none of the results changed  showed that there was little homogeneity in the research literature, and the fixed effect model was employed for combined statistics. The results indicated a pooled SMD of 0.226, a 95% CI of -0.133 ~ 0.585, and a Z score of 1.23 (P = 0.217), suggesting no significant differences in Apo-B between JIA patients and healthy controls. Subgroup analyses were performed according to the study design, and none of the results changed . Begg’s and Egger’s bias tests and funnel plots showed no obvious asymmetry, indicating that there was little publication bias in the selected studies .The differences in serum lipid levels between the JIA and control groups were compared in this meta-analysis. In this meta-analysis of 16 trials involving 1502 participants, the results showed that the VLDL, HDL-C, and Apo-A1 levels in the JIA group were lower than those observed in the control group, and the LDL-C level in the JIA group was higher than that in the control group. There were no significant differences in BMI, HDL, LDL, TG, TC, and Apo-B between the JIA group and the control group.In recent years, many studies have reported that compared with healthy children, children with JIA have blood fat metabolism disorders . CurrentVLDL is one of the plasma lipoproteins. VLDL may be related to physical activity and disease activity in JIA . Some stThe literature included in this study was all case‒control studies or cohort studies published in the last 30 years, and the NOS evaluation criteria were applied to score each study. The criteria for the diagnosis and exposure of JIA were clear in the included literature, so the bias caused by disease diagnosis errors and the determination and measurement errors of exposure factors was low. The funnel plot also suggested low publication bias.This study, nonetheless, is not without its constraints. First, bibliographic bias occurs in the process of literature collection. The language scope of the included studies was restricted to Chinese and English; thus, valuable research published in various linguistic versions could not be retrieved or evaluated. Second, all the papers included have been previously published, and unpublished research results and documentary evidence from other nontraditional sources were lacking. The literature with “positive” results may overstate the strength of the association for some risk factors. An analysis of the causes showed that publication bias may be related to the failure to retrieve unpublished literature with negative results, database bias, etc. Due to publication bias, the results may exaggerate the association strength of a risk factor and deviate from the authenticity of JIA. Therefore, this conclusion is clinically relevant for reference. Finally, the included case‒control and cross-sectional studies were observational, and the strength of evidence was low. The quality assessment of the incorporated studies based on NOS and AHRQ evaluation criteria showed that the character of each study was different, and the assessment of some literature was low.This review highlights studies of serum lipids in JIA. The outcomes of this meta-analysis suggest that dyslipidemia is common in JIA patients compared to healthy controls. The inflammatory status in JIA patients during the active phase of the disease or previous medication use may lead to lipid metabolism disorders. Patients with JIA have a significantly increased risk of atherosclerosis and cardiovascular disease later in life. Therefore, in clinical work, early intervention in lowering blood lipids can be performed on JIA patients with hyperlipidemia, thereby improving the prognosis and quality of life of patients. In future studies, it is still necessary to further analyze whether there is an interaction between different lipid indexes and to conduct a larger sample size population cohort study to explore the pathophysiological mechanism of lipid disorders in JIA.


The purpose of the current meta-analysis was to determine the incidence and risk factors to provide a scientific basis for prevention and treatment of postoperative cognitive dysfunction (POCD) after carotid endarterectomy (CEA).Relevant articles published before October 2022 were searched from Pubmed/MEDLINE, Cochrane and Embase databases. The outcomes were the incidence and risk factors for POCD. A random-effects model was applied to estimate the overall odds ratios (ORs) and mean differences (MDs) for all risk factors through STATA 14.0 and RevMan 5.4. The quality of eligible studies was evaluated by Newcastle–Ottawa Scale (NOS) as previously described.P < 0.001). Of the 16 identified risk factors, hyperperfusion  and degree of internal carotid artery (ICA) stenosis  were the potential risk factors of POCD, whereas patients taking statins preoperative had a lower risk of POCD . Subgroup analysis revealed that the risk of POCD at 1 month after CEA was higher in patients with diabetes .A total of 22 articles involving 3459 CEA patients were finally identified. The weighted mean incidence of POCD was 19%  0.16–0.24, The risk factors of POCD were hyperperfusion and degree of ICA stenosis, while diabetes could significantly increase the incidence of POCD at 1 month after surgery. Additionally, preoperative statin use could be a protective factor for POCD following CEA.The online version contains supplementary material available at 10.1186/s13019-023-02428-6. Stroke is the most common cause of disability and death in the world, killing about 12 million people each year . RecentlDifferent from other surgery, the mechanism of POCD after CEA might be closely associated to existed cerebrovascular lesions and the specificity of the surgical procedure. Recently, Arba et al.  found thIn the present meta-analysis, we will systematically review the incidence and perioperative risk factors for POCD following CEA by comparing with the prior articles, to provide more accurate guidance for routine screening risk factors, which may be beneficial to early interventions of at-risk individuals.The present meta-analysis was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement , which wAll original English prospective and retrospective studies including cohort, case–control, cross-sectional, etc. were considered qualified for inclusion criteria, which assessed cognitive functions in patients before and after CEA. We excluded review articles, meta-analyses, conference abstracts, comments and case reports/case series. Moreover, the reported outcomes should be odd ratios (ORs) of risk factors with 95% confidence intervals (95% CI).All records containing titles and abstracts were inputted into Endnote X9 