There was moderate heterogeneity for most of the results, and subgroup analyses were conducted by dividing the studies according to the geographic location, gender ratio, and selection criteria of the performed study. There were no significant differences between the groups, but different geographic location was a probable source of heterogeneity. All of the studied markers—FVL, prothrombin, PC, PS, and AT—were significantly associated with increased risk of ischemic stroke in young adults and, if tested, could improve the quality of care.Ischemic strokes are one of the leading causes of death worldwide. The aim of this meta-analysis is to elaborate on the role of inherited predisposition to thrombophilia in the etiology of ischemic strokes in young adults. The keywords factor V Leiden (FVL), factor II, prothrombin (PT), protein C (PC), protein S (PS), antithrombin (AT), ischemic stroke, and young were used to search different databases. We selected studies with participants who were between 18 and 65 years. A total of 104 studies were eligible for inclusion in the meta-analysis. All the studied genetic markers were risk factors for ischemic stroke according to our results (FVL OR = 1.74; PT OR = 1.95; PC OR = 10.20; PS OR = 1.74; AT OR = 3.47;  Ischemic strokes are one of the leading causes of death and reduced quality of life worldwide. Although they are traditionally associated with advanced age, more than two million young adults are diagnosed with an ischemic stroke (IS) each year . In BulgWhen ischemic strokes affect the younger population, they have more severe economic consequences because the affected individuals may not fully recover, may be unable to work, and require someone to help them in their daily activities .Because of this, investigation of the etiology of ischemic strokes among young people is of the utmost importance. Risk factors could be traditional ones, such as hypertension, hyperlipidemia, and obesity, but may also include persistent foramen ovale, dissection of the aorta, drug abuse, pregnancy, etc. . NeverthIn the past few years, a lot of attention has been paid to genetic predisposition to thrombophilia—for example factor V Leiden, prothrombin gene mutations, and deficiencies in protein C, protein S, antithrombin, etc. .Factor V Leiden (FVL) is a genetic variant of normal factor V. As a result of amino acid substitution, factor V cannot be inactivated by activated protein C (APC), which leads to APC resistance and a genetic predisposition to thrombophilia. People who are heterozygous carriers of FVL are four times more likely to present with venous thromboembolism .Variants in the prothrombin gene are another reason for a genetic predisposition to thrombophilia. These mutations result in higher plasma levels of prothrombin due to an elevated expression of messenger RNA . ProthroDeficiencies in proteins C and S, as well as in antithrombin, show a 50-times higher chance of thrombosis compared to FVL and prothrombin . In addiBoth protein C and S are produced by the liver, and this process depends on vitamin K. PC is first activated into APC, which acts by inactivating factors Va and VIIIa, thus preventing thrombosis. Protein S (PS) is a cofactor of PC . DependiAntithrombin (AT) is mainly involved in the inactivation of thrombin and factor Xa. When AT binds to heparin, its anticoagulant effect is boosted . AT defiThe aim of this paper is to determine how genetic predisposition to thrombophilia—specifically, the heterozygous or homozygous states of FVL and prothrombin, as well as levels of PC, PS, and AT—affects the etiology of ischemic strokes in young individuals.The search strategy was peer-reviewed and registered with the International Prospective Register of Systematic Reviews. We performed a search of the MEDLINE (PubMed) and Web of Science databases in accordance with PRISMA guidelines  and usedThe following criteria for inclusion in the meta-analysis were used: 1. case–control studies regarding young adults with ischemic strokes who were tested for FVL, prothrombin, PC, PS, or AT were included, while cohort studies were excluded; 2. the indexed patients must be between the ages of 18 and 65; 3. animal-only studies were excluded; 4. reviews and meta-analyses were excluded; 5. the full information about the ages of the case subjects and the types of mutations must be provided by the authors; 6. the articles must be written in English, and the full text must be available.We also collected information regarding the year of publication, the ethnic background, and the total number of the participants, as well as the age, gender, geographical setting, and health status of the included individuals. Studies that did not meet the inclusion criteria were excluded.p-value ≤ 0.05 and analyzed the included articles for publication bias using funnel plots. Using the genetic data provided in the publications, we conducted the meta-analysis. If the information was given as a prevalence of hetero- and homozygotes, we used allele frequency. We made the assumption that the gender ratio was equal if there was no information available regarding the precise number of men and women who took part in a study.After selecting eligible studies, we performed a meta-analysis using Review Manager (RevMan) software  and a fixed model. We found the values of odds ratio (OR), Z-test score, and heterogeneity for FVL, prothrombin, PC, PS, and AT and performed subgroup analyses in cases of high levels of heterogeneity. Our goal was to check the risk of stroke among young individuals who had genetic predispositions to thrombophilia due to changes in the above-mentioned markers compared to healthy control subjects. We applied a two-tailed The quality of the included publications was evaluated using the Newcastle–Ottawa scale (NOS) . The maxPROC gene, those in PS were due to mutations in the PROS1 gene, and those in AT were due to mutations in the SERPINC1 gene. However, most studies about these three markers focused primarily on measuring their levels. The eligible studies were later used in the meta-analysis. The NOS was applied in order to check the quality of all the qualifying studies, and all of the publications received seven or more stars , and the level of heterogeneity remained similar at 20% for the Europe group and 9% for the other group. We also separated the studies according to the gender ratio of the participants: one group for studies with equal gender ratios and another group for studies with unequal ratios, where men or women made up more than 60% of the cohort. However, there was no statistical difference between the two groups (p = 0.71), and the heterogeneity was also moderate at 24% for both groups (p = 0.24); the heterogeneity for the first subgroup was moderate at 26%, while that of the other group was low at 17% , but the heterogeneity for the subgroup with equal gender ratios was low (2%), while it was high for the other group (61%). For the other subgroup analyses, there were no statistical differences between the two subgroups (p > 0.05). However, there were significant changes in heterogeneity: 11% for the “cryptogenic stroke” group, 43% for the “non-cryptogenic stroke“ group, 16% for the “Europe” group, and 65% for the “Asia, South, and North America” group.No matter whether the results were reported as homo- and heterozygotes or as mutated and healthy individuals, prothrombin was also found to be a risk factor for ischemic stroke. In the first case, the OR was 1.95, p < 0.05 , and in p < 0.05 . The levp < 0.05 . In the Because of the high percentage of heterogeneity when participants were reported as mutant and healthy individuals, we performed a subgroup analysis and again divided the studies based on the geographical location of the study into a Europe group and an Asia, South, and North America group. However, the percentages of heterogeneity remained high: 88% and 81%, respectively . Becausep < 0.05; 2 = 38.00%, but for PS and AT, it was higher at 73.00% and 75.00%, respectively. We performed subgroup analyses for all three markers. We subdivided the studies into two groups based on the geographical location of the included participants—those from Europe and those from Asia, South, and North America. The results for PC showed a statistically significant difference between the two groups (p = 0.02) and a notable decrease in the levels of heterogeneity: 0% for the Europe group and 11% for the other group. As for PS, after this analysis, there was not a statistically significant difference between the two groups (p = 0.24), but there were differences in the levels of heterogeneity. For the Europe subgroup, I2 = 0%, and for the other group, I2 = 88%. As for AT, the two groups—Europe and Asia, South, and North America—also did not show a statistically significant difference (p = 0.81), and the percentages of heterogeneity remained high: I2 = 73% and I2 = 90%, respectively. This was why we divided the articles for AT according to the gender ratios of the participants: one group with equal gender ratios and the other with unequal ratios, where men or women made up more than 60% of the cohort. Despite showing no statistical differences between the two groups (p = 0.37), the heterogeneity of the first group was 0%, and of the second one was 84% (Articles on the correlation between strokes and PC, PS, and AT involved laboratory diagnostics without any genetic testing, and the results were divided into subjects with deficiencies in these markers and normal individuals. All three—PC, PS, and AT—were risk factors for an ischemic stroke (OR for PC = 10.20, OR for PS = 1.74, OR for AT = 3.47;  was 84% .The meta-analysis we performed showed that all of the studied genetic polymorphisms—FVL, prothrombin, PC, PS, and AT—were risk factors for ischemic stroke. The funnel plots were symmetrical, and there was no obvious risk of publication bias .There are no well-defined recommendations on genetic counseling and testing for thrombophilia in stroke patients. In the latest recommendations, genetic factors for ischemic strokes are only discussed as possible nonmodifiable risk factors for ischemic strokes ,65,66. TThe results from our meta-analysis showed that FVL, prothrombin, PC, PS, and AT were all risk factors for ischemic strokes among young adults. This finding is in accordance with other reports. Chiasakul et al. also conducted a meta-analysis regarding the role of inherited thrombophilia in patients with arterial ischemic strokes and concluded that FVL, prothrombin, PC, PS, and AT correlated with an increased risk of stroke, especially in young patients . Kim et Another meta-analysis by Hamedani et al. focused specifically on the association between FVL and ischemic strokes in patients who were 50 years or younger. According to their results, FVL was a risk factor for ischemic stroke in the studied cohort, but this association was significant only for patients who were selected based on a clinical hypothesis of prothrombotic condition due to the coexistence of, for example, deep venous thrombosis. In patients without such history, it was less likely to find a correlation between FVL and ischemic strokes . In our As for PC, PS, and AT, we found only one published meta-analysis analyzing the possible correlations between these factors and arterial ischemic strokes in young adults. The authors found that, in patients who were 65 years or younger, PC and PS deficiencies were possible risk factors for ischemic stroke: the ORs were 2.13 and 2.26, respectively . We alsoAccording to Chiasakul et al., deficiency in AT did not show a statistically significant result . On the Nevertheless, there are also reports that deny the roles of the studied factors for predisposition to thrombophilia. For example, Pahus et al. reported that heterozygote carriers of FVL were predisposed only to transient ischemic attacks . There aMTHFR gene. However, according to a large meta-analysis focused on venous thromboembolisms, this variant did not predispose patients toward thrombophilia, even in combination with changes in the genes for FVL or prothrombin [It should be pointed out that there are also other risk factors that, in combination with a genetic predisposition to thrombophilia, may significantly increase the chance of an ischemic stroke. One such factor is, for example, PFO . There wthrombin . This isthrombin .One should also keep in mind that testing for inherited thrombophilia can be very expensive and is not covered by health insurance in all countries. Furthermore, even if a patient tests positive for thrombophilia, the treatment plan is rarely affected . It was Our research had several limitations. We reported moderate percentages of heterogeneity after the first step of the meta-analysis was completed. During the subgroup analyses, we divided the studies based on the geographic location of the research, the gender