Biomarkers are necessary to stratify the risk of diabetic foot ulcers (DFUs). This systematic review and meta-analysis aimed to evaluate the association between the lipid profile and apolipoproteins with the risk of DFU.  A systematic search was conducted in PubMed, Scopus, Cochrane Library, and Web of Science among adult patients. Cohort and case-control studies were included. Random-effects models were used for meta-analyses, and the effects were expressed as odds ratio (OR) and their 95% confidence intervals (CIs). We evaluated publication bias through Egger's test and funnel plot.  A total of 12 cohort studies and 26 case-control studies were included, with 17076 patients. We found that the higher values of total cholesterol (TC), low-density lipoprotein (LDL), triglycerides, and lipoprotein(a) (Lp(a)) were associated with a higher risk of developing DFU . Otherwise, the lower values of HDL were associated with a higher risk of developing DFU (OR: 0.49). Publication bias was not found for associations between TC, HDL, LDL, or TG and the risk of DFU.  The high values of LDL, TC, TG, and Lp(a) and low values of HDL are associated with a higher risk of developing DFU. Furthermore, we did not find a significant association for VLDL, ApoA1, ApoB, and ApoB/ApoA1 ratio. In 2019, the global prevalence of diabetes was estimated at 9.3%, which translates to 463 million people affected by this disease. It is expected that by 2030, the prevalence will increase to 10.2% and, by 2045, to 10.9% [Three factors are usually involved in DFU formation: diabetic neuropathy, trauma with secondary infection, and arterial occlusive disease . PatientThe most feared consequence of patients with DFU is amputation, which occurs in 6 to 43% of cases . CurrentThis systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CD42022308926). In addition, we followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement  see PRI and the A systematic search on articles evaluating the association between lipid biomarkers and apolipoproteins for the risk of developing DFU was carried out on December 20, 2021, in the following databases: PubMed, Scopus, Cochrane Library, and Web of Science. The search strategy was originally built in PubMed and adapted to the other databases (see Search Strategy in Supplementary We included studies that met the following criteria: (1) evaluation of the association between lipid profile and the risk of developing a DFU, (2) case-control and cohort studies, and (3) adult patients (≥18 years). We excluded studies that were (1) case reports, (2) studies carried out in animals, (3) cross-sectional studies, (4) scoping reviews, (5) narrative reviews, (6) systematic reviews, (7) conference abstracts, and (8) letters to editors.Regarding the selection process, after applying the search strategy to each database, the results were exported to the Rayyan QCRI program . After eThere was consensus among the authors in case of discrepancies about the inclusion/exclusion of an article at any stage of the selection process. We used a data extraction sheet built in Microsoft Excel for the data extraction. The following information was extracted from the selected articles independently by four authors : number of participants, year of publication, study design, population characteristics, and association or exposure measures.Quality assessment was evaluated with the Newcastle-Ottawa Scale (NOS)  independp value >0.1 was considered as indicative of no publication bias.The publication bias assessment was evaluated through funnel plots and the Egger test . A p valThe statistical analysis was performed using Review Manager 5.4 (RevMan 5.4)  and STATA Release 17.0 . Odds ratio (OR) and corresponding 95% conﬁdence intervals (CIs) were the only effective measures used. Values expressed as medians and their interquartile ranges (IQRs) were transformed into means and their corresponding standard deviations (SDs) using Hozo's method . Chinn's2 statistic and Cochran's Q statistic. For the I2 statistic, p values ≥60% were considered a sign of severe heterogeneity, and for the Cochran's Q test, p values <0.1 were considered a sign of heterogeneity. Subgroup analyses were carried out by study location. Sensitivity analyses were performed using only studies with a low risk of bias. A p value <0.05 was considered statistically significant.We performed a random-effects meta-analysis of the reported OR in all cases. The heterogeneity of the selected studies was analyzed using the IThe systematic search yielded 1325 records, and 820 duplicates were removed. According to the eligibility criteria, after excluding articles by title and abstract and assessing their full-text documents, 38 were identified as eligible for this systematic review –59. A PRCharacteristics from all included studies are summarized in Regarding the evaluation of the quality of the studies with the NOS, 13 studies were at a low risk of bias , and the remaining 25 studies were at a high risk of bias  (Supplementary n = 9951). We found that higher values of TC were associated with higher risk of developing DFU   and other countries subgroup  did not exhibit statistically significant associations. The Chinese studies subgroup  and Indian studies subgroup ; there was only a decrease in heterogeneity in the Chinese studies subgroup. Additionally, the sensitivity analysis showed a nonstatistically significant association but with reduced heterogeneity   . Due to 2 = 88%) . The Turn = 10982). We found that lower values of HDL were associated with a higher risk of developing DFU    . Due to 2 = 88%) . All subn = 15570). We found that higher values of LDL were associated with a higher risk of developing DFU  , Indian subgroup , and other countries subgroup . Turkish studies subgroup  was the only subgroup that kept the statistically significant association and showed a significant decrease in heterogeneity. The association was not statistically significant in sensitivity analysis but with low heterogeneity   . Due to 2 = 92%) . The stan = 11128). We found that higher values of TG were associated with a higher risk of developing DFU   and other countries subgroup  were the only ones that kept the association and showed a decrease in heterogeneity. In sensitivity analysis, the association remained, and the heterogeneity decreased significantly   . Due to 2 = 89%) . The Chin = 277). We found that higher values of Lp(a) were associated with a higher risk of developing DFU  . However, no statistically significant association was found between ApoB and risk of DFU  . However, no statistically significant association was found between ApoA1 and risk of DFU  . However, no statistically significant association was found between ApoB/ApoA1 ratio and risk of DFU  . However, no statistically significant association was found between high VLDL values and risk of DFU   were associated with the development of DFU. However, there were significant regional variations regarding these associations. Most of the studies showed a high risk of bias. Moreover, in the sensitivity analysis, only the association between HDL and TG with DFU remained statistically significant, with consistently less heterogeneity.Diabetic dyslipidemia (DD) is frequent, especially among patients with type 2 diabetes mellitus, where the prevalence is higher than 75% and is mainly mixed . DD is lDD is associated with a higher risk of cardiovascular events and peripheral vascular disease compared with subjects without diabetes, since it plays a central role in the genesis and progression of atherosclerosis –62. LikeThese data are relevant to our research because both neuropathy and peripheral vascular disease are involved in the development of DFU . In thisA previously published systematic review only included four studies . HoweverAlthough we have not evaluated the effect of nutritional status on our results, its influence on the lipid profile is well-known . In thisHowever, aspects such as the possible effect of gender of the patients included in the studies have not been considered. For example, a study in Chinese diabetic patients showed that the ApoB/ApoA1 ratio predicted cardiovascular disease risk in men. In contrast, TC, LDL, ApoB, LDL/HDL, and TC/HDL were better predictors in women . In addiOur study has several limitations. First, the studies did not adjust the values of the lipid markers with the confounding variables affecting the outcome under study. To avoid confounding bias, lifestyles, sociodemographic, and comorbidity variables should be considered and adjusted in future studies. Second, most of the studies have been carried out in the Asian continent, and very few have been found in other continents. Thus, it would be essential to analyze the value of these biomarkers in the risk of DFU in other latitudes. Third, high statistical heterogeneity was found due to the methodological and clinical differences between the studies. However, heterogeneity decreased when the sensitivity analysis was performed, which only included a low risk of bias studies. Finally, due to the lack of information in the studies, the values of sensitivity, specificity, and an optimal cutoff point of lipids for the risk of DFU were not estimated in a meta-analysis, so it should be addressed in future research.High values of LDL, TC, TG, and Lp(a) and low values of HDL are associated with a higher risk of developing DFU. Furthermore, we did not find a statistically significant association for VLDL, ApoA1, ApoB, and ApoB/ApoA1 ratio. However, primary studies are needed to define the optimal cutoff point for these biomarkers according to the profile of different diabetic populations worldwide.