and repeating items were expurgated. Then, we screened titles and abstracts of the remaining studies according to inclusion criteria. The full texts of potentially included articles were further obtained and assessed by two reviewers to identify studies meeting the selection criteria independently. Any different opinions were identified by discussion, with the participation of a third author if necessary. In addition, all relevant reviews screened by the original search and the reference lists were assessed for additional eligible studies.We extracted details of the eligible studies, such as the first name of author, study type, year and country of publication, patient characteristics , methodological standards (cognitive assessment criteria and time of preoperative and postoperative cognitive assessment), Outcome measures. Variables represented by median and quartile were converted to mean standard deviation . All datI2 test. A fixed effects model was applied to conduct the meta-analysis if there was no heterogeneity (P > 0.1 or I2 < 50%) in the eligible studies. If there was significant heterogeneity (P < 0.1 or I2 ≥ 50%), a random effects model was applied for the meta-analysis. Publication bias was assessed as quality through Egger’s tests. A value of P < 0.05 was identified statistically significant.POCD incidence was shown as proportion of the case in total sample and pooled as proportional-weighted estimates. Review Manager 5.4 and STATA 14.0 software were used to conduct the meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were applied to express effect-size for dichotomous data, while mean difference (MD) and 95%CIs were used to show continuous data. If data on risk factors for studies was incomplete, the effect estimate was shown as log[OR] with standard error. First, we performed a heterogeneity test on identified studies through The original literature searched from three databases produced 2350 records. 2022 studies remained when 328 duplicate records were removed. Then, 1986 studies excluded according to titles and abstracts, and the full texts of 36 relevant studies were accessed and reviewed. Finally, a total of 22 observational studies, published between 2001 and 2021, were identified for further qualitative and quantitative synthesis. The database screening process was shown in Fig. The characteristics of the eligible articles were shown in Table I2 = 93.1%, P < 0.001). The result of subgroup analysis showed that incidence of POCD at 3 days, 1 month, 1 year after surgery was 32% , 13% , 13% , respectively.Incidence of POCD was reported in 21 studies, in total of 3413 patients. The weighted mean incidence of POCD was 19% (95% CI 0.16–0.24), as indicated in Fig. The pooled odds ratios (ORs) and mean difference (MD) of 16 risk factors with their heterogeneity test and confidence intervals results were summarized in Table I2 = 62%, P = 0.02), subsequent sensitivity analysis revealed that the degree of ICA stenosis was still a risk factor for POCD , as shown in Fig. I2 = 0%, P < 0.001), as illustrated in Fig. I2 = 0%, P = 0.02), as shown in Figs. Patient-related risk factors were demonstrated in 18 observational articles  as shown in Table There were 6 articles reporting hyperperfusion, 2 articles evaluating selective shunting placement and 9 studies assessing cross-clamping duration. The result of our analysis indicated that the risk of POCD increased in patients with hyperperfusion after CEA  and each factor relevant studies did not indicate the presence of publication bias: age (P = 0.891), sex (P = 0.939), diabetes (P = 0.518), dyslipidemia (P = 0.699), hypertension (P = 0.913), preoperative symptoms (P = 0.092), and cross-clamping duration (P = 0.299) , which might be related to the adjustment for confounding factors in the most of included studies [In the present article, the pooled incidence of POCD after CEA was 19% 95% CI 0.16–0.24), which was consistent with the result in a previous study (6–36%) [ studies , 16. Fur–0.24, whThe result of this article revealed that hyperperfusion was a significant risk factor for POCD after CEA. Cerebral hyperperfusion, a dramatic increase in cerebral blood flow (CBF) exceeded the metabolic requirements of the brain tissue, could cause cerebral oedema or intracerebral haemorrhage. Hyperperfusion post-CEA was defined as a 100% increase or greater in CBF compared with preoperative values. CBF was measured by single-photon emission computerized tomography (SPECT) scanning before and after CEA in included articles. Some studies indicated that asymptomatic hyperperfusion could also lead to postoperative cortical neural damage and resulted in cognitive decline , 18. TheI2 = 62%, P = 0.02), subsequent sensitivity analysis revealed that the degree of ICA stenosis was still a significant risk factor for POCD. We found the study by Zhang et al. [Moreover, different from the meta-analysis of 2020 , we foung et al. . Previoug et al. , 23. Besg et al. .From this meta-analysis, We did not find significant relationships between patient-related factors and POCD, such as age, sex, hypertension and others. Age is a well known risk factor for POCD in patients undergoing cardiac and noncardiac surgery , 26. TheAlthough there were no significant differences in diabetes, the subgroup analysis indicated that diabetes could significantly increase the incidence of POCD 1 month after surgery. Similarly, in a retrospective review of more than 6000 CEA patients, Tu et al.  verifiedAnother interesting result demonstrated that statin use preoperative was a protective factor for POCD following CEA, which consistent with conclusions of previous meta-analysis . StatinsThere are some limitations in the current meta-analysis. Firstly, the absence of standardisation to define POCD may limit the precision of the analysis. Secondly, the time of evaluating cognitive function is only within 1 year after CEA in included studies, which may lead to errors in the incidence of POCD. Finally, some other risk factors such as frailty, anesthesia method and data on middle cerebral artery Doppler are not considered in this study.The potential risk factors of POCD were hyperperfusion and the degree of ICA stenosis, while diabetes could significantly increase the incidence of POCD 1 month after surgery. What’s more, preoperative statin use could be a protective factor for POCD following CEA. In order to develop accurate prevention strategies, surgeons and nursing staff should have a comprehensive understanding of POCD after CEA. This meta-analysis can help them systematically identify risk factors.Additional file 1: Search Strategy and Supplemental Tables and Figures.