ratio of the participants, and the selection criteria of the performed study. There were no statistical differences between most of the analyzed subgroups. However, the levels of heterogeneity decreased. This illustrated that a different study design may have a significant impact on the results. Despite the fact that the meta-analysis was based on similar case–control studies, the selection criteria of the research groups might have slight differences, for example, because different control groups were used, the participants had different ethnic backgrounds, etc. Moreover, there are data suggesting that the prevalence of genetic predisposition to thrombophilia may differ based on geographic localization. For example, FVL is more prevalent among people of European descent and is rarely reported in patients of sub-Saharan African and east Asian descent. Even in Europe, its distribution is not equal, and there is a possible positive gradient of prevalence from south to north . On the Another important source of heterogeneity was the risk profile of the included participants. In most of the case–control studies, classic risk factors for stroke, such as hypertension, diabetes, hyperlipidemia, etc., were more prevalent among patients with ischemic strokes. These could have an impact on the incidence of stroke and increase stroke risk, as well as the genetic predisposition to thrombophilia. This was also noted by Hamedani et al., who published a meta-analysis on inherited thrombophilia among young stroke patients. They reported a significant association between FVL and the risk of stroke with an odds ratio was 1.4. However, because of high heterogeneity among the included studies, the authors performed subgroup analyses, selecting studies with cryptogenic strokes. The odds ratio for FVL among patients with cryptogenic strokes was higher than that in the first case at 2.7 . This isAnother limitation of our work was that, although we found a large number of studies for FVL and prothrombin, some of them reported their results as mutant or healthy individuals only and did not contain information about the exact genotypes of the participants. This is why we could not perform a meta-analysis with all of the studies but had to separate them in two different groups based on the presence or absence of full genomic data of the included patients. The significance of the current meta-analysis could have been higher if we used a larger number of studies. This is why it is extremely important to follow universal guidelines and to publish full genomic data in order to increase the transparency of results. In addition, we did not perform subgroup analyses on age or the presence of PFO because exact information was missing from the studied articles. It would be interesting to see how age and PFO affect the association between thrombophilia and ischemic strokes.In addition, it should be pointed out that most of the case–control studies on the roles of PC, PS, and AT did not perform genetic testing but instead analyzed the plasma activity or concentrations of these markers and reported deficiencies in the event of reductions in the above-mentioned parameters.Regardless of its limitations, our meta-analysis summarized the largest number of case–control studies on genetic predisposition to thrombophilia among young stroke patients to date. We report significant results about the roles of FVL, prothrombin, PC, PS, and AT as possible risk factors for ischemic stroke. Because the included case–control studies were conducted in many different countries, the results could be applied to clinical practice, regardless of location.The number of young stroke patients is increasing, thus requiring more investigation of the possible risk factors. Inherited thrombophilia is one of them, and it may be associated with ischemic strokes due to hypercoagulability state. According to our results, FVL, prothrombin, PC, PS, and AT could all predispose toward ischemic strokes among young adults and should be part of laboratory testing in cases of young stroke patients. More explicit recruiting criteria, as well as a universal way of reporting genetic results, in case–control studies are needed in order to better evaluate the roles of these thrombophilic factors in the etiology of ischemic strokes among young patients.


Adolescence and youth are critical periods in which alcohol consumption is usually initiated, especially in the form of binge drinking. In recent years, it is increasingly common to find adolescents and young people who also present binge behaviors towards unhealthy food with the aim of alleviating their anxiety  and/or because of impulsive personality. Despite the social and health relevance of this issue, it remains scarcely studied and more preventive research needs to be developed. Our meta-analysis study aimed to evaluate the relationship and co-occurrence of both binge behaviors during adolescence and young adulthood to clarify the link between binge drinking and eating. Selective literature search on different online databases was performed. We identified discrete but significant results regarding the direct association between binge drinking and binge eating in correlation coefficients and odds ratio. Future research should focus on the common psychological background and motives behind these problematic behaviors owing to their clinical implications for effective prevention and treatment. Adolescence is a particularly vulnerable period of neurodevelopment in which the incorrect management of emotional, social, and behavioral changes can lead to an unsuccessful adulthood . RegardiRegarding alcohol consumption, it is a frequent problem in adolescence, and it is usually carried out on weekends involving the ingestion of large amounts of alcohol  in short periods of time (2 h) that increase the blood alcohol concentration above 80 mg/dL ,7,8. NowA binge-based pattern of food consumption has been termed Emotional Eating (EE), which is triggered in response to the presence or avoidance of negative mood states, and was derived from theories of obesity ,14,15,16Owing to these similarities, in the following sections, we will revise the co-occurrence between these binge behaviors and the factors involved in their co-occurrence, and we will establish a reliable estimate of this relationship through a meta-analysis method.The relationship between alcohol and food consumption is evident in comorbidity data, with substance abuse problems found in more than 30% of patients with bulimia nervosa and eating disorders among 15–56% of patients with alcohol use disorder . They arMore research efforts are needed to develop valid and improved clinical measures of binge behaviors, to identify plausible transdiagnostic psychological mechanisms that would provide information on the onset, continuation, and recurrence of binge behaviors and, to recognize the consequences according to type of bingeing, possible co-occurrence of behaviors, and individuals’ sociodemographic characteristics ,44. ThusSeveral studies have observed that both binge behaviors arise in individuals with certain psychological, cognitive, familial, and social characteristics that make them more vulnerable to developing binge episodes. Among the psychopathological aspects, both BD and BE have been associated with depressive symptomatology, anxiety, substance abuse, asocial behaviors, and suicide attempts ,46. ThesNeuropsychological profile has been also involved in binge behaviors . Thus, aWith respect to the family environment, it has been found that families which are poorly flexible, highly disengaged, and with communication problems among members served as risk factors for BE behavior . Some stRegarding social factors, peer pressure and the influence of the social media are important variables in the onset of binge behaviors ,95. ThusTherefore, it seems that there are many psychopathological, personality, cognitive and social factors that seem to predispose adolescents to these unhealthy and risky behaviors. It would be interesting to design prevention programs focused on them, as well as to understand the type of relationship between both binge disorders (BD and BE). This last aspect will be addressed in the following section, although more longitudinal studies would be needed.–Title: Identify the study as relevant for the topic of the review.–Objectives: Provide an explicit statement of the main objective(s) or question(s) the study addresses.–Methods: Specify the inclusion and exclusion criteria for the sample of the study. Specify the information about the methodology performed.–Data: Specify the methods used to analyse the results.–Results: Present results for main outcomes and if comparing groups, indicate the direction of the effect .–Discussion: Provide a summary of the limitations of the results, as well as a general interpretation of the results and important implications.For this purpose, we performed a systematic review following the guidelines for systematic reviews and meta-analyses (PRISMA)  and the The inclusion criteria were articles studying the relationship between BD and BE measured by standardized questionnaires in adolescents (12 to 17 years old) and the young population (18 to 25 years-old), and studies providing a correlation coefficient value or odds ratio between BD and BE, from the last 20 years (2002–2022) available up to 15 July 2022. Exclusion criteria were (a) unpublished research; (b) books, reviews, comments, editorials, master’s theses, or dissertations .The meta-analysis was conducted using the Metafor package . The corp < 0.05) between binge drinking and binge eating , a Random Effect (RE) Model was applied to obtain the pooled correlation coefficient .After the search process, fifteen studies were included in the meta-analysis . The tote eating . Given tp = 0.72) and Rank Correlation Test for Funnel Plot Asymmetry showed no small-study effects  [Each correlation coefficient is represented in a forest plot in  = 0.86) ,121.We also analyzed the odds ratio between binge drinking and binge eating  Table S. Only twOverall, discrete results were found regarding the direct association between binge drinking and binge eating in both correlation coefficients and the odds ratio. However, the magnitude of this association could increase when adding mediation and moderation variables . For insThe objective of this study was to analyze the relationship between BD and BE in young and adolescent people. For this purpose, we performed a quantitative and systematic review to conduct a meta-analysis that could shed light on the co-occurrence between both binge behaviors in adolescents and young people. Following the established inclusion and exclusion criteria , fifteen studies were included in the meta-analysis comprising a total sample of 72,510 adolescents and young people with a mean age of 17.61 years.The meta-analysis displayed in this manuscript determined a rather small effect or association between these two variables (BD and BE). The positive correlation found in the RE Model (r = 0.12), even though significant, is lower than expected by previous scientific literature . This reFurthermore, and as we mentioned before, it is possible that other variables are mediating the relationship between these binge behaviors. Thus, several studies have pointed to different motives to initiate these sorts of unhealthy behaviors ,125,126.According to our search strategy, our meta-analysis was composed of studies carried out with adolescents and young people of both sexes, so it is possible that this aspect could have affected the results. Thus, it is well known that eating disorders are more common in women, specifically during the youth, whereas BD is more prevalent in men as a way of entertainment and socialization ,136. FurFinally, we must also highlight the importance of determining the accuracy of the screening tests employed in the different studies to detect BD and BE. Thus, much of the research that has used the AUDIT, or its reduced versions, has assessed BD in very distinct manners, with most of the studies considering only the number of drinks consumed without referring the strength of the drink or without detailing the number of hours of drinking or only analyzing the consumption from the past week ,139,140.In conclusion, this study contributes towards a deeper understanding of the relationship and co-occurrence between BD and BE in adolescents and young people. Through a review of all studies carried out to date, we observed a discrete relationship between both binge behaviors which suggest that more variables mediating BD and BE must be considered to shed light on this aspect. As a consequence, better prevention and personalized treatment approaches could be developed for vulnerable adolescents and young people who suffer from alcohol abuse and/or eating disorders.