Diet is a main source of acrylamide exposure to humans. Existing observational data on the relationship between dietary exposure to acrylamide and risk of cancer are inconsistent. We performed a systematic review and dose-response meta-analysis of epidemiological studies evaluating the association between dietary acrylamide exposure and several site-specific cancer. A systematic literature search was conducted in PubMed, Scopus, and Web of Science databases until March 7, 2022. Studies were eligible if they were carried out in non-occupationally exposed adults, assessed dietary acrylamide exposure (μg/day) and reported risk estimates of cancer incidence . Using a random-effects model, we performed a meta-analysis of site-specific cancer risk comparing the highest vs. lowest category of dietary acrylamide exposure. We also carried out a one-stage dose-response meta-analysis assessing the shape of the association. Out of 1,994 papers screened, 31 were eligible , which included 1,151,189 participants in total, out of whom 48,175 developed cancer during the median follow-up period of 14.9 years (range 7.3–33.9). The mean estimated dose of dietary acrylamide across studies was 23 μg/day. Pooled analysis showed no association between the highest vs. lowest dietary acrylamide exposure and each site-specific cancer investigated, with no evidence of thresholds in the dose-response meta-analysis. There were also no associations between dietary acrylamide exposure and the risk of cancers when stratifying by smoking status, except for increased risk of lung cancer in smokers. In conclusion, high dietary acrylamide exposure was not associated with an increased risk of site-specific non-gynecological cancer. Acrylamide is a chemical compound mainly used in industry to produce polyacrylamides that are employed for different purposes such as flocculants, dyes, paper, and textiles. Beside the potential exposure of acrylamide in the occupational setting, the main sources of exposure to this substance in the general population is through the intake of certain foods, high in carbohydrates cooked at temperatures >120°C, especially in low moisture conditions . TobaccoAcrylamide is classified as probably carcinogenic to humans (class 2A) by the International Agency for Research on Cancer (IARC) . Howeverin vitro and animal studies have consistently shown that acrylamide is genotoxic, mutagenic, and carcinogenic   and the Prospective and retrospective cohort, case-cohort and case-control studies performed in non-occupationally exposed adults (≥18 years) with acrylamide exposure assessed through diet were considered for inclusion. The included papers reported risk estimates  with corresponding 95% confidence intervals (CIs) for any type of cancer in relation to dietary acrylamide exposure, except for the female reproductive cancers (see section “Exclusion Criteria”). Regarding exposure, eligible studies reported acrylamide exposure as continuous and/or categories . We considered for inclusion studies reporting number of cases, participants, or person-years per dietary acrylamide category. Studies were included when estimates were adjusted at least for smoking status since smoking has been observed to increase the level of acrylamide, could covary with the consumption of foods high in acrylamide, and is a risk factor for many of the cancer forms under study.Studies investigating breast, endometrial or ovarian cancers were excluded, as these outcomes were part of a recently published dose-response meta-analysis .All references resulting from the search were downloaded and duplicates were removed. Titles and abstracts retrieved were independently screened for eligibility by two teams of two authors . Disagreements were solved by a third author (T.F.). In case of missing information for the meta-analysis, the corresponding author of the paper was contacted for clarification. If no additional information was gathered, the paper was excluded.Data from each selected paper were extracted by one of the research team members and independently checked by a second one . The following data were extracted: author, year of publication, type of study design, country including the geographical area, year of the baseline assessment, follow-up time, age, sex, smoking status, doses of acrylamide exposure , number of cases, number of participants, person-years, risk estimates, and list of the confounders which were adjusted for. The risk estimates with their 95% confidence intervals were extracted from the model adjusted for smoking and the greatest number of other covariables.The median or mean diet acrylamide exposure in each exposure category was assigned to the corresponding relative risk (RR), hazard ratio (HR), or odds ratio (OR). If the average intake in each category of exposure was not reported, the midpoint of the upper and lower boundaries of the category was assigned as the average intake. If the upper bound of the highest category or the lowest bound of the lowest category were not reported, they have been estimated using minus/plus 20% of the lower or higher open boundaries, respectively. For the RR reported for each quintile but with no respective intakes reported, the values were calculated under the assumption of a normal distribution using the mean, standard deviation, and zeta for each quintile considered (X-SD*Z quintile).Any site-specific cancer  previously investigated in relation to dietary acrylamide exposure was included in the analysis.The risk of bias was assessed by C.C., R.M., and A.V. using the Cochrane Collaboration tool for assessing risk of bias in non-randomized studies of interventions (ROBINS-I) . Risk ofWe employed a restricted maximum likelihood random-effects meta-analysis to assess summary RR along with 95% confidence interval (CI) for high dietary acrylamide exposure in comparison to low dietary exposure for each site-specific cancer, when at least two risk estimates were available on the same outcome.A dose-response meta-analysis of the association between dietary acrylamide exposure and site-specific cancer was performed using the one-stage approach recently employed in other research fields , 53. PotAdditional analyses were conducted stratifying by geographical area (West and East) due to potential differences in the dietary exposure to acrylamide across countries , and smoI2 statistic, and through the evaluation of the effect of variation across studies using a graphical overlay of study-specific predicted curves , primarily in the Netherlands (n = 8) and Sweden (n = 7), followed by Japan (n = 6) and the United States (n = 3). A total of 1,151,189 participants were included in these case-control, case-cohort, and cohort studies. Participants’ age ranged from 50 to 70 years (mean: 60 years). During a median follow-up period of 14.9 years (range: 7.3–33.9 years), 48,175 participants developed cancer. The following site-specific cancer were investigated in the papers in relation to dietary acrylamide exposure: oral cavity, esophageal, stomach, colorectal , pancreatic, laryngeal, lung, lymphoma, multiple myeloma, renal, bladder/urothelial, prostate, melanoma, and brain. Dietary acrylamide was assessed through food frequency questionnaires in all the analyzed studies. The mean and median estimated dose of dietary acrylamide across studies was 23 μg/day.Out of 1,994 papers retrieved through the literature and manual search, we identified 31 papers that met the inclusion criteria, corresponding to a total of 16 studies. Detailed information on the selection of the studies included is presented in Summary estimates for the association between highest vs. lowest dietary acrylamide exposure and the risk of various types of cancer in smokers and never smokers combined, and by smoking status, are shown in Results from the dose-response analysis showed a null association with no thresholds for all site-specific cancer considered in relation to increasing levels of dietary acrylamide , 3.There was also no association between dietary acrylamide and the risk of site-specific cancer in the subgroups of smokers and never smokers, except for lung cancer, where we observed an increased risk in smokers . Compared to smokers, the summary estimates for never smokers were observed to be higher, albeit very imprecise, for stomach, pancreatic, liver, renal, prostate, and multiple myeloma , 12, 14.n = 1)   could be performed only excluding Asian population  since most of the studies were performed in the West area (Europe and United States). We observed a slightly, though imprecise, increased risk of lymphoma in relation to high dietary acrylamide when we consider only study from the West (99–1.22) .I2 > 50%). The graphical overlay of single study effects in the dose-response meta-analysis did not show substantial variation (data not shown). No evidence of publication bias, visualized by funnel plots, was observed  when compared to the levels of acrylamide observed to be toxic in animal studies (50 mg/kg body weight/day) . There i in mice , i.e., m in mice  or subst in mice , 64.The findings related to the slightly increased risk of lymphomas in relation to high dietary acrylamide exposure restricted to the Western geographical region needs to be interpreted with caution as they are based on one single study  and combIn general, the similar results found in smokers and never smokers in our meta-analysis are in line with a previous meta-analysis . The resFirstly, we have performed an updated meta-analysis of the relationship between dietary acrylamide and the risk of several site-specific cancer. Compared to the previous meta-analyses, we were able to add some studies for several site-specific cancers, resulting in summary estimates with higher precision and accuracy.Secondly, we also investigated the shape of the relationship between acrylamide and site-specific cancer and we evaluated heterogeneity among some groups . However, for some outcomes, the results were still based on a very limited number of available studies.Our systematic review and meta-analysis have some limitations. They are based on epidemiological studies that assessed dietary acrylamide exposure through self-reported questionnaires. Hence, we cannot exclude that the summary estimates may be affected by misclassification of exposure related to the self-reported dietary intake , 69. MorAdditionally, for several of the studies included in the analysis stratified by smoking, doses of acrylamide by smoking status were not available and we used the doses indicated for the general population. Hence, the results on possible differences between smokers and non-smokers need to be carefully interpreted.Based on the results of this dose-response meta-analysis of epidemiological studies, higher dietary acrylamide exposure (vs. lower) was not associated with an increased risk of several site-specific cancers. If associations between dietary acrylamide and the risk of several site-specific cancers were present, the shape of the dose-response relationships would be with no thresholds. Smoking status might modify the relation between dietary acrylamide and some site-specific cancers, but findings need to be furtherly investigated.The original contributions presented in the study are included in the article/TF, TH, AV, and FL conceptualized the study and drafted the manuscript. TF performed the statistical analyses. All authors contributed substantively to this work, involved in the interpretation of results, editing of the manuscript, and approved manuscript submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This is the first meta-analysis that assessed the association between maternal smoking and the risk of placenta accreta spectrum (PAS), so this study was aimed at investigating the association between maternal smoking and PAS based on observational studies. PAS is defined as a severe obstetric complication due to the abnormal invasion of the chorionic villi into the myometrium and uterine serosa. I2 statistic were used to assess heterogeneity. Egger's and Begg's tests were used to examine the probability of publication bias. All statistical analyses were performed at a significance level of 0.05 using Stata software, version 11.  We searched electronic bibliographic databases including PubMed, Web of Science, Scopus, Science Direct, and Google Scholar until January 2022. The results were reported using a random effect model. The chi-square test and the I2 = 4.7%). Subgroup analysis was conducted based on study design, and the result showed that the association between smoking and PAS among cohort studies was significant 1.35 .  Based on the random effect model, the estimated OR of the risk of PAS associated with smoking was 1.21  was used to measure study quality. Placenta accreta spectrum (PAS), formerly known as adherent placenta, is a term used to describe the abnormal attachment of placental trophoblasts to the uterine myometrium and includes placenta accreta (placenta attachment to myometrium without decidua intervention), increta placenta (trophoblast invasion to myometrium), and percreta placenta (invasion through the myometrium is serous and into the surrounding structures) .The importance of this disease is due to the increase in maternal and fetal mortality. Fetal outcomes are mainly due to iatrogenic prematurity, while maternal outcomes are mainly due to increased risk of postpartum hemorrhage and surgical complications. The average blood loss is 3000-5000 ml, and up to 90% of patients need a blood transfusion . ComplicDiagnosis of the PAS is based on two main clinical and pathological criteria. After delivery, the placenta usually separates spontaneously, and any difficulty in separating the placenta or the need for placental abruption is considered a clinical criterion for the PAS. Another clinical criterion is uncontrollable bleeding from the placenta after delivery or cesarean section . PrenataIn the umbrella review of Jenabi et al., multiple gestation and in vitro fertilization (IVF) were identified as definitive risk factors ; also, iThe role of smoking in some diseases is also known such as esophageal cancer  and hypePopulation: pregnant womenIntervention: smoking before and during pregnancyComparison: without smoking before and during pregnancyOutcome: risk of placenta accreta spectrumThe checklist of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used for performing the present meta-analysis. Investigating the association between maternal smoking and risk of PAS was performed regarding to the following PICO framework:Observational studies (case-control and cohort) reporting the association between smoking and the risk of PAS were reviewed, irrespective of language, maternal age, race, country, date, and place of publication.The search strategy was based on combining a set of keywords  and (“Smoking” or “cigarette” or “tobacco” or “cigar”). We searched electronic bibliographic databases including PubMed, Web of Science, Scopus, Science Direct, and Google Scholar until January 2022. To find additional references, we screened the reference lists of the included studies. In addition, we contacted authors of the studies to earn eligible studies, and conference databases were searched.Two authors independently reviewed the articles to ensure that they met the meta-analysis inclusion criteria. Any disagreements among the authors were resolved by discussion. The two authors extracted information from the included articles. The information was the first author's name (year), country, study design, age (year), sample size, and the effect measure and its 95% confidence interval (CI). The Newcastle-Ottawa Scale (NOS) was used to measure study quality . A studyI2 statistic were used to assess heterogeneity [The chi-square test and the ogeneity . Egger'sogeneity  and Beggogeneity  tests weOdds ratio (OR), with their associated 95% CIs, were applied to present the measures of association between maternal smoking and PAS. We used the adjusted forms of the ORs, controlling for at least one of the potential confounding factors. The results were reported using a random effect model. We conduct a subgroup analysis based on study design and crude/adjust form. All statistical analyses were performed at a significance level of 0.05 using Stata software, version 11 .Until 30 January 2022, 321 studies were included in the present meta-analysis. Of these, 176 were excluded due to duplication and 145 studies remained for assessing title and abstract. Then, 128 studies were excluded after reading titles and abstracts. In total, 17 studies were remained for reading the full papers. Three full papers were not considered to be eligible (four studies were reviewed and three studies had no inclusion criteria). In the end, 14 studies were included in the current meta-analysis . We idenI2 = 4.7%). The finding of Farquhar's study ['s study  was repop values for Begg's and Egger's regression were 0.656 and 0.439, respectively. Evidence of publication bias was not seen among studies showing the association between smoking and PAS in Publication bias was carried out using Begg's and Egger's tests. The I2 = 0.0%), but this association among case-control studies was not significant 0.83 . In addition, there was no significant association between smoking and PAS based on crude/adjust form  was significantly associated with placenta accreta, indicating the potential role of PIGF in identifying high-risk pregnancies for placenta accreta .2.5) was associated with placenta inflammation [Several studies have shown that smoking causes hypercoagulability and increased risk of thrombosis, and during pregnancy, due to physiological adaptation, the hemostatic system presents as a relatively hypercoagulable state with decreased anticoagulation function; however, studies in women with PAS have shown that they have hypocoagulability and hyperfibrinolysis ; therefoammation . Therefoammation .According to Tsuji et al., cadmium and lead levels in pregnant women with PAS were higher than normal pregnancies, and it is possible that increased cadmium levels play a role in the pathogenesis of PAS . SmokingThis study has some limitations. In our meta-analysis, diagnosis of PAS was most by clinicians, and pathology reports were not obtained from all cases. Therefore, most of the PAS cases in this study were clinically diagnosed. In addition, some of the included studies in our meta-analysis adjusted for confounding variables. This was another limitation of this study. Also, all studies did not investigate the effect of smoking on the PAS in trimesters of pregnancy, separately. Therefore, we did not conduct a subgroup analysis based on time smoke use during pregnancy.One of the strengths of this study is the homogeneity of the studies included in the meta-analysis and their high quality; also, the present meta-analysis with 3,892,832 participants reported that maternal smoking is a risk factor for the PAS.PAS is becoming increasingly common and is associated with significant morbidity and mortality. Knowledge of risk factors can help prevent and diagnose early. Our results suggested that maternal smoking is a risk factor for the PAS; also, there was no heterogeneity among studies that reported an association between smoking and the PAS.