This study aims at computing the pooled mean estimate (PME) and health risks of heavy metals in seafood obtained from the Niger Delta Region of Nigeria (NDRN), using data from existing literatures. Pubmed, Scopus and Google Scholar were searched to retrieve articles that investigated the heavy metal contents of edible seafood from the NDRN. Search hits were screened against predetermined criteria following which relevant data were extracted from eligible articles. The PME for each metal was computed by performing a maximum likelihood random effect model meta-analysis using the R Studio Software. Outcome from the meta-analysis involving 58 studies and a total of 2983 seafood samples revealed the following PMEs (mg/kg dry wt seafood) for the investigated heavy metals: As (0.777), Cd (0.985), Co (4.039), Cr (2.26), Cu (11.45), Fe (143.39), Hg (0.0058), Mn (13.56), Ni (5.26), Pb (4.35), and Zn (29.32). The health risk assessment suggests that seafood from this region poses considerable carcinogenic and non-carcinogenic risks to human consumers. Our finding calls for urgent actions aimed at identifying and eliminating point sources of heavy metals pollution of the NDRN marine environment. Inhabitants of NDRN are encouraged to reduce seafood consumption while diversifying their protein sources to include non-seafood options.  •Meta-analytic technique was used to compute PMEs of metals in seafood from NDRN.•Seafood from the NDRN are rich sources of micronutrients like Cu, Cr, Mn, Zn and Fe.•Seafood may pose a non-carcinogenic risk to consumers in NDRN due to Cd, Pb and Co.•Seafood may pose a carcinogenic risk to NDRN consumers due to it’s As and Cr content.•Reduction in seafood intake and diversification of protein sources is advised. For instance, during crude oil explorations, drilling machineries alongside with drilling fluids are used to drill down to deep underground crude oil reserves. Since heavy metals are constituents of crude oil, excavated earth and drilling fluids, While individual studies have investigated metal levels in seafood from the NDRN This study therefore aims at the systematic retrieval, the qualitative and meta-analytic synthesis of data extracted from studies that investigated the levels of any of the predominant heavy metals  in seafood obtained from natural water bodies in the NDRN. The potential effect of seafood types, sampling locations, study year and anthropogenic activities around sampling sites on inter-study variations was also investigated. Outcome from this study would provide information on the potential health risks due to heavy metal exposure following seafood consumption as well as assist in the development of appropriate public health guidelines and regulations aimed at protecting inhabitants of the NDRN.22.1This review and meta-analysis was carried out with adherence to the recommendation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline 2.1.1“( TITLE-ABS-KEY ( seafood OR fish OR shellfish OR oyster OR periwinkle OR shrimp OR crab OR catfish OR tilapia) AND TITLE-ABS-KEY  AND TITLE-ABS-KEY )”.2.1.2“(seafood OR fish OR shellfish OR oyster OR periwinkle OR shrimp OR crab OR catfish OR tilapia) AND  AND ”.The search was initially conducted in October 2019 but was repeated in November 2022. The titles and abstracts of hits from the database searches were screened following which unique and relevant articles were selected for full text screening based on pre-defined inclusion criteria.2.2Articles selected for this systematic review and meta-analysis were experimental in nature and determined heavy metals, namely As, Cd, Cr, Co, Cu, Fe, Mn, Hg, Ni, Pb, and Zn, in edible seafood sourced from natural water bodies within any of the 9 states  of the NDRN. Therefore review articles, non-journal articles, non-English articles, articles that dwelled on farmed seafood, or seafood obtained from market far from water bodies or those from locations other than the states of NDRN were excluded from this study. Similarly, studies that were conducted on non-edible seafood, non-edible portions of seafood, those published before 2000, or those that reported wrong, ambiguous or unclear units, or whose full text was not available or retrievable online were excluded. Additionally, studies lacking key statistical details  were excluded from meta-analysis. The selection of relevant article was carried out by FU and reviewed independently by CO and CI.2.3The quality of the included studies were evaluated using a slight modification of the method of 2.4Information on the sampling and experimental methodology, study area description, heavy metals investigated, seafood investigated and results were carefully and methodologically extracted from each included study by one of the authors (FU) and then double checked by the other authors. This data was used to populate the summary table which had a predefined template that includes author’s last name and year of article publication, sampling locations and coordinates, anthropogenic activities, seafood type, sample size, heavy metals investigated and summary of outcome.2.5Data from eligible studies including the mean, standard deviation (SD), sample size, seafood type (fish or shellfish), anthropogenic activities , heavy metal type, year of study and seafood sampling locations (States and water bodies) were extracted from each study and entered into an excel spreadsheet template. Mean and/or SD data were computed for studies that reported only raw data or standard error of mean (SEM) values before insertion into the spreadsheet template. Data extraction from charts was accomplished using the pixel ruler software obtained from https://www.arulerforwindows.com. Heavy metals that were below detection limits were assigned the mean and SD values of 0.0001 and 0 respectively, to permit computation. Data inserted into the spreadsheet were those having the units of "mg/kg dry weight". Mean and SD of studies whose results were originally presented in “mg/kg wet” weight basis were converted to their dry weight equivalent by dividing the “mg/kg wet weight” values by a factor of 0.28. This factor corresponds to an average seafood moisture content value of 72% , as deduced from the data published by 1 and N2 are sample size of group 1 and group 2 respectively; M1 and M2 