Exposure to per- and polyfluoroalkyl substances (PFAS) during pregnancy has been suggested to be associated with neurobehavioral problems in offspring. However, current epidemiological studies on the association between prenatal PFAS exposure and neurobehavioral problems among offspring, especially attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), are inconsistent. Therefore, we aimed to study the relationship between PFAS exposure during pregnancy and ADHD and ASD in offspring based on meta-analyses. Online databases, including PubMed, EMBASE, and Web of Science, were searched comprehensively for eligible studies conducted before July 2021. Eleven studies (up to 8493 participants) were included in this analysis. The pooled results demonstrated that exposure to perfluorooctanoate (PFOA) was positively associated with ADHD in the highest quartile group. Negative associations were observed between perfluorooctane sulfonate (PFOS) and ADHD/ASD, including between perfluorononanoate (PFNA) and ASD. There were no associations found between total PFAS concentration groups and neurobehavioral problems. The trial sequential analyses showed unstable results. Our findings indicated that PFOA and PFOS exposure during pregnancy might be associated with ADHD in offspring and that prenatal PFOS and PFNA exposure might be associated with ASD in offspring. According to the limited evidence obtained for most associations, additional studies are required to validate these findings. Perfluoroalkylated substances (PFASs) are forms of persistent organic pollutants, which have the characteristics of bioaccumulation, long-distance migration, and high toxicity, and they have adverse effects on the environment and human health ,2,3. SinThe National Biomonitoring Program from CDC states that at least one PFAS can be detected in blood samples among the U.S. population , and numCurrent epidemiological studies on the association between prenatal PFAS exposure and neurobehavioral problems in offspring remain unclear. Several studies have reported a positive association between PFAS and the risk of ADHD and ASD ,43,44,45This research study rigorously refers to the principle of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement , and we The authors (HJY and YYF) separately screened all studies by titles and abstracts and ascertained the eligible studies by reading the full text. The studies that were eventually included met the following criteria: (1) observational study design, including case–control or cohort studies; (2) exposure to at least one PFAS , perfluorooctane sulphonate (PFOS), perfluorononanoic acid (PFNA), perfluorohexane sulfonic acid (PFHxS), and perfluoroalkane sulfonamido substances); (3) measure PFAS exposure during pregnancy using maternal blood samples ; (4) the results are either prenatal neurological or child neurological as related problems; and (5) risk estimates are provided, including odds ratios (OR), relative risk (RR), or hazard ratio (HR) and 95% confidence interval (CIs). Laboratory research, non-human animal research, letters, and reviews were excluded. When the same data appear in multiple studies, only studies with the largest data sets are included in the analysis. The screening process of document screening is shown in the flowchart.Due to the limited amount of related research, only two neurobehavioral diseases, ADHD and ASD, were taken into consideration in our study. The diagnosis of ADHD and ASD in offspring may be determined by medical institution registration, expert opinion, or questionnaire survey.The following elements were extracted from each eligible study: name of the first author; year of publication; country; neurobehavioral outcome; type of PFAS; the number of pregnant women; age of the pregnant women; biosample type; pregnancy week of sample collection; study time; maximum adjustment of ORs, RRs or HRs and 95% CIs; adjustment of covariates. The Newcastle–Ottawa Quality Assessment Scale (NOS)  was used2 and p-value, and p-value < 0.05 was regarded as heterogeneous, with an I2 statistic < 25% indicating low, 25–50% indicating moderate, and >50% indicating high heterogeneity. A random-effects model was used in cases when I2 ≥ 50% [In this research study, Stata software (version 16) was used for statistical analyses. We used quantitative meta-analysis when there were ≥ 3 qualified studies on the specific association between PFAS exposure in pregnancy and children’s neuro-related behaviors that contain identical types of data. A simplified summary was conducted when qualified studies were less than three. Pooled risks and 95% CIs with the fixed-effects model or the random-effects model were assessed as the main statistical method according to the heterogeneity. The heterogeneity of the articles involved was tested with the II2 ≥ 50% .2 score [When there were more than 3 eligible studies, we conducted a dose–response meta-analysis using linear and non-linear models and selected the significant model with the best goodness-of-fit χ2 score . When ex2 score . Since t2 score .To assess the publication bias in this study, Begg’s test and Egger’s regression asymmetry test were performed. A funnel chart was used to evaluate the results. Simultaneously, the sensitivity analysis was carried out to observe the stability of the comprehensive results.The risks of random errors were tested by the trial sequential analysis (TSA) with the Stata package (metacumbounds command), aiming at maintaining an overall 5% risk of a Type I error and a power of 80%. The information size calculation for meta-analyses  was combined with an adapted threshold of statistical significance in the cumulative meta-analysis. With the control event’s proportion calculated from the actual meta-analysis in the calculation of the required information size, an intervention effect of a 20% relative risk reduction (RRR) was anticipated .A total of 1755 articles were retrieved by a literature search of PubMed, Embase, and Web of science. After the removal of 219 duplicates, 1536 studies were further screened for title and abstract. A total of 1424 articles were removed due to systematic reviews, cross-sectional studies, and other unrelated topics. We excluded 101 of 112 articles due to the unavailable concentration of PFASs during maternal pregnancy, lack of quantitative estimates, or duplicate publications. Finally, the remaining 11 articles were included in the present meta-analysis . Two of n = 7), PFOS (n = 7), PFNA (n = 3), and PFHxS (n = 3) on ADHD were included. In the total concentration group, the summarized evidence suggests that there is no significant association between prenatal PFAS exposure and ADHD in offspring. Pooled estimates for comparisons of the highest vs. lowest quartile showed that PFOA  and PFOS  were significantly associated with ADHD  and PFNA  were negative for ASD compared to the lowest category , suggesting that the summary result might be unstable.The highest quartile arrays of PFOA and PFOS associated with ADHD, including the highest quartile array of PFOS and PFNA associated with ASD, were subjected to trial sequential analyses. No publication bias was found in this meta-analysis .In this systematic review and meta-analysis, we systematically gathered the available evidence on the effect of prenatal PFAS exposure with respect to the outcome of neurobehavioral problems in future generations. We included 11 articles in the present study. In the total concentration group, the relationships between PFAS  and ADHD or ASD could not be identified. However, in the highest quartile group, PFOA is positively associated with ADHD, while PFOS is negatively associated with ADHD and ASD. PFNA is negatively correlated with ASD when compared with the lowest quartile group. There is no publication bias in this study. Unlike the study designed by Joan et al. , we direIn the highest quartile group, PFOA exposure increased the risk of ADHD in future generations, which is consistent with the results of previous animal studies ,62. PregIn the total concentration group, there is no significant association between PFAS exposure and ADHD, which is consistent with many of the studies ,72,73,74There are several advantages in the present study. This is one of the first studies to comprehensively and systematically evaluate the relationship between prenatal exposure to PFAS and neurobehavioral problems in offspring. More than 8000 participants were included in this study, which makes the summary results more reliable. The use of various statistical methods also improved the effectiveness of meta-analysis. However, due to the lack of existing studies, sequential analyses suggested that the summary result might be unstable. In addition, hierarchical analyses cannot be conducted. According to the different study designs and methods, the dose–response analyses cannot be accurately assessed based on the dose–response relationship. Therefore, more in-depth studies are needed.In summary, PFOA, PFOS, and PFNA exposure during pregnancy were found to be associated with ADHD and ASD in offspring in the highest quartile group. The findings indicated that prenatal PFAS exposure and neurobehavioral problems in offspring are not linear associations, but the research result is unstable. More research should be encouraged to further study its associations and mechanisms of action.