Background: Several meta-analyses have analyzed the association of GSTM1 present/null, GSTT1 present/null, and GSTP1 IIe105Val polymorphisms with leukemia risk. However, the results of these meta-analyses have been conflicting. Moreover, they did not evaluate the combined effects of the three aforementioned gene polymorphisms. Furthermore, they did not appraise the credibility of the positive results. Finally, many new studies have been published. Therefore, an updated meta-analysis was conducted.Objectives: To further explore the relationship of the three aforementioned gene polymorphisms with leukemia risk.Methods: The crude odds ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the association of the individual and combined effects of the three aforementioned genes. Moreover, the false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) were applied to verify the credibility of these statistically significant associations.Results: Overall, the individual GSTM1, GSTT1, and GSTP1 IIe105Val polymorphisms added leukemia risk. On combining GSTM1 and GSTT1, GSTM1 and GSTP1, and GSTT1 and GSTP1 polymorphisms, positive results were also observed. However, no significant association was observed between the combined effects of these three polymorphisms with leukemia risk in the overall analysis. Moreover, when only selecting Hardy–Weinberg equilibrium (HWE) and medium- and high-quality studies, we came to similar results. However, when the FPRP and BFDP values were applied to evaluate the credibility of positive results, the significant association was only observed for the GSTT1 null genotype with leukemia risk in Asians .Conclusion: This study strongly suggests a significant increase in the risk of leukemia in Asians for the GSTT1 null genotype. Leukemia is a cancer of hematology, characterized by abnormal hematopoietic function and malignant cloning of white blood cells. Leukemia includes acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myeloid leukemia (CML), and chronic lymphoblastic leukemia (CLL) . Over thGSTM1 and GSTT1 (null genotypes) can result in the complete absence of GSTM1 and GSTT1 enzyme activities; the former is located on chromosome 1 (1p13.3) and the latter is situated at chromosome 22 (22q11.2)  to valine , thereby giving rise to decreased enzymatic activity  is a kind of phase II enzyme which includes M1, P1, and T1; the main functions of the three aforementioned genes were the metabolism of xenobiotics, reactive oxygen species, and carcinogens for detoxification and metabolism . A parti22q11.2) . GSTP1 gactivity . Previouactivity . The GSTactivity .GSTM1 present/null, GSTT1 present/null, and GSTP1 IIe105Val polymorphisms with leukemia risk. However, results of these meta-analyses were conflicting. Moreover, they did not evaluate the combined effects of the three aforementioned gene polymorphisms. Furthermore, they did not appraise the credibility of the positive results. Finally, many new studies have been published. Therefore, an updated meta-analysis was conducted.Several meta-analyses analyzed the association of Five databases including PubMed, Embase, Web of Science, CNKI, and WanFang were applied to search the literature . The following retrieval strategy was employed: (glutathione S-transferase M1 OR GSTM1 OR glutathione S-transferase T1 OR GSTT1 OR glutathione S-transferase P1 OR GSTP1) AND  AND (leukemia OR leukaemia). Furthermore, if necessary, we contacted the corresponding authors by e-mail.The studies that met the following criteria were included: 1) case-control or cohort study, 2) genotype data or odds ratio (OR) with 95% confidence interval (CI) provided, and 3) investigation of the association of the three aforementioned gene polymorphisms with the risk of leukemia. Studies such as overlapping data, case reports, editorials, reviews, letters, and meta-analyses were excluded.GSTM1 and GSTT1 null genotypes, we considered studies that scored ≥10 as high quality; for GSTP1 IIe105Val, studies scoring ≥12 were deemed as high quality.Information was extracted and checked by two researchers from all selected studies. Any disagreement was solved through discussion. Extracted information in shown in 2 value were carried out to evaluate heterogeneity  polymorphisms and leukemia risk. The Q statistic and Iogeneity . Only a t models . We perft models . Sensitinel plot  and Eggenel plot  were carnel plot , BFDP  vs. T1 present/P1 IIe/IIe: OR = 1.50, 95% CI = 1.04–2.15; T1 null/P1 Val* vs. T1 present/P1 IIe/IIe: OR = 4.24, 95% CI = 2.49–7.24; all risk genotypes vs. T1 present/P1 IIe/IIe: OR = 1.70, 95% CI = 1.30–2.22; and T1 null/P1 Val* vs. : OR = 3.31, 95% CI = 1.85–5.91) and increased risk of leukemia among Indians  vs. T1 present/P1 IIe/IIe: OR = 1.65, 95% CI = 1.05–2.59; T1 null/P1 Val* vs. T1 present/P1 IIe/IIe: OR = 4.39, 95% CI = 2.51–7.68; all risk genotypes vs. T1 present/P1 IIe/IIe: OR = 1.91, 95% CI = 1.45–2.50; T1 null/P1 Val* vs. : OR = 3.39, 95% CI = 1.94–5.94; No significantly increased leukemia risk was observed in the three combined polymorphisms in the overall populations .p = 0.000) and quality score (p = 0.038) were sources of heterogeneity for the GSTM1 null genotype. For GSTP1 IIe105Val polymorphism, in Val/Val vs. IIe/IIe + IIe/Val, type of controls (p = 0.002), matching studies (p = 0.023), and HWE (p = 0.005) were the heterogeneity sources. Similar results were observed in Val/Val vs. lle/lle + lle/Val where type of controls (p = 0.001), matching studies (p = 0.037), and HWE (p = 0.007) were the sources of heterogeneity. For the combined GSTM1 and GSTT1 polymorphisms, the sample size (model 1: p = 0.015) was the source of heterogeneity , second, FPRP <0.2 and BFDP <0.8, third, I2 < 50%, and fourth, statistical power >80%. GSTM1, GSTT1, and GSTP1 IIe105Val polymorphisms with the risk of leukemia. Only the GSTT1 null genotype with leukemia risk in Asians was considered as “positive” results . All other important connections were regarded as less-credible results, also shown in The “reliable results” was defined as the positive results that met the following criteria . First, GSTM1, GSTT1, or GSTP1 polymorphisms brought about diminished gene expression and enzymatic activity  and medium and high-quality studies, we had come to a similar conclusion. Finally, in view of the quantities of genomic data being produced currently, we used a more exact Bayesian measure of false-positive found in genetic epidemiological studies in the present study. Using FPRP and BFDP to correct the positive results, in all of these positive results we found previously, only the association between GSTT1 null and leukemia risk was watched in ethnicity . Our results indicated that the false-positive associations were common between SNP and disease risk. Moreover, these results further confirmed that the occurrence of leukemia was the result of multiple genes.Overall, the present study showed that the GSTM1, GSTT1, and GSTP1 polymorphisms and the risk of leukemia. GSTM1 and GSTT1 null genotypes and the risk of leukemia, and their results suggested that there was a significant association between GSTM1 and GSTT1 polymorphisms and leukemia risk. The studies of GSTM1 null genotypes increased the risk of acute leukemia. The results of GSTP1 polymorphism with the risk of leukemia; however, GSTP1 polymorphism and the risk of leukemia, and the results showed that there was no significant connection. The number of studies and sample sizes in the current study were larger than the published meta-analyses. When comparing to the present meta-analysis, previous studies had several defects. First, none of the previous studies performed quality assessments. Second, HWE was not reported in any published meta-analysis. Third, all previous meta-analyses did not adjust the positive results for multiple comparisons, and only five previous meta-analyses  We explored the credibility by applying the Venice criteria, FPRP, and BFDP. 2) The qualified studies were evaluated for quality. 3) The sample size was larger and the data collected were more detailed over the previous meta-analyses. 4) We conducted more subunit analyses, such as ethnicity, age group, type of control, matching or not, type of leukemia, quality score, and HWE. 5) We established a more complete genetic model. 6) Our study is the first one to explore the combined effects of This meta-analysis strongly suggests that only a minority of meaningful associations are credible results. Hence, larger-scale investigations of this topic should be performed in the future to verify or rebut our findings.