are mean of group 1 and group 2 respectively, SD1 and SD2 are the standard deviation of group 1 and group 2 respectively.3The PME for each heavy metal reported in the included studies was computed by performing a meta-analysis on R Studio Software (version 3.6.1); 3.1We performed a subgroup meta-analysis to explore the potential sources of heterogeneity in the computed PMEs. Four subgroup categories including seafood type (i.e. fish or shellfish), anthropogenic activities at sampling sites (i.e. oil-industries or non-oil industries or urban or domestic activities), state-wise sampling locations  and study year  were examined. Information about the prevailing anthropogenic activities at sampling sites was obtained from the description given within each study. Any site with oil-related activities or with past history of oil spill was assigned “oil-related”, while non-oil related sites were assigned “non-oil related industries” or urban or domestic depending on the presence of non-oil industries, commercial or rural activities respectively.3.2The potential non-carcinogenic and carcinogenic risks posed on the health of NDRN residents following the consumption of heavy metal contaminated seafood was investigated by calculating the target hazard quotient (THQ) and excess lifetime cancer risk THQ = The EDI of each heavy metal  was calculated by multiplying the heavy metal content of the seafood (i.e. mg/kg wet wt) by the food intake rate (FIR) (i.e. kg of food/person/day) and dividing by the average body weight of the individual (i.e. kg/person) as shown in -1 day−1)=EDI . A body weight of 60 kg was assumed as the average body weight of a normal Nigerian adult The carcinogenic risk was estimated using the Incremental Lifetime Cancer Risk (ILCR) (Equation 4). The ILCR estimates the probability of developing cancer following a daily exposure to a carcinogen for a lifetime of 70 years Incremental Lifetime Cancer Risk = .-1 day−1) is the lifetime estimated daily intake dose calculated as presented in equation 2, CSF (mg/kg-day)-1 is the oral cancer slope factor.Where EDI (mg kg-1 were applied for Cr (VI), Pb and As respectively The oral cancer slope factors of 0.5, 0.0085 and 1.5 (mg/kg-day)44.1A total of 1012 hits were obtained following the searches conducted on Pubmed, Scopus and Google Scholar. Title and abstract screening yielded a total of 143 unique articles. Following the screening of these articles for eligibility, 63 articles did not meet the eligibility criteria and so were excluded while 80 and 58 of these articles were used for qualitative synthesis and meta-analyses respectively.  PRISMA.F4.2The summaries of the included studies are presented in The studies conducted in Bayelsa obtained their seafood from Azuzuama, Lobia and Ogboinbiri communities in Yenagoa. The presence of oil exploration industries and urban centers have been reported around these locations. In Edo state, seafood samples were largely collected from Ikpoba and Benin Rivers as well as from Agenebode community . These water bodies are potentially contaminated with wastes from both crude oil and non-crude oil related industries. Studies conducted in Akwa Ibom obtained seafood samples from Itu, Oron and Qua Iboe River while those conducted in Imo obtained seafood from Mbaa and Imo Rivers. These water bodies especially those of Imo, Mba and Qua Iboe Rivers receives effluent from crude and non-crude industries, agricultural runoffs and municipal wastes. Aba River is the sampling location of included studies conducted in Abia state while those conducted in Cross river state, were sampled from the Cross-river system . Activities around sampling sites of the Aba river and Cross-river system are mainly those of non-crude oil related industries. Seafood used for studies conducted in Ondo state were obtained from communities along the Ondo coastal area including Ayetoro and Awoye as well as from Oluwa River. Farming and fishing were the predominant activities around most of the sampling site while some of the sites had oil exploration activities. The seafood investigated in the included studies consists of different species of commonly consumed fish  and shellfish   S.4.3The majority of the included studies performed poorly in the "Testing equipment" and "Sampling and detection bias" domains of the quality assessment . Most of4.42 =100%) was obtained (2 =100%) (2 =100%) computed from a total of 108 seafood samples investigated across 9 studies (2 =100%) (2 =100%) derived from 38 studies consisting of a total of 1743 seafood samples (2 =100%) from 31 studies consisting of 1109 seafood samples  seafood   while Co studies . The PME2 =100%)  while Cu samples . Fe had  samples  while Hg samples , Fig. 11 samples  respecti4.52 value of 91% and 99% respectively, while the other metals  had I2 value of 100%. Subgroup meta-analysis based on the seafood category did not improve the I2 of any of the heavy metal investigated except for a slight improvement in the I2 of Hg. Similarly, the Chi square test for seafood category difference was not significant (p > 0.05) for any of the heavy metal investigated . The prevailing anthropogenic activities in each study area significantly influenced the between-study variation in the As, Co, Mn, Ni and Pb contents of seafood from the NDRN (p < 0.05). However, only slight improvement in the I2 values of As and Co were observed after performing a subgroup meta-analysis based on the anthropogenic activities. Subgroup meta-analysis based on the state-wise categorization of seafood sampling location showed slight reductions in the I2 values for Cd, Co, Cr, Cu, Fe, Hg, Ni, Zn and Pb. The test for subgroup difference showed that the state-wise categorization significantly influenced the between-study variation in the seafood contents of all the metals investigated (p < 0.05) except for Mn. The study-year subgroup meta-analysis did not improve heterogeneity in any of the heavy metals while the test for Chi square differences in the Pb, As, Co and Cr subgroup meta-analysis indicate significant differences (p < 0.05) in the PME of seafood across different study years . Consumption of 26 g of this seafood on a daily basis can supply the RDA for Cu (0.3 – 1.3 mg) and Cr (0.005 – 0.045 mg). Additionally, the Mn, Zn, and Fe content in the seafood