This study aimed to systematically review the effect of cognitive behavioral therapy (CBT) in terms of improving the quality of life (QOL) and negative emotion of informal cancer caregivers.PubMed, Cochrane Library, EMBASE, Web of Science, MEDLINE, China National Knowledge Infrastructure (CNKI), and China Biology Medicine disc (CBMdisc) were searched from the database establishment to October 2021. Literature screening, data extraction, and quality evaluation were conducted based on inclusion and exclusion criteria. Stata 14.0 software was used for data analysis.SMD = 0.28, 95%CI: −0.09–0.65, P < 0.001). However, the improvement of depression in CBT intervention group was significantly better than that in control group . The HADS subgroup showed differences in depression scores . The overall effect of CBT on anxiety was statistically different, the improvement of anxiety in CBT intervention group was significantly better than that in control group .A total of 17 randomized controlled trials (RCTs) involving 2,348 cancer informal caregivers (CGs) were included in this study, with an overall loss rate of 13.3%. Meta-analysis showed no statistically significant difference in the impact of CBT on QOL (CBT had a positive effect on reducing depression and anxiety in informal cancer caregivers, and the effect on quality of life was not statistically significant, but showed a positive trend.https://inplasy.com/generate-invoice/, identifier: INPLASY202230120. With the incidence of cancer increasing year by year . Not onlConsidering the progress in studies concerning cancer caregivers since 2011, psychosocial interventions to caregivers are not just confined to one single outcome variable; instead, more than two outcome variables are taken into consideration. For example, some studies involved interventions directed on the quality of life (QOL), depression, anxiety, sleep, or self-efficacy of caregivers . A largePublications from establishment of the database to October 2021 were systematically selected. A literature search was conducted in the following digital databases: PubMed, the Cochrane Library, EMBASE, Web of Science, MEDLINE, China National Knowledge Infrastructure (CNKI), and China Biology Medicine DISC (CBMdisc). The search strategy followed the PICO model: Population: informal cancer caregivers; Intervention: cognitive behavioral therapy; Comparison: routine nursing/health education, or blank control; Outcome: QOL, depression, or anxiety.Keywords related to oncology  were combined with keywords related to the population (caregiver OR carer OR caregiving OR spouse OR relative OR partner OR family) and the intervention . In addition, a backward search  of reference lists of identified studies was conducted, and earlier systematic reviews together with a forward search (citation tracking) until no additional relevant studies were found.All studies selected for final inclusion met the following criteria: (1) interventions must include informal caregivers, alone or with patients with cancer. (2) The intervention content of the study should conform to the CBT content standard, include at least one of the following components, and be considered as CBT : cognitiIn addition, studies involving children with cancer were excluded as well as those involving drug interventions, because of the nature of the parent-child relationship. All previous studies were evaluated independently by two researchers, and disagreements over the inclusion/exclusion of the study were resolved by consensus. A literature search focused only on studies published in peer-reviewed journals to enhance the rigor of the methodology examined.A pair of raters reviewed relevant studies and extracted data. In consideration of the heterogeneity of interventions and data, this study adopted the Cochrane Reviewer Handbook 5.1.0  as the rTwo researchers conducted data extraction by reading the full text to determine the indicators for analysis independently. Descriptive data were extracted based on the following four aspects: literature characteristics, participant characteristics, intervention plan, measurement indicators, and test tools. Literature characteristics included author and year of publication. Participant characteristics included types of cancer, number of participants, and average age. The intervention plan included intervention content and follow-up. Measurement indicators and test tools included testing tools for QOL, depression, and anxiety in patients with cancer. The outcome indicators included QOL, depression, and anxiety measurement results  was selected as the effect scale index for statistics. The magnitude of effect indicated the degree of influence of CBT on informal cancer caregivers. The effect values were all expressed in a 95% confidence interval (CI). Heterogeneity was explored using First, the researcher preliminarily screened 1980 relative studies in the literature. After removing duplicates, screening titles and abstracts, and reviewing the full text, 17 studies met the criteria, with 2,348 informal cancer caregivers. All of 17 studies reported the changes in life quality, depression, or anxiety of informal cancer caregivers after the intervention. A summary of the results of the literature search and screening process is shown in A summary of all study characteristics is shown in The average age of the caregivers was 57.25 and were primarily spouses, adult children, parents, siblings, friends or significant others of cancer patients. Except for studies that did not report cancer types, almost every study included spouses/partner. Three studies specifically focused on spouses or partners , 18, 22.The results of the ROB assessment are shown in SMD = 0.28, 95%CI: −0.09–0.65, P < 0.001), the forest plot of pooled effect estimate for quality of life in SMD = 0.12, 95%CI: −0.32–0.57, P = 0.029; I2 = 88.0%, P < 0.001), meta-regression analysis showed that publication age was not correlated with inter-study heterogeneity (P = 0.958). The results of sensitivity analysis are shown in I2= 77.3%, P = 0.001), but the difference in QOL score between the two groups was still not statistically significant , and the forest map of effect estimation is shown in P = 0.960).Ten studies compared the two groups with QOL. Seven studies adopted CQOL-C, while the other three were different. Subgroup analysis was performed according to different measuring tools, and the results showed that there was no significant difference in quality of life between the two groups , with moderate heterogeneity , and the forest map estimated by comprehensive effect is shown in SMD = −0.80, 95%CI: −1.30 to 0.29, P = 0.002; I2 = 51.6%, P = 0.127); the heterogeneity was almost negligible in CES-D subgroups , but there was no significant difference in depression scores . There was no significant publication bias (P = 0.803), and the Egger's test results were shown in A total of 12 studies compared depression scores between the two groups. Among them, CES-D was used in five studies to measure depression score, and HADS was used in three studies [Hudson et al.  used HADSMD = −0.36, 95%CI: −0.720 to −0.004, P = 0.047), with moderate heterogeneity . The forest map estimated by comprehensive effect size is shown in SMD = −0.31, 95%CI: −0.94–0.32, P = 0.337), and there was high heterogeneity between HADS subgroup . Meta-regression analysis of HADS subgroup excluded the influence of publication years (P = 0.627). The results of sensitivity analysis were shown in I2 = 0.0%, P = 0.957). However, the difference between the two groups was still not statistically significant , and the forest map of effect size estimation was shown in P = 0.339).Eight studies compared anxiety scores between the two groups after the intervention. Four of the studies used HADS to measure anxiety scores, and the other four used different scales. Meta-analysis showed statistically significant difference in anxiety scores between the two groups , but with moderate heterogeneity, while the CES-D subgroup showed no significant differences in depression scores between the two groups, with no heterogeneity. Therefore, we suggested that the effect of CBT on depression in informal cancer caregivers might be influenced by different measurement tools, in addition to the specific intervention content of CBT. Carefully selecting measurement tools, such as HADS, to assess depression may be more meaningful in the future. The overall effect of CBT on anxiety was statistically different, but the difference was no longer significant after the literature was excluded by subgroup and sensitivity analyzes. These were not consistent with the results of previous studies. One study (P = 0.008), but the result was limited to the application of CQOL-C to assess the integration of the three studies. Depression were discussed by descriptive analysis. This study included more RCTs and extracted more outcome indicators, and CBT interventions used in RCTs were different. Therefore, this study from clinical sense could not completely deny the effect of CBT intervention measures.Three outcome indicators were extracted: QOL, depression, and anxiety. Subgroup analysis, meta-regression, and sensitivity analysis were performed to eliminate the bias caused by confounders for QOL, but the results were not satisfactory. After excluding the RCTs that had a large impact on heterogeneity, the difference between the two groups was still not statistically significant. However, the result was stably reliable, that is, from the statistical sense, the improvement effect of CBT on the QOL of the informal cancer caregivers was not obvious. Regarding the effects of CBT on depression, the combined effect size showed significant differences between the two groups, but the results showed moderate heterogeneity. Subgroup analysis showed that the HADS subgroup had significant differences , different CBT intervention contents , same ending index selection of different measurement tools, and many other factors. Third, this study did not account for the fact that different CBT intervention might bring about different effects on informal cancer caregivers. For example, the CBT interventions by face to face and mobile phones might be problematic in evaluating efficacy. Fourth, some studies did not carry out follow-up evaluation and the follow-up time and evaluation indexes were not consistent in the follow-up studies; hence, the overall long-term intervention effect could not be counted. Hence, it is difficult to provide specific recommendations for certain timings and frequency of the interventions.This meta-analysis showed that CBT had a positive effect in terms of reducing depression and anxiety in informal cancer caregivers, did not reach statistical significance for QOL, but showed positive trends. The literature included in this study was limited, and hence its conclusions need to be further confirmed by more large-sample, multicenter randomized controlled studies. In the future, studies should be conducted according to the specific situation of the research object, including the type of cancer, cancer stage, relationship between patients and caregivers, sex of the caregiver, and so on. They should generate corresponding intervention content, have an appropriate evaluation time, and select reasonable measurement tools to enhance the QOL of informal cancer caregivers.YW and YB conceptualized the research. SZ and QW conducted the literature search. SZ and GY were responsible for data extraction and carried out the meta-analysis. SZ drafted the protocol and the initial manuscript while HR reviewed them and made suggestions for revisions. All authors revised and approved the final version.This study was funded by National Science and Technology Support Program (Grant No. 2021ZD0200701) and Project of Hebei Provincial Finance Department (LNB202016).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.