This study aims to explore the association between dietary acid load and hyperuricemia in Chinese adults.A case-control study was conducted. Adult participants with hyperuricemia were recruited as the cases and those without hyperuricemia were as the controls. Food consumption was evaluated by food frequency questionnaire (FFQ). Dietary acid load was assessed by potential renal acid load (PRAL) and net endogenous acid production (NEAP). Dietary acid load was divided into four levels: the first quartile (Q1), the second quartile (Q2), the third quartile (Q3) and the fourth quartile (Q4). Logistic regression model was applied for exploring the association between dietary acid load (PRAL and NEAP) and hyperuricemia. Odds ratio (OR) and its correspondence confidence interval (CI) were computed.p-value: 0.004), 2.90  and 3.14 , respectively. There was a positive association between elevated NEAP and hyperuricemia. OR of hyperuricemia for Q2 was not material significance , however, ORs of hyperuricemia for Q3  and Q4  were statistically significant.A total of 290 participants were eligible in this study, in which there were 143 individuals in case group and 147 in control group. A higher level of PRAL was found to be associated with odds of hyperuricemia. ORs of hyperuricemia for Q2, Q3 and Q4 of PRAL were 2.74 (95%CI: 1.94 ~ 3.88, Higher level of dietary acid load was found to be associated with hyperuricemia in Chinese adults, indicative of advocation of a well-balanced diet in this population. Hyperuricemia is characterized by abnormally high serum uric acid, and it may lead to deposition of sodium urate crystal, especially in arthrosis, if without any treatments . The lonPrevalence of hyperuricemia varies in different ethnic groups, countries and territories, and it shows a positive correlation between economic growth and the prevalence of hyperuricemia . A prevaA variety of factors contribute to the long-run increase of hyperuricemia in Chinese adults, and diet pattern modification in the last decades might be the most important one , 17. TheThis study was based on case-control design. Participants were recruited from Wenzhou hospital of traditional Chinese medicine affiliated to Zhejiang Chinese medicine university in a period from January 2017 to December 2021. Participants diagnosed with hyperuricemia were included in case group and should also meet the following criteria: (1) with an age > 18 years; (2) with basic communication capability and memory; (3) without cancer, neuropsychological diseases, diabetes and gastrointestinal diseases, as these diseases have large impact on food pattern; (4) the food pattern was not largely changed in last 12 months. Almost the same number of participants without hyperuricemia were included in the control group. Male proportion and age distribution in the control group were similar to the case group, while other eligible criteria for the control group were also in accord with the case group. This study was performed in line with the principles of the Declaration of Helsinki, and approved by the Ethical Committee of Wenzhou hospital of traditional Chinese medicine affiliated to Zhejiang Chinese medicine university. Informed consent was obtained from all individual participants included in the study.Anthropological data and health-related information were derived from electronic patient record. Anthropological data included age, gender, weight (kg), height (cm) and body mass index (BMI). Health-related information included diastolic blood pressure (mmHg), systolic blood pressure (mmHg), heart rate (beats/minutes), serum uric acid (μmol/L), smoking, drinking and chronic diseases. Smoking statues were divided into current smoking, ever smoking and never smoking. Ever smoking was defined as those who quit smoking for more than 12 months. Alcohol drinking statues were classified as current drinking, ever drinking and never drinking. Ever drinking was defined as those who quit drinking for more than 12 months. The list of chronic diseases was as follows: hypertension, coronary heart disease, osteoporosis, chronic obstructive pulmonary disease， chronic kidney disease and hyperlipidemia. These chronic diseases required a clear clinical diagnosis, and self-reporting was not considered in this study as the lack of uniform standards of diseases assessment from different participants.We used a Chinese general criterion to diagnose hyperuricemia in this study. Hyperuricemia for men was defined as fasting serum uric acid > 420 μmol/L in two separate days, and for women was > 360 μmol/L.  In additA validated food frequency questionnaire (FFQ) was applied for food consumption survey. Briefly, FFQ in this study was adapted from China Health and Nutrition Survey which is an ongoing open cohort and designed to examine the effects of the health, nutrition status and other factors on the study population . Given tPRAL (mEq/d) =0.4888 × protein intake (g/d) + 0.0366 × phosphorus (mg/d) - 0.0205 × potassium (mg/d) - 0.0125 × calcium (mg/d) - 0.0263 × magnesium (mg/d);NEAP (mEq/d) = (54.5 × protein intake (g/d) ÷ potassium intake (mEq/d))-10.2In order to compute daily nutrient intake, the related data from the Chinese food composition table (2012 version) were used. Energy intake and three macro-nutrients including carbohydrate, fat and protein were calculated. In order to evaluate dietary acid load (PRAL and NEAP), additional nutrients including sodium, magnesium, phosphorus, magnesium and calcium were also computed. According to previously studies , PRAL an2 test, student’s test or Wilcoxon rank sum test. Logistic regression model was applied to assess the association between dietary acid load (PRAL and NEAP) and the odds of hyperuricemia. Dietary acid load was divided into four level: the first quartile (Q1), the second quartile (Q2), the third quartile (Q3), and the fourth quartile (Q4), in which each group has an approximately same number of participants. Q1 was considered as a reference group and odd ratios (ORs) and the correspondent confidence intervals (CIs) of Q2, Q3 and Q4 were computed. Additionally, possible risk factors, such as age and sex, as well as multiply variables  were put in the Logistic regression model to obtain adjusted effects. Statistical analysis was conducted in R language . Forest plots were produced based on R language software package named FORESTPLOT. In this study, a p-value < 0.05 was perceived as statistical significance.Variables on discrete distribution were as number and proportion, while if variables on continuous distribution were in accord with normal distribution than they were exhibited as mean and standard deviation (SD), otherwise were exhibited as median and range interquartile (IQR). Variable difference was evaluated by χp-value < 0.05). Characteristic of participants was summarized in Table A total of 290 participants were eligible in this study, in which there were 143 cases (diagnosed with hyperuricemia) and 147 controls (without hyperuricemia). Participant selection was exhibited in flowing chart . Fish consumption in case group were material higher than in control group . In terms of other food groups including grains, potato, soy, red meat, poultry, dairy, egg, beverages and edible oil, there were lack of significant differences between participants in case group and control group, shown in Table As respect to food groups, vegetable consumption and fruit consumption in the case group were material lower than in the control group , 2.90  and 3.14 , respectively and p-value for trend was < 0.001. The positively significant associations were remained after adjusting for age and sex, or for multiple variables, shown in Table Higher PRAL was found to be associated with hyperuricemia. Crude ORs of hyperuricemia for Q2, Q3 and Q4 of PRAL were 2.74 , however, ORs of hyperuricemia for Q3  and Q4  were statistically significant. P-value for trend was < 0.001 indicative of a dose-response relationship between NEAP and hyperuricemia. After adjusting for age and sex, or for multiple variables, the positive associations did not fluctuate largely, shown in Table There was a positive association between elevated NEAP and hyperuricemia. Crude OR of hyperuricemia for Q2 was not material significance (OR:1.54, 95%CI: 0.93 ~ 2.53, To our best understanding, this is the first study to explore the association between dietary acid load and hyperuricemia in mainland China. Results from the current study showed a positive association between higher dietary acid load and hyperuricemia. We applied two assessment indicators of dietary acid load including PRAL and NEAP, and the results were consistent. Our results were relative robustness as they were lack of large fluctuations after adjusting a broad of possible risk factors as we could. Since the prevalence of hyperuricemia in Chinese adults is increasing continuously, advocation of well-balanced diet is urgently needed to prevent and control the disease. In addition, we also identified vegetable and fruit consumption were lower in participants with hyperuricemia, but fish consumption higher. Patients with hyperuricemia should eat more vegetable and fruit but less rich-purines foods, such fish, on the premise of dietary diversity.According to previous reports, high dietary acid load is characterized by both a high consumption of acid precursors and a low intake of base precursors . Acid prOther studies also exhibited a positive relationship between higher dietary acid load and risk of hyperuricemia. Dayeon et al. , found ap-value for trend according to Logistic regression analysis in different group divided by level of dietary acid load, analysis of dose-response relationship was not available as the limited number of participants in this study.There are some limitations in this study which should be notably taken into consideration. Firstly, this study was based on case-control design, which cannot avoid biases, such as recalling bias. Food consumption frequency and amount of some kinds of food might exist deviations with reality or error reporting, in particular in the senior citizens who had impaired memory. FFQ including 12 food groups was applied for food consumption survey, while there must be large bias of the estimation of nutrients intake as the nutrients content of specific foods within the same group may vary greatly, causing inaccurate estimates of nutrients. Secondly, a case-control study could only provide clues to the cause of hyperuricemia and cannot draw a causal conclusion. Thirdly, only adult participants were included in this study, indicative of limited extrapolation of the results. Hyperuricemia is commonly acknowledged as a chronic disease. Even though the age of onset of hyperuricemia trends to be younger, the majority of cases are still among adults, especially those middle-aged and elderly group. Fourthly, the dose-response relationship between dietary acid load and hyperuricemia was less understood. Although we gave Two aspects should be noted in the future study. The first one is that prospective studies are urgently needed to verify the association between dietary acid load and the risk of hyperuricemia and its possible mechanisms should be also uncovered. The second one is that dose-response relationship between dietary acid load and hyperuricemia should be further studied.This study based on case-control design identified a significantly positive association between higher dietary acid load and the odds of hyperuricemia in Chinese adults. Both of PRAL and NEAP had consistent results, indicative of advocation of a well-balanced diet in Chinese population. Given the limitation of case-control study, further prospective studies with large population are urgently needed.