has the potential to fulfill 29%, 30%, and 53% respectively of the RDA for Mn (1.2–2 mg), Zn (2.5–12 mg), and Fe (7 – 27 mg) The THQ, which is a ratio of the EDI of the contaminant of interest to a standard reference dose (i.e. the maximum exposure dose of each contaminant that is not expected to elicit any adverse effect) gives a value that indicates the extent to which the ingested dose exceeds the maximum safe levels of the contaminant in question Exposure to Cd have been reported to weaken the skeletal system by increasing the demineralization of bones, reducing bone density therefore increasing the risks of bone fractures and osteoporosis Cobalt is an important constituent of cobalamin (i.e. Vitamin B12) which is produced in some animals through the activities of intestinal microorganism Pb is a known systemic toxicant that affects several organs including the kidney, bone, brain, and the reproductive organs 4 can trigger cancer when inhaled or ingested whereas Cd, Co and Ni exposure have been documented to trigger carcinogenesis following inhalation but not through oral exposure According to the USEPA The life time cancer risk gives a numeric indication of how many new cases of cancer can result within a population of people who have been similarly exposed to a particular agent 2 test for heterogeneity assesses the presence and extent of inter-study differences between studies combined for meta-analysis 2 values less than 40 is considered low heterogeneity while 30–60% and above 75% is considered moderate and high heterogeneity respectively 2 values after subgroup meta-analysis, showed that none of the subgroup category could fully explain the sources of the observed heterogeneity in the PME of the heavy metals. This indicates that the heterogeneity observed in this study is likely influenced by multiple factors, rather than being solely attributed to a single factor. It also implies that additional factors beyond the ones investigated in this study needs to be considered for better understanding of the sources of the observed variations. Other potential sources of heterogeneity not accounted for in this study includes seasonal variation The I8The strength of this study lies in the numbers of studies used in the computation of the PME, this gave a more precise data than those from the individual studies. An additional strength is the rigorous quality assessment we conducted for the included studies as well as the at-a-glance overview of the study quality we provided. Despite our effort to retrieve all relevant paper in this subject area we acknowledge the possibility of unintentional omission of some relevant studies either due to the keywords we used or the literature databases we searched. Since this study relied solely on the data from other studies, the validity, usefulness and reliability of the PMEs and risk assessments are subject to the quality and authenticity of each included studies. For instance, as seen from the quality assessment section of this paper, majority of the study did not provide evidence that equipment or method validation was carried out before elemental analysis. Similarly most of the included study had high likelihood of assessment and sampling bias while a few of the studies had high risk of publication biases. The inherent biases and limitations of the included studies could limit the accuracy of the PMEs and the conclusions drawn about the potential health risks to inhabitants of the NDRN. The high heterogeneity in the meta-analysis might impair the generalizability of the PME  for the entire NDRN’s population, however, the ease of trans-border trades amongst communities of the NDRN predisposes majority of the inhabitants to an average exposure level that may be close to the computed PMEs. This assertion is supported by evidence from the sensitivity analyses which showed that the PME of most of the metals was robust enough to prevent a drastic change in its value following the removal of any particular study. The presence of uneven group sizes and low number of studies within each subgroup , and high heterogeneity in the dataset may potentially affect the outcomes and conclusions drawn from the subgroup analyses 9This systematic review and meta-analysis was necessitated by the need to comprehensively evaluate the metal contents of seafood in the NDRN and determine their potential health risks. The findings of this study raise serious concerns regarding the safety of seafood from the NDRN. Not only do the Pb levels exceed thresholds associated with decreased intelligence quotient in children, but the Cd and Co contents also surpass safe limits for renal and thyroid dysfunctions respectively. Additionally, the presence of As and Cr in seafood has potentials to increase the risk of skin and gastrointestinal cancers among consumers. These alarming results have significant implications for public health and economic growth of the region since majority of the inhabitants rely heavily on seafood as their primary source of essential nutrients.To mitigate these potential adverse effects, consumers are encouraged to minimize seafood consumption and to diversify their sources of animal proteins to include non-seafood options. This would reduce the accumulation of specific heavy metals to levels that can cause adverse effect. To ensure a sustainable and healthy seafood supply in the NDRN, we recommend that relevant regulatory agencies should conduct frequent monitoring of seafood from this region especially in locations such as Ogoniland (Rivers State), Woji Creek (Rivers State), Benin River (Edo State) and Oguta lake (Imo State) where unusual levels of toxic metals were detected. Such monitoring activities should focus at identifying point sources of marine pollution as well as restricting fishing at highly contaminated regions. Stricter enforcements of regulations against the release of industrial effluents, municipal wastes and crude oil related substances into water bodies are equally recommended.Finally, in order to improve the quality of future bio-monitoring data generated from the NDRN, appropriate method validation should be performed prior to sample analysis and efforts should be made to reduce sampling and detection biases.Not Applicable.The authors did not receive support from any organization for the submitted work.Francis Uchenna Umeoguaju: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Data curation, Writing – original draft. Joyce Oronne Akaninwor, Eka Bassey Essien and Benjamin Achor Amadi: Supervision, Writing – review and editing. Chimaobi James Ononamadu: Validation, Investigation, Resources, Data curation. Onyedika Igboekwe and Charles German Ikimi: Validation, Data curation. All the authors read and approved the manuscript.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