Is statin use during androgen-ablative therapies (androgen deprivation or androgen receptor axis–targeted therapies) associated with reduced mortality among men with prostate cancer?In this systematic review and meta-analysis of 25 cohorts including 119 878 men, concurrent statin use was associated with a 27% reduced risk of overall mortality and a 35% reduced risk of prostate cancer–specific mortality.These findings suggest that concurrent statin use may improve survival in men receiving androgen-ablative therapies for advanced prostate cancer; randomized clinical trials are warranted to confirm these findings. This systematic review and meta-analysis quantifies the association between concurrent statin use and overall and prostate cancer−specific mortality among men undergoing androgen-ablative therapies for advanced prostate cancer. Epidemiological evidence supports a role for statins in improving survival in advanced prostate cancer, particularly among men receiving androgen-ablative therapies.To study the association between statin use and survival among men with prostate cancer receiving androgen deprivation therapy (ADT) or androgen receptor axis–targeted therapies (ARATs).This systemic review and meta-analysis used sources from MEDLINE, EMBASE, Epub Ahead of Print, Cochrane Clinical Trials, Cochrane Systematic Reviews, and Web of Science from inception to September 6, 2022.Observational studies reporting associations of concurrent statin use and survival outcomes (in hazard ratios [HRs]).Two authors independently abstracted all data. Summary estimates pooled multivariable HRs with 95% CIs using the generic inverse variance method with random-effects modeling. A priori specified subgroup and sensitivity analyses were undertaken, and heterogeneity, study quality, and publication bias were evaluated. Confidence in the evidence was assessed using the GRADE  approach.Overall mortality and prostate cancer–specific mortality (PCSM).I2 = 83%) and a 35% reduction in the risk of PCSM , with substantial heterogeneity in both estimates. Subgroup analyses identified a PCSM advantage associated with statins for men receiving ARATs compared with ADT alone . Confidence in the evidence was rated low for both outcomes.Twenty-five cohorts of 119 878 men (65 488 statin users [55%]) with more than 74 416 deaths were included. Concurrent statin use was associated with a 27% reduction in the risk of overall mortality (HR, 0.73 ; The findings of this meta-analysis show that concurrent statin use was associated with reduced overall mortality and PCSM among men receiving androgen-ablative therapies for advanced prostate cancer. These findings are limited by the observational nature of the data and residual unexplained interstudy heterogeneity. Randomized clinical trials are warranted to validate these results. With a median survival of 3 to 6 years from ADT initiation,3 there is an urgent need for therapies that can delay progression and improve survival in this population.Androgen deprivation therapy (ADT), whether through bilateral orchidectomy or luteinizing hormone–releasing hormone agonists or antagonists, is the standard of care for men with advanced prostate cancer.4 One potential cohort includes men receiving castration therapy. Preclinical studies suggest that statins may work synergistically with androgen-ablative therapies to limit intratumoral steroidogenesis5 and inhibit adrenal androgen transport into prostate cancer cells.6 Observational data support this mechanism and suggest a survival advantage in men with CRPC. Indeed, statins appear to prolong the time to progression while using ADT and ARATs.7 A recent meta-analysis8 found statins to be associated with a modestly lower risk of biochemical recurrence; however, this association was nullified after excluding men receiving ADT. Several additional studies have since reported a protective association between statins and survival among men receiving androgen-ablative therapies.9Statins, which are prescribed to lower cholesterol levels, have drawn recent attention as a potential adjunctive therapeutic in prostate cancer. Although statins appear to preferentially benefit later-stage disease, the subpopulation in which statins may be most efficacious remains unclear.A comprehensive up-to-date synthesis of this association to aid clinical decision-making is lacking. Thus, we conducted a systematic review and meta-analysis to quantify the association between concurrent statin use and overall mortality and prostate cancer-specific mortality (PCSM) among men undergoing androgen-ablative therapies for advanced prostate cancer.Cochrane Handbook for Systematic Reviews of Interventions10 and reported in compliance with the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Our study protocol was registered (PROSPERO identifier: CRD42021237047). This study was exempt from research ethics board review as per University of Toronto guidelines on human research.11This study was conducted in accordance with the Using a librarian-guided comprehensive search strategy, MEDLINE, EMBASE, Epub Ahead of Print, Cochrane Clinical Trials, Cochrane Systematic Reveiws, and Web of Science were searched from inception to September 6, 2022  between concurrent statin use and survival outcomes  in men undergoing androgen-ablative therapies for prostate cancer were eligible. To minimize influence of prevalent users, studies that evaluated statin exposure before initiation of castration therapy were excluded. Titles and abstracts of all studies were initially assessed by 1 author (V.H.J.) and a full-text review was undertaken by 2 independent authors (V.H.J. and R.C.). If multiple publications derived data from the same cohort, preference was given to the study that provided larger sample sizes, was available as full text, or reported more complete data for subgroup analyses. All discrepancies were resolved by discussion, and by consulting a senior author (R.J.H.) when necessary.Two authors (V.H.J. and R.C.) independently extracted relevant demographic, exposure, outcome, and statistical data from eligible studies. Subpopulation-specific data  were preferred, as opposed to pooled estimates, whenever possible. Individual study authors were contacted for additional data. Data on race and ethnicity were not specifically available in the published reports.12 A study was considered high quality with a low risk of bias if the NOS score was greater than 6 points.The Newcastle-Ottawa Scale  quantified risk of bias across the domains of cohort selection (4 points), comparability of design or analysis (2 points), and adequacy of outcome measures (3 points).13 Two authors (V.H.J. and R.C.) without conflicts of interest related to this study reviewed the synthesized evidence and downgraded its certainty based on study design, risk of bias, inconsistency, indirectness, and imprecision.The GRADE  approach was used to evaluate the quality of evidence for the primary outcomes and categorized as high, moderate, low, or very low.The 2 primary outcomes consisted of the association between concurrent statin use and overall mortality and PCSM. For each, we meta-analyzed individual HRs with corresponding 95% CIs from the most adjusted multivariable model, using the generic inverse variance approach with random-effects modeling. Pooled summary estimates were reported as HRs with 95% CIs.Q test (significant at α < .10) and quantified using the I2 statistics . Subgroup analysis by meta-regression was undertaken if heterogeneity was significant and at least 10 cohorts were available. A priori subgroups included median age (≤70 vs >70 years), baseline metastasis (nonmetastatic vs mixed vs metastatic), hormone sensitivity (HSPC vs CRPC), type of androgen-ablative therapy (ADT vs ARAT), type of primary treatment , adjustment for cardiovascular covariates (yes vs no), and NOS-based study quality (high vs low).Interstudy heterogeneity was determined using Cochran 14 we performed a sensitivity analysis by removing all studies potentially susceptible to immortal time bias. A cohort was considered susceptible if (1) no time-dependent analysis was performed or (2) information regarding the timing of statin exposure was not established or available.We performed 4 a priori specified sensitivity analyses. We first removed each cohort individually from the meta-analysis and recalculated the summary estimate (leave-one-out approach). Second, we removed all studies that were available only in the form of abstracts. Third, to evaluate for any undue influence of small studies on the summary estimate, we repeated the meta-analysis using fixed-effects modeling. Last, owing to the vulnerability of cohorts of statin users to immortal time bias because patients have to survive long enough to start statin therapy,A dose-response analysis was planned a priori; however, because insufficient data were available for meta-analysis, only a systematic review was reported. Similarly, analyses of statin class (hydrophilic vs lipophilic) were precluded by limited data availability.P < .10 indicated significant publication bias).Publication bias was assessed by visually inspecting funnel plots for asymmetry. Results were formally tested using the Egger test . All other analyses were undertaken on R, version 3.6.1 . GRADE assessments were performed on GRADEpro (McMaster University and Evidence Prime Inc).33 reporting data from 25 cohorts of 119 878 men (65 488 [55%] statin users) to be included , whereas PCSM was reported in 14 cohorts (10 publications33).Systematic literature review identified 5190 records, of which 54 reports were reviewed in full. After completing full-text reviews , we identified 19 publications29 multicenter cohorts in 7 studies,33 and single-institution experiences in 5 studies.28 The median age across study participants ranged from 62 to 75 years. Most cohorts consisted of men with newly diagnosed hormone-sensitive disease (n = 16). Seventeen cohorts33 had ADT exposure as the primary androgen-ablative therapy, whereas 7 cohorts25 had ARAT exposure . Eight cohorts31 included chemotherapy-naive patients, whereas 5 cohorts29 evaluated patients post chemotherapy, and 8 cohorts33 evaluated both.Individual cohort characteristics are summarized in the 33 patient interviews,29 and retrospective medical record reviews31; methods of exposure assessment were not reported in 2 cohorts.25 All studies evaluated statin exposure occurring concurrently alongside androgen-ablative therapies.Cohorts ascertained statin use from prescription databases,20 reported multivariable-adjusted models; 2 cohorts32 adjusted for propensity scores  in random-effects meta-analysis .Nineteen retrospective cohorts of 108 512 men (61 950 [57%] statin users) with more than 73 885 mortality events (deaths reported for 12 cohorts) were included in a meta-analsis.analysis , with siI2 = 83%), although 58% of the observed association was weighted on 1 cohort. Removal of this cohort diminished the magnitude of the association, although the pooled estimate remained significant . Last, removing cohorts susceptible to immortal time bias31 did not significantly change the overall association .None of the a priori subgroups modified the observed association or the interstudy heterogeneity . The dir33 assessed a statin dose-response association for overall mortality  to 0.90  in the highest exposure categories.3 One study19 used a continuous model per milligram of statin dose equivalent and failed to identify a significant dose-response association .Four studiesP = .57). Study quality was high  for 13 of 19 studies33  in random-effects meta-analysis .Fourteen retrospective cohorts of 115 612 men (64 511 [56%] statin users) with