To explore the association between ovulation induction drugs and ovarian cancer.Systematic review and meta-analysis.Not applicable.Women without ovarian cancer who ever or never underwent ovarian induction.An extensive electronic search of the following databases was performed: PubMed, EMBASE, MEDLINE, Google Scholar, Cochrane Library and CNKI, from inception until January 2022. A total of 34 studies fulfilled our inclusion criteria and were included in the final meta-analysis. The odds ratio (OR) and random-effects model were used to estimate the pooled effects. The Newcastle-Ottawa Scale was used to assess the quality of included studies. Funnel plots and Egger tests were used to assess publication bias.New diagnosed borderline ovarian tumor (BOT) and invasive ovarian cancer (IOC) between ovulation induction (OI) group and control (CT) group considering fertility outcome, OI cycles and specific OI drugs.Primarily, there was no significant difference in the incidence of IOC and BOT between the OI and CT groups. Secondly, OI treatment did not increase the risk of IOC and BOT in the multiparous women, nor did it increase the risk of IOC in the nulliparous women. However, the risk of BOT appeared to be higher in nulliparous women treated with OI treatment. Thirdly, among women exposed to OI, the risk of IOC and BOT was higher in nulliparous women than in multiparous women. Fourthly, the risk of IOC did not increase with increasing OI cycles. Lastly, exposure to specific OI drugs also did not contribute to the risk of IOC and BOT.Overall, OI treatment did not increase the risk of IOC and BOT in most women, regardless of OI drug type and OI cycle. However, nulliparous women treated with OI showed a higher risk of ovarian cancer, necessitating their rigorous monitoring and ongoing follow-up.The online version contains supplementary material available at 10.1186/s13048-022-01084-z. Infertility affects more than 48.5 million couples worldwide –3. It isThe PRISMA guidelines were used for this study. A systematic literature search was then conducted in PubMed, EMBASE, MEDLINE, Google Scholar, Cochrane Library and CNKI, which included records up to January 2022. The main keywords included the following domains of Medical Subject Heading terms: “ ovulation induction “ and “ ovarian cancer “. The retrieval strategy adopted the combination of subject terms and free words. These terms were then combined with “AND” or “OR”. Also, to broaden the search, review articles were used to ensure that all relevant citations were identified and imported.Two independent researchers (YL and WQQ) simultaneously screened the titles, abstracts and full text of the literature according to the inclusion and exclusion criteria. Any disagreements were discussed and solved by consensus or third-party arbitration (ZS). The inclusion criteria were as follows: (1) Cohort studies and case-control studies with adequate samples; (2) Exposure to ovulation induction drugs such as clomiphene citrate (CC), gonadotrophin (GDT) and gonadotropin-releasing hormone analogs (GnRH-a); (3) Follow-up in the cohort study was sufficiently long to demonstrate treatment differences; (4) The study had a clear description of the exposure to OI drugs and essential information about enrolled patients;(5) The type of cancer included borderline ovarian tumor (BOT) or invasive ovarian cancer (IOC). The exclusion criteria were as follows: (1) Non-English or Non-Chinese literature; (2) Non-human studies; (3) Literature with incomplete data; (4) Duplicate and inaccessible literature.Two independent researchers (YL and SJF) performed the data extraction after viewing the complete manuscripts of the eligible literature. Relevant data was input into separate spreadsheets and then cross-checked by each researcher to maintain the quality of the data. The data of bibliography (year and author), study design , outcome measures  and other endpoint evaluation  were extracted from each study. If necessary, discussions with the third-party arbitration (XW) would solve all disputes.Two researchers (YL and YWN) independently assessed the quality of the literature by using the NOS scale . The main components of the NOS scale included: patient selection, intergroup comparability and outcome measurement . DisagreP < 0.05 was regarded as statistically significant.The meta-analysis was performed by using STATA 12.0. Binary variables were evaluated by odds ratio (OR) and its 95% confidence interval (95% CI). 2 value less than 50% were deemed to be low heterogeneity, 51–75% were deemed to be moderate heterogeneity, and greater than 75% were deemed to be high heterogeneity [2 value exceeded 50%, the random-effect model was chosen. Otherwise, if the I2 value was less than 50%, both the random effects and fixed effects models were acceptable [Depending on heterogeneity, the appropriate model (random or fixed) was then selected to merge the outcome indicators . The I2 ogeneity . If the ceptable .In principle, funnel plot analyses were performed to accompany meta-analyses involving more 10 studies and to judge the publication bias . If therThis meta-analysis was based on the data from published articles and independent of any patient participation. As such, institutional review board (IRB) approval was not required.A flowchart detailing the process of identification and inclusion for the target literature was shown in Supplemental Material Fig. Of the 34 studies, 12 reported BOT –30 and 32 = 54.9%, Table 2 = 73.4%, Table In the subgroup analysis of case-control studies, 12 studies reported IOC , 36–43 a2 = 21.8%, Table 2 = 50.5%, Table In the subgroup analysis of cohort studies, 18 studies reported IOC , 44–51 aIn this section, we sought to find out whether the multiparous and nulliparous women treated with OI presented an increased risk of ovarian tumors when compared to those who had not been treated with OI. Relevant data were presented in Supplemental Material Table 2 = 21.3%, Table 2 = 73.5%, Table Firstly, 10 studies of IOC –42, 50 a2 = 69.5%, Table 2 = 0%, Table In the second part, 8 studies of IOC , 40–42 a2 = 52.2%, Table 2 = 0%, Table In this chapter, we attempted to figure out the differences in cancer risk between the multiparous and nulliparous woman in the OI group. Relevant data were presented in Supplemental Material Table Then, we tried to find out whether cancer risk increased with more OI cycles. Totally, 8 studies provided relevant data for IOC , 46, 47.2 = 42.9%, Table 2 = 0%, Table 2 = 0%, Table 2 = 0%, Table 2 = 0%, Table 2 = 0%, Table Using a cut-off of 3 cycles, we did not find a higher cancer risk in those women who received less than 3 cycles when compared to the CT group , the gonadotrophin group (GDT) and the gonadotropin-releasing hormone analog group (GnRH-a). Relevant data were provided in Supplemental Material Table = 1.01, 95%CI: 0.88–1.17, I2 = 0%, Table 2 = 72.6%, Table We firstly analyzed the relationship between CC and cancer risk. This part of analysis included 17 studies of IOC , 50, 51 2 = 71.6%, Table 2 = 34.7%, Table 2 = 0%, Table Secondarily, we focused our attention on GDT and performed a subgroup analysis in this section. GDTs mainly consisted of human menopausal gonadotropin (HMG) and human chorionic gonadotropin (HCG). However, some studies did not further categorized GDT. For IOC, there were 5 studies of HMG , 41, 47,2 = 83.3%, Table 2 = 56%, Table 2 = 54.1%, Table While for BOT, 2 studies of HMG , 29, 2 s2 = 71.9%, Table Thirdly, we only found 2 studies which provided analyzable data on the relationship between the risk of IOC and GnRH-a , 47. AloIn our analysis, funnel plot analysis and Egger regression analysis were performed to judge the publication bias of the included studies. Neither the funnel plot  the incessant ovulation hypothesis stated that ovarian epithelium could be destroyed and repaired during uninterrupted ovulation. When a sufficient amount of damage is caused, malignant transformation of ovarian epithelial cells will be triggered . FurtherResearch in this area was based on cohort studies, case series and case-control studies. And, there were still no randomized controlled trials regarding the relationship between ovulation inducing drugs and ovarian cancer due to ethical issues, the relatively low incidence of ovarian cancer and recall bias after ovulation induction . This upBOTs are morphologically similar to IOCs and follow a similar pathogenesis , 74. As In addition, during the review of the literature, we found several studies supporting that OI treatment could induce an increased risk of ovarian cancer in the nulliparous women , 12. A cRodriguez et.al previously found that infertility itself might increase ovarian cancer risk without concomitant exposure to OI drugs . A curreIndeed, it would be arbitrary to diagnose the relationship between OI and ovarian cancer solely based on the history of OI exposure. According to incessant ovulation hypothesis, more ovulatory cycles appeared to be associated with a higher risk of developing ovarian cancer , 99, 100In accession, several studies had reported the risk of individual ovarian cancers due to specific OI drug exposure , 29, 101Most of our findings were generally consistent with previous studies on this topic , 108. A This study included 34 studies from around the world and provided an up-to-date meta-analysis to explore the potential impact of OI treatment on ovarian cancer risk. The inclusion and exclusion criteria for this systematic review and meta-analysis had been made more rigorous. In addition, the included studies were updated and the process of meta-analysis was made more rigorous. In our analysis, lessons learned from previous studies were incorporated and further subgroup analyses were conducted based on study type, tumor type, parity, OI cycle and specific OI drugs. Of note, this meta-analysis was the first study to evaluate the relationship between the OI cycles and ovarian cancer.However, our study still had some objective shortcomings. Firstly, further work should focus more attention on patient demographics and specific data including drug combinations, cycles of use, use dosage and administration methods. Secondly, loss of follow-up existed in included studies in our analysis and retrospective studies were always considered to be lower quality evidence due to the presence of recall bias. We needed more large and long-term prospective cohort studies with careful follow-up. Thus, follow-up process needed to be improved. Last but not least, the formation of symbiotic relationships between cancer registries and fertility services should be encouraged to link fertility data with cancer information. Communication and collaboration between fertility services should also be encouraged in order to collect adequate data. We believe that further exploration in this area will facilitate the further development of reproductive science.OI treatment did not increase risk of ovarian cancer, regardless of treatment regimen and treatment cycle. However, nulliparous women treated with OI might have an increased risk of BOT compared to the nulliparous women not treated with OI. Meanwhile, nulliparous women treated with OI appeared to have a higher risk of IOC and BOT than multiparous women treated with OI. In view of the above, OI treatment was relatively safe but those nulliparous women treated with OI must be followed up rigorously.Additional file 1: Supplemental Material Fig. 1. The flowchart of systematic search and screening process.Additional file 2: Supplemental Material Fig. 2. (A) Funnel plot of all the included studies; (B) Egger’s regression test of all the included studies.Additional file 3: Supplementary Table S1a. Quality evaluation of case-control study assessed by the Newcastle-Ottawa Scale. Supplementary Table S1b. Quality evaluation of cohort study assessed by the Newcastle-Ottawa Scale.Additional file 4: Supplementary Table S2. ovarian cancer study characteristics.Additional file 5: Supplementary Table S3a. Ovarian tumor in the nulliparous women. Supplementary Table S3b. Ovarian tumor in the multiparous women.Additional file 6: Supplementary Table S4. Ovarian tumor between the nulliparous and multiparous group.Additional file 7: Supplementary Table S5a. Ovarian tumor and stimulation cycles(< 3 cycles). Supplementary Table S5b. Ovarian tumor and stimulation cycles(≥3 cycles). Supplementary Table S5c. Ovarian tumor and stimulation cycles(< 6 cycles). Supplementary Table S5d. Ovarian tumor and stimulation cycles(≥6 cycles). Supplementary Table S5e. Ovarian tumor and stimulation cycles(< 12 cycles). Supplementary Table S5f. Ovarian tumor and stimulation cycles(≥12 cycles).Additional file 8: Supplementary Table S6a. Ovarian tumor in women who ever received CC. Supplementary Table S6b. Ovarian tumor in women who ever received HMG. Supplementary Table S6c. Ovarian tumor in women who ever received HCG. Supplementary Table S6d. Ovarian tumor in women who ever received GDT. Supplementary Table S6e. Ovarian tumor in women who ever received GnRH-a.Additional file 9: Supplementary Table S7. Sensitivity analyses for the novel study during this update.