It has been assumed that perinatal factors such as multiple pregnancies may affect subsequent breast cancer risk in the mother. Considering the inconsistencies in the results of case-control and cohort studies published in the world, this meta-analysis was conducted in order to determine the exact association between multiple pregnancies (twins or more) and the breast cancer incidence.This study was performed as a meta-analysis based on PRISMA guidelines by searching the international databases of PubMed (Medline), Scopus, and Web of Science as well as by screening selected articles based on their subject, abstract and full text. The search time was from January 1983 to November 2022. Then the NOS checklist was used to evaluate the quality of the final selected articles. The indicators considered for the meta-analysis included the odds ratio (OR) and the risk ratio (RR) along with the confidence interval reported in the selected primary studies. The desired analyzes were performed with STATA software version 17 to be reported.In this meta-analysis, 19 studies were finally selected for analysis, which fully met the inclusion criteria. Of these, 11 were case-control studies and 8 were cohort ones. Their sample size was 263,956 women  and 1,658,378 , respectively. After combining the results of cohort and case-control studies, the effect of multiple pregnancies on the breast cancer incidence was equal to 1.01  and 0.89 , respectively.The present meta-analysis results showed, in general, multiple pregnancies were one of the preventive factors of breast cancer.The online version contains supplementary material available at 10.1186/s13690-023-01089-0. The growing breast cancer prevalence in women is one of the most important problems of humanity in today’s society. In 2020, 2.3 million women were diagnosed with breast cancer and 685,000 died because of its worldwide –3. By thThe present study was a systematic review and meta-analysis based on the structure of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) . The seaThe inclusion criteria were defined based on the PECOT structure . This stAfter the screening stage based on the inclusion and exclusion criteria, an information extraction checklist containing information related to studies , information related to the desired exposure , information related to the target population  and information related to the outcome  was designed, based on which information was extracted from the final articles.Two of the authors (YM and PV) conducted a qualitative evaluation of the studies on the basis of the Newcastle-Ottawa Quality Assessment Scale (NOS) checklist . This chIn this meta-analysis, two types of case-control and cohort studies were analyzed. The indicators considered for the analysis included the odds ratio (OR) and the risk ratio (RR) along with the confidence interval reported in the selected primary studies. Since these indicators are right-skewed, they should be converted to normal distribution for analysis, and for this reason, the logarithm of these indicators was included in the analysis. The desired model for analysis was random effects or fixed effects (inverse variance). The degree and percentage of heterogeneity in this study were expressed using I square and Cochrane’s Q index . AccordiAfter completing the search, 558 studies were retrieved in PubMed, 893 in Scopus and 330 in Web of Science. A total of 1781 studies were included in the review, of which 681 were duplicated and in the first step, 1100 studies were entered into the screening stage based on the title. After removing irrelevant studies in this stage, 190 articles were entered into the screening stage based on the abstract. In this step, 99 studies were excluded and in the next step, i.e., screening based on the full text, 91 studies were evaluated   and the results have been reported in Table In the second step of meta-analysis, the results of case-control studies were evaluated. Of the 11 selected studies, the highest and lowest odds ratios were related to the studies of Muphy et al. and Innes et al., respectively. After combining these studies, the pooled OR was equal to 0.89  (Figs. The main goal of this meta-analysis was to determine the association between multiple births and the incidence of breast cancer in women. In this meta-analysis, two types of case-control and cohort studies were examined and analyzed. Due to the fact that these two types of studies were different in terms of the nature and method and reporting the effect sizes, we decided to separately report the combination of the results of these two types of studies to determine the association. On the other hand, because breast cancer was not rare in women with multiple births according to the results of previous studies, combining the results of these two types of studies was not correct in terms of methodology and increased the possibility of reporting an unrealistic effect size –28. The The combination of these two indicators is possible only if the desired outcome frequency in the studied population is less than 0.05 or the desired outcome is rare , 30. HowIn addition, according to the results of the study of Janssens, Jaak Ph et al., the HCG hormone has an anti-proliferative role in the laboratory environment on cancer cells  and its An increase in the levels of estradiol, testosterone, progesterone, human chorionic gonadotropin and alpha-fetoprotein hormones has been observed and proven in pregnancy, and it seems the increase in human chorionic gonadotropin and fetoprotein progesterone can have a protective effect against breast cancer due to its anti-estrogenic properties effective on the breast tissue, but the association between the higher incidence of breast cancer and the birth of twins or multiples