more than 12 408 mortality events (deaths reported for 11 cohorts) were included in a meta-analysis.analysis , with si19 with 589 patients) compared with men with HSPC or those receiving ADT (12 cohorts33 with 115 014 patients) . Neither the directionality nor the significance of the observed association were altered by systematic removal of individual cohorts from the pooled analysis  or by removing 1 cohort available only as an abstract . Recalculating the meta-analysis using a fixed-effect model did not suggest a strong influence of small studies , although 52% of the observed associated was weighted on 1 cohort. Removal of this cohort from the fixed-effects model reduced the magnitude of the association, although the pooled estimate remained significant . Last, removing cohorts susceptible to immortal time bias31 did not significantly alter the overall association .Of the evaluated a priori subgroups, castration sensitivity (HSPC vs CRPC) and androgen-ablative therapy type (ADT vs ARAT), both with identical cohort distributions across subgroups, significantly modified the pooled association . Statin 33 assessed a statin dose-response association for PCSM  to 0.74  in the highest categories. One cohort19 used a continuous model per milligram of statin dose equivalent and failed to identify a significant dose-response association .Four cohortsP = .64). Study quality was high (NOS score >6) for 13 of 14 cohorts33 38 suggest a modest 10% to 12% risk reduction in biochemical recurrence with statins. This benefit, however, was rendered null after men receiving ADT were excluded from analyses.The literature supports a protective association of statins in preventing high-grade disease, with little to no association with low-grade disease.9 noted a survival advantage of 25% to 35% among statin users before and after diagnosis, although subpopulation-specific assessments were not reported. Interestingly, a more recent cohort study39 identified a 20% lower risk of PCSM among men with postdiagnostic use of statins, although subgroup analyses revealed this risk reduction to be limited to men receiving hormonal therapy, with no advantage for men after surveillance, radical prostatectomy, or radiation therapy.The most consistent evidence of an association between statins and prostate cancer comes from studies of survival outcomes. Two meta-analyses33 whereas 1 found no association.19 It is unclear why no association was noted in the study by Gordon et al,19 although the findings may relate to the dose classification used (continuous per-milligram simvastatin dose19 vs defined daily dose categories33) or the type of background androgen-ablative therapy (ARAT19 vs ADT33). Increasing duration of postdiagnostic statin use also appears to improve prostate cancer biomarkers in clinical trials,40 and studies of statins and prostate cancer survival among all men support a dose-response association.41 Taken together, there likely exists a dose-response association between statins and survival in advanced prostate cancer, although a specific dose cannot be recommended based on the available data. Considering that all cohorts evaluated men receiving statins for nononcologic indications, it stands to reason that commonly used moderate to high statin doses are likely sufficient to elicit the observed survival benefits.Our study represents, to our knowledge, the most comprehensive summary to date on the associations between statin therapy, androgen-ablative therapy, and prostate cancer. We observed a consistent overall and prostate cancer–specific survival advantage for statin users undergoing androgen-ablative therapies, independent of patient age, baseline metastasis status, prior use of chemotherapy, or primary treatment type. For overall mortality, the observed benefit was independent of hormone sensitivity status and type of androgen-ablative therapy. Conversely for PCSM, there was an incremental advantage of statins for men receiving ARATs compared with men receiving ADT. Although a dose-response analysis was planned as part of this study, the heterogeneity of available data precluded formal statistical assessments. Of the 4 cohorts that investigated a dose-response association, 3 suggested greater survival with increasing cumulative statin dose,4Several pathways may explain the observed association. Statins may inhibit inflammation, angiogenesis, cell proliferation, migration, adhesion, invasion, and promotion of apoptosis by disruption of cellular communication mechanisms.42 Indeed, lowering circulating cholesterol levels has been reported to decrease intraprostatic androgen levels and slow proliferation of prostate cancer.43 Moreover, statins and DHEAS enter prostate cancer cells via the same membrane transporter, SLCO2B1; statins competitively inhibit entry of DHEAS into prostate cancer cells, decrease available intratumoral androgen pools, and slow tumor proliferation.6 Reinforcing this mechanism at the population level, statin users were found to have a nearly 10-month longer time-to-progression while receiving ADT.6 Statins may also affect the ARAT, abiraterone, in a similar fashion. Abiraterone inhibits CYP17A, blocking the conversion of pregnenolone to DHEAS precursors, decreasing adrenal androgen biosynthesis.44 Abiraterone also enters prostate cancer cells through SLCO2B1 to elicit intraprostatic antineoplastic effects.45 Thus, statins and abiraterone may work together to lower circulating and intraprostatic DHEAS levels. Observational data buttress this pathway, reporting a nearly 5-month longer time to progression while statin users were receiving abiraterone.7In addition, a synergistic effect among statins, reduction of cholesterol levels, and androgen-ablative therapies may play a role. Cholesterol is a precursor for androgen biosynthesis. In the castration setting, testicular androgens diminish, and prostate cancer relies on adrenal androgens, namely dehydroepiandrosterone sulfate (DHEAS), and intratumoral de novo steroidogenesis to drive androgen-dependent tumor progression.46 Statins may work to negate some of the adverse cardiometabolic effects of androgen-ablative therapies, contributing to a survival benefit.Last, it is established that androgen-ablative therapies increase cardiometabolic risk by promoting visceral obesity, dyslipidemia, and dysglycemia.48 and may in part drive the statin–prostate cancer association,50 potentially contributing to residual confounding of these findings. Second, the retrospective nature of exposure assessment leading to uncaptured discontinuation of or nonadherence to statin therapy may limit the accuracy of the primary outcomes. Third, there remained unexplained interstudy heterogeneity in both primary outcomes. It is worth noting, however, that although variability remained considerable, the differences were between small and large protective associations; in other words, these findings appear to accurately support a statin benefit, although they may be restricted by imprecision.51 Fourth, possible influences of frequently encountered biases in studies investigating drug repurposing, namely immortal time bias and selection bias, must not be overlooked.52 Six cohorts included in this meta-analysis were susceptible to immortal time bias; however, a sensitivity analysis excluding these cohorts did not alter the primary results, suggesting minimal influence of immortal time. Although the influence of selection bias was not formally investigated, we restricted our analysis to statin users concurrently receiving androgen-ablative therapies, excluding cohorts with prediagnostic users to mitigate any overt effects of prevalent users. In our study, cohorts that analyzed prediagnostic users reported similar or worse survival outcomes, compared with new postdiagnostic users33; thus, it is unlikely that selection bias dramatically affected the observed association.Several limitations warrant discussion. First, the observational nature of these data limits causal inferences and raises the possibility of residual confounding from unadjusted prognostic factors. It is particularly noteworthy that serum cholesterol levels were not adjusted for in any included studies. Serum cholesterol levels appear to correlate with levels of prostate-specific antigenThe notion of incorporating a readily available medication with an established cardiovascular benefit and favorable toxicity profile, such as statins, in the treatment of prostate cancer is exciting. In this systematic review and meta-analysis of observational studies, we identified a significant overall mortality and PCSM advantage of concurrent statin use for men receiving androgen-ablative therapies.These results contribute to our understanding of the associations between prostate cancer, the androgen axis, and statins and provide high-quality evidence supporting a chemopreventive role for statins in prostate cancer. However, the use of retrospective data and unexplained heterogeneity lower our confidence in directly incorporating these findings into clinical practice. In seeking the optimal setting for statins to succeed in treating prostate cancer, work remains to delineate an optimal statin dose and class. The time is ripe for well-designed, randomized clinical trials to evaluate the effect of statins on prostate cancer survival.


The purpose of this study was to clarify the role of genetic factors on posttransplant diabetes mellitus (PTDM) risk.  Relevant publications were systematically retrieved from PubMed, EMBASE, and the Cochrane Library up to December 2020. Data from eligible case-control and cohort studies were extracted for qualitative and quantitative analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to estimate the association between gene polymorphisms and PTDM in the quantitative meta-analysis. TCF7L2 rs7903146 was significantly associated with PTDM risk in 5 genetic models (OR (95% CI): allelic: 1.59 (1.17–2.16), P=0.003; dominant recessive: 1.62 , P=0.007; recessive: 1.87 , P=0.007; homozygote: 2.21 , P=0.008; and heterozygote 1.50 , P=0.017). KCNQ1 rs2237892 was significantly correlated with PTDM risk in 3 genetic models , P < 0.001; dominant: 0.6 , P < 0.001; and heterozygote: 0.61 , P < 0.001). KCNJ11 rs5219 was significantly linked with PTDM in the recessive genetic model , P=0.047). No significant correlations of PTDM with TCF7L2 rs12255372, SLC30A8 rs13266634, PPARγ rs1801282, CDKN2A/B rs10811661, HHEX rs1111875, and IGF2BP2 rs4402960 polymorphisms were found.  