Sudden cardiac death (SCD) is a global public health issue, accounting for 10–20% of deaths in industrialized countries. Identification of modifiable risk factors may reduce SCD incidence.This umbrella review systematically evaluates published meta-analyses of observational and randomized controlled trials (RCT) for the association of modifiable risk and protective factors of SCD.Fifty-five meta-analyses were included in the final analysis, of which 31 analyzed observational studies and 24 analyzed RCTs. Five associations of meta-analyses of observational studies presented convincing evidence, including three risk factors  and two protective factors [implanted cardiac defibrillator (ICD) and physical activity]. Meta-analyses of RCTs identified five protective factors with a high level of evidence: ICDs, mineralocorticoid receptor antagonist (MRA), beta-blockers, and sodium-glucose cotransporter-2 (SGLT-2) inhibitors in patients with HF. On the contrary, other established, significant protective agents , did not show credibility. Likewise, risk factors as left ventricular ejection fraction in HF, and left ventricular hypertrophy, non-sustain ventricular tachycardia, history of syncope or aborted SCD in pediatric patients with hypertrophic cardiomyopathy, presented weak or no evidence.Lifestyle risk factors , comorbidities like DM, and electrocardiographic features like ERP constitute modifiable risk factors of SCD. Alternatively, the use of MRA, beta-blockers, SGLT-2 inhibitors, and ICD in patients with HF are credible protective factors. Further investigation targeted in specific populations will be important for reducing the burden of SCD.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020216363, PROSPERO CRD42020216363. Sudden cardiac death (SCD) constitutes a significant global public health burden, with some estimates of its mortality burden as high as 20% of all deaths in industrialized countries –3. SCD rWhen the death is not witnessed, the timeline expands to 24 h , 5.In the past 20 years, cardiovascular mortality has decreased significantly in high-income countries , especiaIdentifying and targeting modifiable risk factors for SCD can improve survival for at-risk patients by preventing the onset of SCD. Yet, risk prediction for SCD is complex. The propensity for sudden death is due to1a combination of intrinsic factors, such as genetic or acquired heart diseases, and transient factors that can trigger an SCD event . These fHere we perform an umbrella review to summarize the existing evidence concerning risk and protective factors associated with SCD among published meta-analyses. In accordance with best research practices, we rank the evidence of existing meta-analyses in this topic according to sample size, strength of the association, and existence of diverse biases , 10.This umbrella meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  reportinWe performed a systematic search in PubMed, Web of Science, Cochrane review, and Cochrane database of clinical trials through 21st May 2021, to identify systematic reviews with meta-analysis of observational or randomized controlled trials (RCT) examining associations between lifestyle factors, comorbid diseases, medications, echocardiogram (ECHO) abnormalities, electrocardiogram (ECG) abnormalities, and serum biomarkers, with the risk of SCD as a primary or secondary endpoint. Our search strategy was broad to identify all eligible studies using terms related to SCD and meta-analysis . The bibTwo researchers  independently searched articles for eligibility. The full texts of the retrieved articles were further scrutinized for eligibility by the same researchers. Any discrepancies were resolved after consultation with a third researcher (DT).We included only peer-reviewed systematic reviews which included meta-analyses of RCTs or observational studies with a cohort, case-control, or nested case-control study design, which measured any association between SCD and modifiable risk or protective factors, in any population. In case of the availability of multiple meta-analyses on the same topic, we proceeded with the meta-analysis with the larger number of studies, as previously described . All avaMeta-analyses were excluded if they were: (1) of other study designs than described above ; (2) of an individual patient or participant data, pooled analyses that examined a non-systematic selection of observational studies or RCTs, and non-systematic reviews; (3) examining genetic variants as risk factors of SCD; (4) published in other languages than English; (5) provided inadequate data for quantitative synthesis; or (6) presented study-specific effects estimates as mean difference. Reasons for exclusion after full-text assessment were listed in the https://amstar.ca/Amstar-2.php) by two independent researchers  , independently performed data extraction. Any disagreements were resolved by consensus. For each meta-analysis, the following variables were collected: first author, standard identifier (DOI), journal, study design, year of publication, number of component studies, total sample size, and risk and protective factors assessed. For each primary study, the following variables were collected: first author, year of publication, study design, sample size (exposure and non-exposure), and relative risk estimates  with the corresponding 95% confidence interval (CI). The methodological quality of meta-analyses included was assessed using the AMSTAR2  .I2 statistic  of individual studies reported in each meta-analysis was extracted, then the pooled effect sizes and 95% confidence intervals (CIs) were re-calculated, using random-effects models . Inter-statistic . Then, statistic , 18. Fintatistic . The expnificant . All anaFollowing previous umbrella reviews , eligiblp-value < 0.01, 0.01 ≤ p-value < 0.05, p-value ≥ 0.05), 95% prediction interval (excluding the null or not), and presence of large heterogeneity (I2 > 50%), small study effects (p < 0.10), and excess significance (p < 0.10) ; and (4) RoB review quality, by the responses to AMSTAR 2 questionnaire . Then, reviews were classified as high, moderate, low, or very low, by GLE  . An algo < 0.10) , 23. BriInitially, 2,586 publications were identified. After title and abstract screening, 167 potentially eligible articles were retrieved. Then, 112 articles were excluded after full-text assessment . In totaThe quality of included meta-analyses of observational studies according to AMSTAR2 was scored as high in 10 meta-analyses, moderate in 11, and low in 10 . The medp ≤ 0.05) under the random-effects models and 21 of those (38%) reached a p-value < 10−6. Thirty associations (36%) had more than 1,000 cases per association. Twenty-one associations (25%) had large heterogeneity (I2 > 50%), and only 19 associations (23%) had a 95% prediction interval that excluded the null value. In 57 associations (69%), the ES of the largest study had a nominally statistically significant effect (p ≤ 0.05). Finally, small-study effects were found for 12 associations (15%) and excess significance bias was found for nine associations (11%).In the observational studies meta-analyses, 55 of the 83 examined associations (66%) had a nominally statistically significant effect  associations presented convincing evidence , includiIn the prospective analysis, only three risk factors from the main analysis remained at the same class I level. These included T2DM, smoking, and physical activity. However, the five class I factors with convincing evidence in the main analysis remained convincing when associations with >1,000 cases were excluded .The quality of included meta-analyses according to AMSTAR2 was scored as high in 12 meta-analyses of RCTs, moderate in 4, and low in 8 . The medp < 0.05 (10 had p < 0.001). Only 13 (23.2%) associations had a significant confidence interval, 48 (85.7%) showed no large heterogeneity (I2 < 50%), six (11%) showed small study effects, and four (7.1%) showed excess significance bias.Overall, 31 of the 56 (55%) associations reported a nominally significant summary result at When the RCT credibility criteria were applied, five (8.9%) associations between protective factors and SCD presented a high GLE . These aMore specifically, about the use of ICD and CRTs to prevent SCD, meta-analyses of RCTs showed that ICD prevents SCD in patients with HF, IHD, and non-IHD. The evidence of these associations was of high epidemiological credibility. However, CRT-Ds but not CRT-pacemaker (CRT-Ps) showed to protect significantly from SCD in patients with non-IHD.In this study, we reviewed 55 articles concerning the risk and protective factors of SCD. Despite most of the associations being statistically significant, only a minority of them provided convincing evidence. Our meta-analyses of observational studies showed that the presence of ERP on ECG, current smoking, and T2DM were important risk factors, while physical activity was an important protective factor. In patients with HF, the use of CRT-D compared to CRT-P was the most important protective factor. Sensitivity analyses limited to prospective cohort studies did not alter marginally the main results. Our meta-analyses of RCTs showed that in patients with HF taking MRAs or SGLT-2 inhibitors, and the use of ICDs and CRT-Ds were important protective factors. Furthermore, the association of AF, HTN, and T2DM in patients with cardiovascular comorbidities with the risk of SCD was supported by highly suggestive evidence. Beta-blockers and ICDs were protective factors from SCD with moderate evidence, in certain subpopulations .ERP is defined as an elevation of the QRS-ST junction, J-point, and QRS notching in multiple ECG leads, and is high prevalent in middle-aged individuals . Althougn < 1,000) in the included primary studies. Smoking as a risk factor is modifiable, and the risk of cardiovascular disease is reduced by 39% as soon as 5 years