was first established in the 1980s . The phyIn a similar meta-analysis published by Kim, Hye Sook et al., analyzing 17 articles published from 1983 to 2007, different results were obtained [One of the current meta-analysis limitations was the lack of subgroup analyzes based on important variables such as receiving treatment, the type of treatment, time and method of cancer diagnosis, body mass index and age which were not examined due to non-reporting or incomplete reporting in the initial studies.The present meta-analysis results showed, in general, multiple pregnancies were one of the preventive factors of breast cancer, but information on twin pregnancies was conflicting. Therefore, it is necessary to conduct more cohort and case-control studies with appropriate sample sizes, taking into account important and effective factors such as genetics, age, body mass index, receiving treatment and type of treatment.Below is the link to the electronic supplementary material.Supplementary Material 1


To evaluate rates of familial disclosure of hereditary cancer syndrome information.A systematic review and meta-analysis was conducted in accordance with PRISMA guidelines (PROSPERO no.: CRD42020134276). Key electronic databases were searched to identify studies evaluating hereditary cancer syndrome cascade relative disclosure. Eligible studies were subjected to meta-analysis.Thirty-four studies met inclusion criteria. Among 11,711 included relatives, 70% (95% CI 60 - 78%) were informed of their risk of carrying a cancer-associated pathogenic variant; of 2,875 relatives informed of their risk who were evaluated for uptake of cascade testing, 43% (95% CI 27 - 61%) completed testing. Rates of disclosure were higher among female vs male relatives (79% [95% CI 73% - 84%] vs 67% [95% CI 57% - 75%]) and first-degree vs second-degree relatives (83% [95% CI 77% - 88%] vs 58% [95% CI 45 – 69%]).Nearly one-third of at-risk relatives remain uninformed of their risk of carrying a cancer-associated pathogenic variant. Even among those informed, fewer than half subsequently complete genetic testing, representing a critical missed opportunity for precision cancer prevention.Five studies evaluating interventions to improve disclosure rates were generally ineffective. Urgent work is needed to elucidate barriers to relative disclosure by probands to develop targeted interventions that can optimize proband-mediated cascade genetic testing rates. •30% relatives are unaware of their risk of having a cancer associated pathogenic variant.•Female relatives and first-degree relatives are more likely to be informed.•Among those aware of their risk, only 43% complete genetic testing. In the context of cancer-predisposing pathogenic variants, cascade genetic testing offers the opportunity for cancer surveillance and risk-reduction strategies that can decrease cancer morbidity and mortality . There apulation ,4.Approximately four million people currently living in the United States harbor a cancer-associated pathogenic variant; however, the majority of these individuals are not aware . PredictAlthough relatives can learn of the presence of a cancer-associated pathogenic variant in their family without being informed by the proband, for example via direct contact by healthcare providers, disclosure by probands is the most common method of information dissemination within families . Disclos22.1This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was preregistered with PROSPERO (registration no.: CRD42020134276) . A compr2.2Eligible manuscripts included all primary English language studies that assessed cascade genetic testing for cancer-associated pathogenic gene variants with a focus on disclosure of genetic testing results to at-risk relatives. All non-primary research studies including commentaries, case reports, systematic reviews, and meta-analyses were excluded. A comprehensive review of reasons for exclusion of studies can be found in the PRISMA flow diagram .Fig. 1PR2.3All manuscripts were independently evaluated for inclusion by two reviewers and disagreements were discussed with a third reviewer. Data were independently extracted by two different reviewers, with a third reviewer checking the final extracted data for accuracy.2.4All included studies were evaluated for risk of bias in their design, conduct, and analysis using the Joanna Briggs Institute’s Critical Appraisal tools .2.52). A random effects analysis was used to calculate pooled proportions. The random effects analysis is more conservative and allows for more variability in the individual study proportion estimates when generating the pooled proportion. The pooled proportion was calculated using the Freeman-Tukey Double arcsine transformation, and the 95% CI was calculated using the Clopper-Pearson interval. The DerSimonian-Laird estimator was used to estimate the between-study variance. For the outcome proportions of interest, the results of each study were expressed as binary proportions with exact 95% CIs. For each meta-analysis, a funnel plot was constructed and reviewed, displaying the study proportion against study precision, estimated by the standard error, to assess for publication bias.Meta-analyses for the proportion of probands that informed at least one at-risk relative, the proportion of at-risk relatives who were successfully informed and proportion of at-risk relatives who completed genetic testing among those informed were conducted using R software . Statistical heterogeneity was tested through the chi-square test , and a P value < 0.2 was used to indicate the presence of heterogeneity. Statistical heterogeneity was also assessed by the inconsistency statistic , France (3), Australia (3), Netherlands (2), Belgium (1), Finland (1), Israel (1), Malaysia (1), Sweden (1), and the United Kingdom (1). Twenty studies evaluated disclosure rates among relatives at risk for hereditary breast and ovarian cancer only, 4 evaluated disclosure rates among those at risk for Lynch syndrome only, 1 among those at risk for hereditary pancreatic cancer only, and 9 included mixed hereditary cancer syndrome populations .Table 1D3.2A total of 3,779 probands and 11,711 relatives were evaluated for disclosure of genetic test results. The median age of probands across all studies was 50 years