A total of 43 eligible articles were identified, and 16 studies on 9 DNA variants from 8 genes were included in the meta-analysis. TCF7L2 rs7903146, KCNQ1 rs2237892, and KCNJ11 rs5219 may predispose kidney transplant recipients to PTDM. Large sample size studies on diverse ethnic populations were warranted to confirm our findings. The gene polymorphisms of  Approxiβ-cells . It has β-cells .TCF7L2 rs7903146, TCF7L2 rs12255372, KCNQ1 rs2237892, KCNJ11 rs5219, SLC30A8 rs13266634, PPARγ rs1801282, CDKN2A/B rs10811661, HHEX rs1111875, and IGF2BP2 rs4402960 have recently been detected and shown to affect PTDM occurrence. Among them, TCF7L2 rs7903146 had an established strong effect across different populations and is the most common susceptible gene for PTDM [TCF7L2 rs7903146 polymorphism and PTDM [γ, CDKN2A/B, HHEX, and IGF2BP2 with PTDM risk in all allelic and genotype models. Moreover, we reviewed the literature on genetic SNP markers susceptible to PTDM, which might help predict the risk of PTDM and facilitate the early prevention of this disease.More evidence suggests that genetic risk factors play a significant role in the development of PTDM. Many genes associated with diabetes mellitus (DM) have also been correlated with PTDM risk. Gene mutations such as single nucleotide polymorphisms (SNPs) are the most common type of genetic variation. SNPs of According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline , we systematically searched PubMed, EMBASE, and the Cochrane Library for studies published up to December 2020.The inclusion criteria included (1) kidney transplant recipients diagnosed with new-onset diabetes after transplantation (NODAT) or PTDM according to ADA or WHO guideline, (2) original studies examining the relationship between the gene polymorphism and NODAT or PTDM in patients after kidney transplantation, (3) study type: cohort or case-control studies, and (4) language restricted to English.When searching for possible eligible studies in the PubMed, EMBASE, and Cochrane Library databases, we used the mesh term of “kidney transplantation,” “polymorphism, genetic,” “posttransplant diabetes mellitus,” and “new-onset diabetes mellitus after transplantation,” as well as relevant keywords.The selection and inclusion of studies were performed in two stages by two independent reviewers, which included the analysis of titles/abstracts followed by the full texts. Disagreements were resolved by a third reviewer. Data retrieved from the eligible studies consisted of main demographical and clinical variables, including names of authors, publication year, study design, country, ethnicity, mean age, mean BMI, female percentage, genetic risk factors for PTDM, genotyping method and genotypes, diagnosis of PTDM, immunosuppressive therapy, time of PTDM diagnosis after transplantation, and age at transplant. We selected SNPs that showed significant associations with PTDM in allelic and/or genotype models from individual studies. The outcome was the evaluation of the impact of SNPs on the development of PTDM. Excel spreadsheet was used for the collection of extracted data. The methodological quality of included studies was evaluated by NOS. The base information was shown in Supplementary γ (rs1801282) C/G, CDKN2A/B (rs10811661) C/T, HHEX (rs1111875) C/T, IGF2BP2 (rs4402960) G/T, and KCNJ11 (rs5219) C/T polymorphism. The pooled OR was calculated for allelic effect of C/T, G/T, or C/G; dominant model of CC/CT + TT, GG/GT + TT, or CC/CG + GG; recessive model of TT/CC + CT, TT/GG + GT, or GG/CC + GC; homozygote model of CC/TT, GG/TT, or GG/CC; and heterozygote model of CT/CC, GT/GG, or GC/GG. The significance of the pooled OR was determined by the Z-test (P ≤ 0.05).Crude ORs with their 95% CIs were estimated and used to assess the strength of correlations of PTDM with TCF7L2 (rs7903146) C/T, TCF7L2 (rs12255372) G/T, SLC30A8 (rs13266634) C/T, KCNQ1 (rs2237892) C/T, PPARP < 0.10 indicated evidence of heterogeneity; https://doi.org/10.1136/bmj.327.7414.557). When significant heterogeneity (P < 0.10) was achieved, the random-effects model was used to combine the effect sizes of the included studies; otherwise, the fixed-effects model was adopted [Cochran's Q statistic was used to assess the heterogeneity among studies : allelic: 1.59 (1.17–2.16), P=0.003; dominant recessive: 1.62 , P=0.007; recessive: 1.87 , P=0.007; homozygote: 2.21 , P=0.008; and heterozygote 1.50 , P=0.017; In this meta-analysis, the TCF7L2 rs12255372 polymorphism to PTDM in five genetic models (OR (95% CI): allelic: 0.16 , P=0.314; dominant recessive: 1.18 , P=0.424; recessive: 1.36 , P=0.401; homozygote: 1.45 , P=0.317; and heterozygote 1.15 , P=0.529; The pooled analysis did not observe the susceptibility of SLC30A8 rs13266634 polymorphism was not found to be significantly correlated with PTDM in five genetic models (OR (95% CI): allelic: 1.28 , P=0.421; dominant: 1.29 , P=0.442; recessive: 1.43 , P=0.467; homozygote: 1.66 , P=0.396; and heterozygote 1.16 , P=0.593; KCNQ1 rs2237892 polymorphism with PTDM in three genetic models (OR (95% CI): allelic: 0.68 , P < 0.001; dominant: 0.6 , P < 0.001; and heterozygote: 0.61 , P < 0.001), but the association was not observed in other two genetic models (OR (95% CI): recessive: 0.87 , P=0.672, and homozygote: 0.75 , P=0.444; There was a linkage between γ rs1801282 polymorphism, no significant correlation was found in all five genetic models (OR (95% CI): allelic: 0.98 , P=0.885; dominant: 1.04 , P=0.772; recessive: 0.44 , P=0.213; homozygote: 0.44 , P=0.217; and heterozygote: 1.11 , P=0.505; Regarding PPARCDKN2A/B rs10811661 polymorphism was also not shown to be related with PTDM risk in all five genetic models (OR (95% CI): allelic: 1.10 , P=0.588; dominant: 1.51 , P=0.079; recessive: 1.06 , P=0.778; homozygote: 1.52 , P=0.092; and heterozygote: 1.54 , P=0.075; HHEX rs1111875 polymorphism, no significant correlation with PTDM risk was demonstrated in all five genetic models (OR (95% CI): allelic: 1.15 , P=0.283; dominant: 1.35 , P=0.067; recessive: 1.09 , P=0.735; homozygote: 1.30 , P=0.357; and heterozygote: 1.35 , P=0.051; With regard to IGF2BP2 rs4402960 polymorphism was not significantly associated with PTDM in all five genetic models (OR (95% CI): allelic: 0.97 , P=0.801; dominant: 0.92 , P=0.670; recessive: 0.23 , P=0.292; homozygote: 1.14 , P=0.532; and heterozygote: 0.88 , P=0.559; Similarly, the KCNJ11 rs5219 polymorphism was significantly associated with PTDM risk in the recessive genetic model (OR (95% CI): 1.59 , P=0.047), though no association was found in the other genetic models (OR (95% CI): allelic: 1.10 , P=0.651; dominant: 0.98 , P=0.929; heterozygote: 0.90 , P=0.641; and homozygote: 1.45 , P=0.228; In addition, the overall analysis revealed that TCF7L2 rs7903146, SLC30A8 rs13266634, and PPARγ rs1801282 with PTDM risk, the sensitivity analysis results showed that in all five genetic models, the reestimated ORs were all similar to the overall effects when excluding any individual study and assessing the remaining ones  [TCF7L2 rs7903146 loci has been linked with impaired insulin secretion and hepatic insulin resistance. The results of the association between TCF7L2 rs12255372G/T and PTDM remained conflicting [TCF7L2 rs7903146 and rs12255372 haplotype analyses did not reveal any significant association with PTDM [Previous studies indicated that these nine gene SNPs were associated with T2DM. Many genes associated with T2DM have also been associated with an increased risk of PTDM. T2DM and PTDM were thought to share certain common pathophysiological processes. Impaired insulin secretion and increased insulin resistance have been suggested as mechanisms underlying the development of PTDM. One of the most intensively studied genes was ecretion , 10. Twos (GWAS) . Its asss (GWAS) . The T aflicting , 12. TCFith PTDM .KCNQ1 rs2237892 SNP to PTDM, opposite effects of KCNQ1 rs2237892 polymorphism have been discussed. Hwang et al. showed that KCNQ1 rs2237892C/T, located in intron 15, was significantly associated with decreased risk of PTDM in both allelic and genotype models, suggesting a protective effect on the development of PTDM [KCNQ1 rs2237892 was correlated with a high risk of PTDM in an allele-specific manner [KCNQ1 encodes a subunit of the voltage-gated K + channel. It is expressed in the pancreas and may help regulate the membrane potential of insulin-secreting cells and is involved in triggering and maintaining glucose-stimulated insulin secretion , 43. Alt of PTDM . Kang etβ cells, as well as glucose metabolism. KCNJ11 rs5219 glutamic acid to lysine amino acid substitution reduces potassium channels' sensitivity to ATP molecules, resulting in overactivity of the channel and subsequent inhibition of insulin secretion [KCNJ11 rs5219 polymorphism with risk of T2DM [KCNJ11 rs5219 in susceptibility to T2DM in East Asians, Caucasians, and North Africans [The pooled analysis of KCNJ11 genes suggested its role in the pathogenesis of PTDM. ATP-sensitive potassium channel KCNJ11 plays an important role in the regulation of insulin secretion by pancreatic ecretion , 24, 25.Africans .γ, CDKN2A/B, HHEX, and IGF2BP gene polymorphisms with PTDM. In this overall analysis, these extensively evaluated genes were not found to contribute to the development of PTDM. SLC30A8 belongs to the zinc transporter family, which plays a major role in transporting zinc from the cytoplasm to intracellular vesicles for insulin maturation, storage, and secretion from β-cells [β-cell function, has been proposed as important genetic markers of T2DM in Europeans and East Asians but not the African population [γ gene belongs to the nuclear hormone receptor subfamily that controls the expression of genes involved in glucose and lipid homeostasis. The SNP rs1801282 (C/G) is the most common variant located in exon-2 of PPARγ, and the substitution of proline to alanine of PPARγ reduces its transcriptional activity and insulin sensitivity [PPARγ rs1801282 was significantly associated with T2DM under the heterozygote genetic model in Asian and Caucasian populations [β-cell regeneration. The locus rs10811661 locates ∼100 kb upstream of CDKN2A/B gene-coding sequence, but the mechanism by which this SNP affects T2DM and PTDM susceptibility remains to be investigated [IGF2BP2 rs4402960 suggested a significant association with T2DM in Asian populations [IGF2BP2, has been found to attenuate glucose-stimulated insulin secretion [Controversial results have been reported for the association of SLC30A8, PPAR β-cells , 38, 50.pulation , 55. PPAsitivity , 38, 41.ulations . CDKN2A/stigated , 38. HHEstigated , 38. Thestigated . The metulations . The mRNecretion , 38.KCNJ11 rs5219, PPARγ rs1801282, SLC30A8 rs13266634, and TCF7L2 rs7903146 polymorphisms were included, whereas the genetic variants of TCF7L2 rs12255372, KCNQ1 rs2237892, CDKN2A/B rs10811661, HHEX rs1111875, and IGF2BP2 rs4402960 were not studied. These GWAS revealed the most significantly associated pathway of β-cell apoptosis and dysfunction in the pathogenesis of PTDM.McCaughan et al. examined in GWAS the association between PTDM and 26 gene SNPs in the White population . This asTCF7L2 rs7903146 and KCNQ1 rs2237892 were correlated with higher PTDM risk, whereas the allelic distribution of TCF7L2 rs12255372, SLC30A8 rs13266634, PPARγ rs1801282, CDKN2A/B rs10811661, HHEX rs1111875, IGF2BP2 rs4402960, and KCNJ11 rs5219 was not linked with PTDM. Our meta-analysis included a number of updated publications till 2019, covering Asian, Caucasian, White, and African populations from both cohort and case-control studies. We comprehensively analyzed nine SNPs of eight genes in five allelic and genotype models, each model containing a minimum of three publications with complete data information, which would provide better power to identify alleles associated with PTDM susceptibility robustly. However, our study suggested KCNQ1 rs2237892 was correlated with lower PTDM risk in the allele model. Furthermore, significant associations with PTDM were found for TCF7L2 rs7903146 in the dominant, recessive, homozygote, and heterozygote genotype models; for KCNQ1 rs2237892 in the dominant and heterozygote models; and for KCNJ11 rs5219 in the recessive model. The meta-analysis by Quaglia et al. focused on TCF7L2 rs7903146 studies published from 2009 to 2014 and showed that TCF7L2 rs7903146 was strongly associated with PTDM in the dominant and recessive models, which was similar to our findings [The previous meta-analysis by Benson et al. collected case-control kidney transplant studies that were carried out in Asian, Caucasian, and mixed ethnicity populations up to 2015 and investigated the association between 18 genetic variants across 12 genes and PTDM in the allele model . They foHNF4A [ACE and AGT [Fox1) [adiponectin [PAI-1 [IRS [CAPN10 [PPARα, and POR [CCL5 [IL-6 [IL-1B, IL-2, IL-4, IL-17, IL-7R, and IL-17R [GPX1 599C to T