after cessation . These results are consistent both in IHD patients and non-IHD patients , 38, witMore than ten medications have been studied for the risk of SCD, in different patient populations. Androgen deprivation therapy, macrolides, antipsychotics, and Parkinson's drugs, were evaluated in observational studies as risk factors for SCD. All were significant risk factors for SCD but, none showed high epidemiological credibility. However, in the performed sensitivity analysis, when the criterium of more than 1,000 cases per association was omitted, the association of antipsychotics with SCD was upgraded to highly convincing for risperidone and convincing for the antipsychotics' haloperidol, quetiapine, and thioridazine, a finding in line with the literature . The risMore than six medicines, including amiodarone, beta-blockers, statins, ACE-inhibitors, MRA, SGLT-2, omega-3 fatty acids, and other antihypertensive drugs were tested in meta-analyses including only RCTs. All were found to be statistically protective against SCD, but only SGLT-2 and MRA associations were supported by a high GLE. It is also important to note that these medicines are used for the treatment of heart failure  and arrhn > 1,000 patients was omitted. This finding is surprising as low LVEF is the criterion used most commonly during the last decades to find patients eligible for ICD therapy for primary prevention of SCD. The small number of primary studies and the issue of low reproducibility of the measurement of LVEF in clinical settings can possibly explain this finding , were significant, albeit with weak evidence. This finding could be explained by the observational study design, the small sample size, and the critically low quality of the included studies, a fact which was also annotated in the latest published guidelines . Hence, Other interesting factors associated with the risk of SCD but not included in previous meta-analyses that fulfill the inclusion criteria of our umbrella review involve risk factors such as gender in young, episodes of supraventricular tachycardias, and COVID-19 infection. Data from observational studies show that the incidence of SCD in young men is lower compared to young women, indicating that SCD due to potentially inherited cardiac diseases is less often in young women . Even ifIn the current guidelines , there iThere were several modifiable risk factors with only a weak level of evidence , in the general population and subpopulations tested. This is likely due to the limited number of available cohorts and the small number of participants available for the subpopulation analysis. Larger cohorts may be helpful for further elucidating the role of these modifiable risk factors, by providing more evidence about these associations.Our umbrella review provides a broad picture of the non-genetic factors that have been studied for SCD. However, this study has also several limitations. First, in meta-analyses that included observational data, the associations which were supported by high epidemiological credibility can be considered strong evidence, but they cannot imply causality. On the contrary, meta-analyses which include RCTs provide data mostly in patients already at high risk, and therefore is less generalizable to the general population. Thus, our study yields risk factors with proven significant associations to SCD but does not allow conclusions as to their clinical value in primary prevention. Second, grading of meta-analyses which include observational data can provide only warnings concerning the presence of systematic biases and not proof about the nature of these biases , 73. ThuIn this umbrella review, we mapped the epidemiological evidence on non-genetic factors associated with SCD as identified in previously published meta-analyses. Even though SCD is a prevalent medical issue, we were only able to identify a small number of risk factors associated with SCD and even fewer with high epidemiological credibility. The association between SCD and the following risk factors were supported by convincing and highly supported evidence: lifestyle risk factors, like the lack of physical activity and smoking; comorbidities, like AF and DM; the use of medications, like MRA or SGLT-2 inhibitors; ECG features, like ERP; and the use of ICD. Further investigation with targeted interventions in these populations is the first step toward a better strategy for SCD prevention.The original contributions presented in the study are included in the article/EC, DT, and ED designed the study. DK and EC performed a comprehensive screening of the literature, selected the studies included in the meta-analysis, and abstracted the data items. DT and ED performed the statistical analysis. DT and EC drafted the manuscript. EC, DT, DK, LOK, AS, DV, EF, AA, CT, CA, and FB interpreted the results and edited the manuscript critically. All the co-authors have read and accepted this version of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


About 60-80% of thyroid cancer (TC) cases are papillary thyroid cancer (PTC). Studies have shown that serum adiponectin levels are inversely related to the risk of TC and PTC. Aim of the present study was to evaluate the association between adiponectin rs2241766 and rs266729 polymorphisms and risk of PTC. 122 PTC patients and 128 healthy subjects were enrolled in the study. PCR-RFLP and ARMS-PCR methods were used for genotype analysis. The rs266729 polymorphism did not correlate with risk of PTC. As regard rs2241766 polymorphism, the frequency of the GG genotype did not have a significant difference between the two groups, although, PTC cases showed higher frequency of GT genotype compared to controls . We observed a significant association between adiponectin rs2241766 polymorphism and PTC, however, our result showed no significant relationship between adiponectin rs266729 polymorphism and risk of PTC.  Althoug2 , 4. Epid2 . Adipose2 , encodede 3q27.3 . Studiese 3q27.3 . In 2003e 3q27.3 . Cheng ee 3q27.3 . ADIPOQ gene has been shown to create a haplotype associated with obesity and insulin resistance [ADIPOQ gene promoter at position -11,377 and causes C to G substitution. Studies indicate the regulatory role of this polymorphism in promoter activity and plasma adiponectin levels. The association of rs266729 with high body mass index has also been reported [A single nucleotide polymorphism (SNP) is considered as a DNA sequence variation occurring in people if its prevalence is more than 1% . Growingsistance . The rs2reported . Low serRegarding the important role of adiponectin in developing PTC, the presents study focused on the relationship between adiponectin rs2241766 and rs266729 gene polymorphisms with the risk of PTC in Iranian patients.Study subjects: Zahedan University of Medical Sciences' Ethics Committee approved the protocol for this case-control study (IR.ZAUMS.REC.1399.523). The study included 122 patients with PTC and 128 healthy subjects (matched for age and gender), who were referred to the endocrinology clinic at Ali-ebn Abitaleb Hospital, Zahedan, South-East Iran. In the case group, the study exclusion criteria were as follows: statin and antihypertensive drug use, a history of neck irradiation, thyroid disease, a history of thyroid surgery. In the control group, subjects with a history of diabetes Mellitus, autoimmune disease, malignancy, and renal or hepatic disorders were excluded from the study.DNA extraction and genotyping analysis: 500 µl of EDTA-containing blood was used for DNA extraction by the salting-out method. The quality of the DNA was checked by agarose gel electrophoresis and OD260/OD280 ratio analysis. The PCR-RFLP method was used for rs266729, as described previously [eviously . Tetra-peviously . The seqStatistical analysis: We evaluated the impact of SNPs on disease development by using the odds ratio (OR) and 95% CI. χ2 tests were used to analyze demographic characteristics. P<0.05 was considered statistically significant. We used SPSS version 23 for data analysis.Demographic and clinical characteristics of PTC patients and controls are shown in The rs266729 and rs2241766 polymorphisms in control group were in Hardy-Weinberg equilibrium. There was no significant association between rs266729 polymorphism and risk of PTC. Regarding the rs2241766, the frequency of GT genotypes in the PTC group was significantly higher than that in the controls and may be a risk factor for PTC  . vs 9.1%), suggesting it may be a risk factor for PTC . In PTC patients, the frequency of the GG haplotype was higher (5.3% vs 1%), but the difference was not statistically significant (P=0.061). In addition, controls had a higher frequency of the GT haplotype than PTC patients (12.2% vs 9.4%), but the difference was not statistically significant (P=0.76).According to ADIPOQ and the risk of PTC development. Genetic models and allelic distribution also showed similar results. In addition to modifying the amino acid sequences, SNPs can also be silent or appear in noncoding regions. They may also affect promoter activity and mRNA stability. As a result, analysis of gene variants is effective in further understanding our changes in the incidence of disease [From a molecular point of view, some mutations, including proto-oncogene mutations such as RAS and BRAF, are often observed in PTC . Firming disease . To the best of our knowledge, this is the first report of the association between adiponectin rs2241766 and rs150299 gene polymorphism and risk of PTC. The results obtained from studies conducted on the effect of this polymorphism on risk of cancer are contradictory. A meta-analysis showed that rs2241766 and rs150299 polymorphisms had a protective effect on cancer incidence, while similar to our results, they did not find a significant relationship between the rs266729 and cancer incidence . A meta-We declare that we have no conflict of interest.