and the median age of relatives across all studies was 33.5 years. Among 31 studies that included information on proband biologic sex, 5,118 (83.9%) were female and 981 (16.1%) were male. Among 11 studies that included information on relative biologic sex, 2,094 (50.5%) were female and 2,051 (49.5%) were male.Twenty-two studies reported information on probands’ race and ethnicity. Among the 2,136 probands in these studies, 1601 (75.0%) were White, 224 (10.5%) were Black, 170 (8.0%) were Hispanic, 125 (5.9%) were Asian and 6 (0.3%) were Native American. Of these probands, 626 (29.3%) were Ashkenazi Jewish.3.3Among 3,779 probands, 94% (95% CI 88-97%) initiated the cascade of information about their pathogenic gene variant by disclosing to at least one relative . Among 13.4et al. and Cheung et al. reported higher rates of disclosure among White vs non-White families, whereas two studies found no association [et al. studied disclosure patterns among Black families only, finding that 77% of Black probands in their cohort disclosed their genetic test results to at least one relative [Other studies identified factors associated with disclosure of genetic test results, but the data were either too limited or heterogenous to be meta-analyzed. Four studies reported on the association between race and ethnicity and results disclosure. Taber ociation . Conley relative .Five studies evaluated the impact of proband education level on rates of disclosure. Two studies reported that probands who had at least a college education were more likely to disclose results to relatives when compared to probands whose highest level of education was high school ,29. Threet al. reported that probands with annual incomes higher than $35,000 were more likely to share their genetic test results with relatives when compared to probands with annual incomes lower than $35,000; Cheung et al. reported no association between income and disclosure rates of probands [Two studies evaluated the impact of proband socioeconomic status on disclosure rates. Taber probands ,24.3.5Sixteen studies reported on barriers that probands faced in disclosing to relatives. The most common barrier to disclosure reported by probands in 10 studies was not being in close contact with relatives, including being estranged and not having relatives’ contact details . Nine st3.6Five studies evaluated interventions to assist probands in disclosing information about a familial pathogenic variant to their relatives . A meta-3.7Studies were assessed for risk of bias using tools from the Joanna Briggs Institute. Although all studies suffered from risk of bias in at least one domain, most commonly in lack of identification and control of confounders, they were all deemed appropriate to include in this synthesis. The funnel plots for rates of disclosure and uptake of cascade genetic testing suggest underrepresentation of smaller studies .4We have systematically reviewed the available literature on disclosure of genetic test results by probands to their relatives in the context of cancer-associated pathogenic variants and found that up to 30% of relatives are not aware of the familial cancer risk. Disclosure of genetic testing results by probands is the obligate prerequisite to the process of proband-mediated cascade genetic testing that can result in early cancer detection and cancer prevention for at-risk relatives. With the majority of cancer-associated pathogenic gene variant carriers in the U.S. unaware of their risk, determining rates of disclosure as well as uptake of genetic testing among those relatives to whom disclosure was made, are essential to characterize the efficiency of cascade genetic testing when the process is mediated by probands . SubsequNotably, our findings revealed that only 70% of at-risk relatives are aware of their increased risk of carrying a cancer-associated pathogenic gene variant. Furthermore, among those relatives who are successfully informed, only 43% successfully complete genetic testing to define their pathogenic variant status. Probands were more likely to disclose to female vs male relatives, a trend that has also been observed in uptake of cascade genetic testing . ProbandThis study should be viewed in light of important limitations. First, disclosure of genetic test results to relatives was reported by probands and not confirmed by relatives for all included studies, and thus the meta-analyzed data are subject to recall bias. Furthermore, funnel plots for both proportion of probands disclosing to at least one at-risk relative as well as proportion of at-risk relatives disclosed to demonstrate a skew towards higher disclosure rates among smaller studies. However, larger studies far outnumbered smaller studies in both these funnel plots, and thus the absence of smaller studies with lower disclosure rates is unlikely to be a significant contributor to publication bias. Finally, although all studies were deemed to be of sufficiently low risk of bias overall to be included in our synthesis, no study was entirely unbiased—every included study suffered from risk of bias in one or more domain, most commonly failing to identify and control for confounders.4.1Interventions aimed to better equip probands to disclose genetic risk information by providing written or telephone resources were generally ineffective, highlighting the need for studies focused on proband barriers to disclosure so that targeted interventions can be developed.Recent studies have focused on direct relative contact via clinicians or genetic testing clinical laboratories as a strategy to increase rates of cascade genetic testing ,12. DireSearch StrategySupplementary Table 1The following are the supplementary data related to this article.NIH/NCATS Grant # KL2-TR-002385. Ravi N. Sharaf is supported by the following grants: National Cancer Institute Grant # K07CA216326 and R01CA211723 and Patient Centered Outcomes Research Institute Grant # IHS-2017C3-9211.Melissa K. Frey is supported by the following grant: 10.13039/100007273Clinical and Translational Science Center at Weill Cornell Medical College (1-UL1-TR002384-01).Paul J. Christos and Charlene Thomas are supported by the following grant: Kevin Holcomb reports a relationship with Johnson & Johnson that includes: consulting or advisory.