mutation, increases the exposure of pancreatic β cells to oxidative stress and development of PTDM [ATF6, GST (SOD and CAT), INFγ and  polymorphisms, which play important roles in endoplasmic reticulum stress, oxidative stress, and inflammation respectively, were not found to be associated with PTDM [CYP3A4 and CYP24A1 were associated with increased risk of PTDM [GCK, LEP, LEPR, and PCK2 SNPs may contribute to PTDM by influencing glucose and lipid homeostasis [ABCC8 encoding SUR1 was implicated to be associated with a high prevalence of PTDM. Moreover, other inflammation genes including TLR4, TLR6 [MBL2 [HNF1β [MMP-2 SNPs may also predispose transplant recipients to the development of PTDM. The effect size of several genetic variants, such as GPX1 599TT, CYP24A1 rs2296241 AA, IL-17F rs763780TC, LEP rs2167270 AA, PCK2 rs4982856TT, TLR6 rs1039559 CC, and MMP-2 rs1132896 CC are relatively large (ORs between 3.5 and 10) [IL-1B rs3136558, IL-2 rs2069762, IL-7R rs1494558, IL-7R rs2172749, IL-17R rs2229151, IL-17R rs4819554 [MMP-2 rs243849 [IL-6 174 [TLR4 rs1927914 [PAI-1 −675 5G5G [CAPN10 SNP-63 rs5030952 [GWAS have identified more than 120 genetic loci associated with T2DM susceptibility . In addi and AGT , 44; insT [Fox1) , adiponeponectin , 40, andn [PAI-1 ; insulinI-1 [IRS ; glucose [CAPN10 , PPARα,  and POR , 36; andOR [CCL5 , 48, IL-L5 [IL-6 , IL-1B, d IL-17R , 29, 39  of PTDM , 49. Addith PTDM , 45, 49. of PTDM , 23. GCKeostasis , 23, 30.R4, TLR6 , MBL2 [1R6 [MBL2 , transcrrs243849 , IL-6 17675 5G5G , and CAPs5030952  were repThis study had several limitations. First, the etiopathogenesis of PTDM was multifactorial. Immunosuppressive regimen, ethnicity, older age, sex, BMI, and other related clinical characteristics contributed significantly to the risk of PTDM. However, crude estimates of effect were often used to evaluate the association between genes polymorphisms and PTDM without adjustments for other confounding variables. Second, PTDM in kidney recipients occurred mainly during the first months. Additionally, there could be a reversible phenotype change from PTDM to non-PTDM. In this study, there was high heterogeneity regarding the observational follow-up time after renal transplantation, which varied from 3 to 12 months among the studies. Third, treatment modality varied greatly for different studies, which may substantially influence the overall incidence of PTDM. Fourth, certain minor allele frequencies (MAF) differed greatly in different races. The sample size in some studies might be too small to detect minor effects, and some study populations presented with various genetic backgrounds. Furthermore, for most studies, it is unclear whether there was preexisting impaired glucose tolerance, which may affect the estimated incidence of PTDM.TCF7L2 rs7903146, KCNQ1 rs2237892, and KCNJ11 rs5219. Furthermore, we reviewed the literature on available gene SNPs that were susceptible to PTDM. The regulatory mechanism of relevant genes SNPs in the occurrence and development of PTDM was worthy of further exploration. SNPs showing association may serve as genetic markers for the prediction of the development of PTDM, combined with other risk factors of PTDM. Alternate medication of diabetogenic drugs may be considered for early prevention of PTDM based on risk assessment. Further large sample studies with diverse race populations are necessary to confirm our findings.Our meta-analysis revealed a significant association between PTDM and gene polymorphisms of


The association between vascular calcification (VC) and kidney stone is still inconclusive. Therefore, we conducted a meta-analysis to estimate the risk of kidney stone disease in subjects with VC.To identify publications from related clinical studies, we performed a search on PubMed, Web of Science, Embase, and Cochrane Library databases from their inceptions until 1 September 2022. According to obvious heterogeneity, a random-effects model was used to calculate the odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Subgroup analysis was conducted trying to dissect the effects of VC in different segments and population regions in predicting kidney stone risk.Seven articles were included with a total number of 69,135 patients, of which 10,052 have vascular calcifications and 4728 have kidney stones. There was a significantly higher risk of kidney stone disease in participants with VC versus control . Sensitivity analysis confirmed the stability of the results. VC can be separated into abdominal, coronary, carotid, and splenic aortic calcification while pooled analysis of abdominal aorta calcification did not indicate a significant higher kidney stone risk. An obvious higher risk of kidney stone was observed in Asian VC patients .Combined evidence of observational studies suggested patients with VC may be associated with an increased risk of kidney stone disease. Despite the predictive value was relatively low, it is still worth noting that patients with VC are under the threat of kidney stone disease. Kidney stone disease is a global health problem affecting approximately 10% adult population over the world . NotablyMoreover, observational studies have indicated associations between myocardial infarction or coronary heart disease (CHD) and stroke in kidney stone formers . CoronarSeveral observational studies have reported associations between kidney stone occurrence and coronary artery calcium score, carotid atherosclerosis or increased systemic calcification in abdominal and splenic aortic vessels . Howeverhttps://www.crd.york.ac.uk/PROSPERO/) as CRD42022357772. The report details are presented in Supplementary table 1.This meta-analysis was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA)  and regiSupplementary table 2. No restrictions to languages, regions and publication types were set. Two reviewers (Huang Linxi and Hu Junjie) independently screened article titles, abstracts and full texts to identify potential studies. The inclusion criteria were followed: (1) observational or cohort studies were eligible; (2) subjects were diagnosed with kidney stone or vascular calcification. Reviews, case reports, comments and duplicates were removed. The main flow-work was diagramed in We conducted a systematic review of the published literatures in electronic databases PubMed, Embase, Web of Science and Cochrane Library from their inceptions until 1 September 2022. The details of search strategies and results in mentioned databases are presented in Two independent reviewers (Huang Linxi and Xue Cheng) collected data from identified correlative studies and assessed the risks of bias. Any conflicting evaluations were solved by negotiations or consulting the third author (Guo Zhiyong). Information extracted from these studies included name of the first author, publication year, study district, study design, sample size and diagnostic evidence. We also assessed the risk of bias of included studies according to the basis of the Newcastle-Ottawa scale ,29. Tabl2I statistic. 2I ranges of 0–25%, 25–75% and over 75% are regarded as low, moderate and considerable heterogeneity, respectively. The random-effects model was used because of considerable heterogeneity between articles. Sensitivity analysis was conducted by excluding each enrolled study. Funnel plot, Egger and Begg tests were used to evaluate publication bias [All statistical analyses were performed using Review Manager 5.3  and R (version 4.0.3). The odds ratios (ORs) were used to compare dichotomous variables, and entire results were reported with 95% confidence intervals (CIs). Statistical heterogeneities among articles were assessed using the chi-square test, and heterogeneity was calculated using the ion bias .From the literature search in electronic databases, a total of 547 publications were retrieved. After duplicates removal, 98 records were excluded. six records identified from Cochrane Library were registered clinical trials and were ineligible. Screening of titles and abstracts excluded 414 records. Then the full texts of remaining 29 articles were retrieved for further evaluation. Of these, reviews, case reports, comments and animal researches were excluded and two clinical studies did not provide available numbers of patients diagnosed with kidney stone or vascular calcification. Thus, seven studies involving 69,135 participants were ultimately included for quantitative synthesis . The maj2I = 89%, p < 0.05) was substantial in our analysis, and random-effects model was used to evaluate the OR and its 95% CI. Pooled OR of kidney stone prevalence increased 1.54-fold in patients with vascular calcification compared with control participants  and no publication bias was observed .After the stratification of studies according to the regions, we found two studies conducted in America, one study conducted in the United Kingdom, three studies conducted in Asia and one in Arab state. Subgroup analysis according to the regions of participants indicated a significant higher risk of kidney stone risk in Asian participants (This meta-analysis provides the first comprehensive evidence for the association of vascular calcification with kidney stone risk. We demonstrated an overall 54% increased risk of kidney stone disease in patients with nonrenal vascular calcification in comparison with controls. This association persisted in sensitivity analysis. The enrolled studies reported vascular calcification in abdominal aorta, coronary, splenic and carotid artery. In single-study comparisons of populations with coronary or splenic artery calcification versus control, we observed an obvious increased risk of kidney stone in patients with vascular calcification. In pooled analysis of patients with abdominal aortic calcification, nonsignificantly increased risk of kidney stone disease was generated. Coronary artery calcification is a well-defined causal factor for cardiovascular events . AbdominAfter we stratified studies according to regions, we found the higher risk of kidney stone disease was significant in Asian participants, but not significant in Americans. Nevertheless, the population enrolled in Asian studies reached 67,046, which is far larger than that in American studies with mere 2243 participants in total. Moreover, the composition of participants in American studies is more comlex, including Hispanics, non-Hispanic blacks and whites . We beliCalcium phosphate deposition, mainly in the form of hydroxyapatite, is the hallmark of vascular calcification, which also constitutes the second largest composition of kidney stones ,44. OxalOur work has several limitations. The quantity of enrolled studies is small. Observational studies have inherent limitations, and we could not address direct interaction and draw causal conclusion. The majority of enrolled studies are case-control studies, which have adjusted for a wide variety of potential confounders like age, gender, smoking history and comorbidities. However, the residual confounding factors which contributed to both kidney stone and vascular calcification can still be substantial and cannot be excluded. Despite the majority of studies utilized X-ray photography or CT in diagnosing, Kim et al. and Li et al. also adopted ultrasound, which was not as effective ,33. In aPatients with vascular calcification may be associated with an increased risk of kidney stone disease. The assumed predictive value of vascular calcification on kidney stone disease informed physicians, specifically nephrologists, of the potential impact on kidney injury with future risk for chronic kidney disease, subsequent cardiovascular morbidities and mortalities.Click here for additional data file.Click here for additional data file.