N-nitroso compounds (NOCs) are a class of chemical carcinogens found in various environmental sources such as food, drinking water, cigarette smoke, the work environment, and the indoor air population. We conducted a systematic review and meta-analysis to investigate the links between nitrate, nitrite, and NOCs in food and water and the risk of gastrointestinal (GI) cancers, including esophageal cancer (EC), gastric cancer (GC), colorectal cancer (CRC), and pancreatic cancer (PC). A systematic search of the literature in Scopus, PubMed, Google Scholar, Web of Science, ScienceDirect, and Embase was performed for studies on the association between NOCs in drinking water and food sources and GI cancers. Forest plots of relative risk (RR) were constructed for all the cancer sites and the intake sources. The random-effects model was used to assess the heterogeneity between studies. Forty articles were included after removing duplicate and irrelevant articles. The meta-analysis indicated that the intake of high dose vs. low dose of these compounds was significantly associated with the overall GI cancer risk and nitrite , and N-nitrosodimethylamine (NDMA) . We found that dietary nitrite intake increased GC , and EC . Additionally, dietary NDMA intake increased the risk of CRC . This meta-analysis provides some evidence that the intake of dietary and water nitrate, nitrite, and NOCs may be associated with GI cancers. In particular, dietary nitrite is linked to GC and EC risks and dietary NDMA intake is associated with CRC. In 2020, cancer accounted for nearly 10 million deaths and nearly one in six deaths worldwide. Gastrointestinal (GI) cancers, with an estimation of approximately 5 million new cases and 3.5 million deaths worldwide, accounted for half of the cancer burden in 2020 [H pylori infection, high body mass index, low physical activity, and dietary factors [In addition to non-modifiable risk factors such as the demographic characteristics, family history, and genetic predisposition, some preventable risk factors are well established for GI cancer, including tobacco smoking, alcohol consumption,  factors ,4,5,6.The N-nitroso compounds (NOCs) are a broad class of chemical carcinogens that exist in various environmental sources such as food, drinking water, cigarette smoke, the work environment, and the indoor air population, although intrinsic sources are also available for crucial needs of our bodies ,10,11,12Several experimental and epidemiological studies have shown that nitrate, nitrite and NDMA can affect human health , includiThe online database searches were performed in January 2022. Searches were undertaken for English-language peer-reviewed publications on the association of nitrate, nitrite, and NOCs and the risk of GI cancers between 1990 to the present. The databases included Scopus, PubMed, Google Scholar, Web of Science, ScienceDirect, and Embase. The search strategy was designed using MeSH terms like “Gastrointestinal Cancers”, “Digestive System Cancers”, “Organic Chemicals”, “Nitroso Compounds”, “Nitrate”, “Nitrite”,”NDMA”, and “Epidemiologic Studies”. Based on our searches on the databases, a total of 12,750 articles were retrieved, including 4539 articles for GC, 2204 for EC, 6673 for CRC, and 2243 for PC. A total of 40 studies were included after the title, abstract, full-text evaluations, and quality assessment ,60,61,62The study screening and quality assessment were conducted by three researchers , and in the event of any discrepancies, a referee (EM) intervened. The data extraction file contained the demographic characteristics of the article such as the author’s name, the year of publication, the title, the type of study, the country, as well as the design characteristics, including the sample size, the sampling method, the source of the population, the type of controls, the type of cancer, the source of nitrate, nitrite, and the NOCs , and the method of data collection . Finally, the effect size measures, including the relative risks (RRs) for the cohort studies and the odds ratios (ORs) for the case-control studies and their 95% CI were abstracted.Quality assessment of the included articles (case-control or cohort studies) was accomplished using the Newcastle-Ottawa Scale (NOS) . For cas2 statistic  [2 > 60%), was estimated using a random-effects model [p-value of heterogeneity was assessed using a sub meta-analysis. Moreover, publication bias was examined by creating a funnel plot and a regression asymmetry test [The relationships between nitrite, nitrate, or NMDA intake and the risk of GI cancers were examined based on the effect size measurements and the corresponding 95% CIs of each study. Because of the rare disease assumption, the ORs are assumed to approximate the RRs . Heteroggeneity) . The poots model . All anatry test ,69.A total of 40 independent studies were included in the meta-analysis, including 27 case-control studies ,57,60,61The meta-analysis was repeated for each cancer site based on the nitrate, nitrite, NDMA and the source intake.2 = 80.2%, P-heterogeneity = 0.025), the food intake of nitrate , and the food intake of nitrite  . There were no statistically significant excess risks from the food sources of nitrate, NDMA, or the water sources of nitrate intake. We observed significant heterogeneity for studies of the food sources of NDMA (I= 0.004) . There w= 0.004) .2 = 92.2%, P-heterogeneity = 0.000). Additionally, there were significant heterogeneities for studies of the food intake of NDMA , the food intake of nitrate , and the water intake of nitrate   (I= 0.000) . We foun= 0.000) .2 = 73.4%, P-heterogeneity = 0.002), the food nitrite intake , and the water intake of nitrate  . No statistically significant heterogeneity across studies was observed for CRC in relation to NDMA intake, but heterogeneity was statistically significant for studies of the food nitrate intake (I= 0.000) . Stratif= 0.000) .2 = 80.7%, P-heterogeneity = 0.000), and nitrite   . No sign= 0.000) .We found limited high-quality research on nitrate, nitrite, NOCs, and cancer risk, most likely due to the difficulty of quantifying these compounds from different sources worldwide. Despite this limitation, the literature suggests that dietary and water sources may be risk factors for GI cancers, in particular, nitrate intake from water sources and diet for CRC, nitrite intake from diet for GC, and NDMA intake for CRC and EC ,56,59,70Nitrate and nitrite as precursors of the NOCs  are suspected of playing a key role in cancer carcinogenesis through the induction of DNA-damaging metabolites, like aldehydes and alkyldiazonium ions, which could cause cancerous lesions in cells ,16,58,70H pylori infection in the GC studies [There was heterogeneity in the study designs and the methodologies, which may explain the differences in the results of the published studies. The high heterogeneity observed in our meta-analyses may be due to the variety of confounders used in the models as well as the differences between the study settings, the population characteristics, the compound ranges, and the estimation methods. Except for age and gender, other confounders were less consistently controlled for, particularly dietary factors and specific risk factors, such as  studies .The number of reviews for EC was limited. A meta-analysis study by Lie et al.  in 2016 H.pylori infection may increase the NOCs product level and increase the risk of GC [In 2016, Lie and others found an inverse association between dietary nitrate consumption and GC, and a borderline association between dietary nitrite consumption and GC . In 2015sk of GC .Previous studies on association between the NOCs and CRC are inconsistent. In 2016, one systematic review reported that dietary nitrite/nitrate intake was not significantly linked with CRC , howeverNone of the previous reviews reported a significant relationship between dietary or water intake of nitrate, nitrite, and NDMA and the risk of PC ,19. Our The geographical distribution of the studies plays an important role in achieving reliable results. A majority of the studies included in our review were conducted in Europe (30%) and North America (48%), and we found no reliable studies from low- and middle-income countries (LMICs). As a result, our findings cannot be generalized to LMICs, where the amounts of nitrate, nitrite, and NOCs may vary based on the dietary patterns, the cooking methods, the water sources, the effect of seasonal rainfall on water compounds, and the fertilizer compounds . Also, mIn conclusion, our meta-analysis shows modest evidence on the association between dietary and water nitrate, nitrite, and NOCs intake and certain types of GI cancer risk. The dietary intake of nitrite is associated with GS and EC and the dietary NDMA intake is associated with CRC. In future studies, the influence of different compound types on cancer should be explored by considering the source intake, and gender differences, particularly in less studied geographical regions.


Measurements of blood cholinesterase (ChE) activities, including those of erythrocytes (EChE), plasma or serum (PChE), and whole blood (WBChE), are used to assess exposure to ChE-inhibiting pesticides. The purpose of this review was to report normal reference ChE activities in the blood of healthy adult humans, as determined by a modified electrometric method. We performed a systematic review following PRISMA guidelines. Single-group meta-analysis of means of PChE, EChE, and WBChE activities of adult healthy subjects was conducted using the random effects model. The programs used were Open-Meta Analyst and Meta-Essentials Version 1.5. Studies selected for analysis comprised 21, 19, and 4 reports of normal reference/baseline PChE, EChE, and WBChE activities in 690, 635, and 121 healthy adult males and/or females, respectively. The meta-analysis showed normal reference values of the means (effect sizes) with 95% CI of PChE, EChE, and WBChE activities of healthy adult subjects, which were 1.078 , 1.075  and 1.331 , respectively. By the subgroup analysis, heterogeneity (I2>89%) was considerably reduced in females to 4.4% and 30.1% for PChE and EChE, respectively. Funnel plots indicated no publication bias. However, Egger's regression confirmed the symmetry of the data points for PChE and WBChE activities with a significant effect on EChE. This meta-analysis showed normal reference values of PChE, EChE, and WBChE activities, measured by a modified electrometric method, in healthy adult humans. Pesticides of organophosphorus and carbamate compounds are extensively used to control insects in public health, agriculture, and veterinary clinical practice –3. Thesein vivo and in vitro blood ChE inhibitions induced by organophosphates and carbamate insecticides [Several laboratory and field methods are available to determine blood ChE activities. These include, but are not limited to, spectrophotometric, electrometric (potentiometric), radiometric, biosensors, and manometric procedures –25. The cticides , 31–37.et al. [The procedural details of the modified electrometric method have been adequately described for laboratory applications to measure blood ChE activities in humans –30 and aet al.  stressedet al. –15. The et al. –30. The et al. –44. TherAll procedures of the present review and meta-analysis were approved and conducted according to institutional regulations of the Review Board, which observes the principles of medical research expressed in the Declaration of Helsinki.The steps for determining human blood ChE activities by the modified electrometric method –30 are iThe data search included studies (research articles and academic theses) that used the modified electrometric method , 29 for All authors were involved in the selection processes, according to PRISMA. Initially, a single reviewer (FKM) screened the studies for normal values of blood ChE activities as measured by the modified electrometric method , 29. TheA single group meta-analysis (according to PRISMA guidelines) was conducted to evaluate the mean PChE, EChE, and WBChE activities of healthy adult subjects, using random effects model to account for the anticipated sources of heterogeneity among different studies , 21, 25.2 were applied to assess statistical heterogeneity and inconsistency in the reported ChE values among the reports, respectively. The level of statistical significance for the heterogeneity test (Cochrane Q-test) was set at a p-value of <0.10. After that, the forest plot was used to summarize the findings [The Cochrane Q-test and Ifindings –69. The findings , 69. TheUsing the randomized effects model, single group meta-analysis of the present reports revealed that the normal reference values of the means (effect sizes in the forest plots) with 95% CI of PChE, EChE, and WBChE activities of adult healthy subjects were 1.078 , 1.075  and 1.331 , respectively . The per2 statistical test was used to examine the variations among the studies as a result of heterogeneity; the value of I2 could range from 0% (no heterogeneity) to 100% (high heterogeneity) [The Igeneity) –68. The 2 values of 4.4% and 30.1%, respectively  used indiscriminately remained significantly high (Because of the considerable heterogeneity (>88%) in the meta-analysis , we condectively . The I2 tly high . The evitly high .Leave-one-group meta-analysis was conducted to assess the sensitivity of the analysis and stability of the effect size estimates. According to the resultant forest plots of PChE, EChE, and WBChE activities, it was revealed that the percentages of changes in the effects sizes ranged between 1 to 2% for both PChE and EChE activities and between 2.5 to 3% for the WBChE activity , Table 5The funnel plot and Egger's test were used to assess the possibility of publication bias. The standard errors (y-axis) were plotted against the effect sizes (x-axis). The asymmetrical distribution of the data points of the reports suggested the presence of such a condition. However, visual examination of the funnel plots of PChE, EChE, and WBChE activities indicated no publication bias . Furtherin vitro evaluation of antiChE drugs and pesticides [Measuring blood  ChE activities is an important biomonitoring tool to assess exposure to organophosphate and carbamate pesticides, especially among agriculture workers, , 43, 57.sticides , 39, 71.The present meta-analysis reports the reference ChE activities in the plasma, erythrocytes, and whole blood of healthy adult humans. These values could form the basis for comparison following exposure of workers to antiChE pesticides, especially in the absence of pre-exposure values , 15–18. 2 values of males and both sexes (MF) remained significantly high, with no conclusive evidence for WBChE subgroup analysis because of the limited available reports  was considerably reduced in the PChE and EChE activities of females, which consisted of only two reports. The I reports , 3 and 5 reports , the genWe noticed some studies misquoted the modified electrometric method or missed some of the important details of the procedure, such as the incubation time and concentration of the substrate –44. HoweIn the present review, we report normal reference WBChE values in humans with no heterogeneity . This isThis study and the meta-analysis showed normal reference values of PChE, EChE, and WBChE activities, measured by a modified electrometric method, in adult healthy humans. These blood ChE values could form the basis for interpreting workers' exposure to antiChE pesticides. Further studies are needed to update meta-analysis on normal blood ChE activities determined by the modified electrometric method and on the sources of blood ChE variations due to age, gender, and demographic characteristics of the subjects.