Previous studies have drawn causal associations between fluoroquinolone use and collagen pathologies including tendon rupture and retinopathy. This meta-analysis2 = 72%) with current use of fluoroquinolones compared to their nonuser counterparts. Based on the “number needed-to-harm” analysis, 7246  patients would need to be treated with fluoroquinolones for a duration of at least three days in order for one additional patient to be harmed, assuming a population baseline incidence of aortic dissection and aneurysm rupture to be 10 per 100,000 patient-years. With strong statistical association, these findings suggest a causal relationship, warranting future research to elucidate the pathophysiological and mechanistic plausibility of this association. These findings however, should not cease prescription of fluoroquinolones, especially when clinically indicated.attempted to assess the association between fluoroquinolone use and the risk of aortic dissection or aortic aneurysm. A systematic search was performed on Medline, EMBASE, and the Cochrane library. 9 studies were included in final analysis. Primary random-effects meta-analysis of 7 studies, excluding 2 pharmacovigilance studies demonstrated statistically increased odds of aortic dissection  aortic aneurysm , and aortic aneurysm or dissection (OR, 1.47; 95% CI, 1.13–1.89; I Epidemiological studies have shown an increased risk of tendon disorders associated with fluoroquinolone use, such as tendinopathy and Achilles tendon rupture6. In vitro studies have demonstrated the mechanistic associations attesting the properties of these antibiotic involved in potentiating the activity of matrix metalloproteinases, resulting in degradation of collagen and structural components of the extracellular matrix. This is accompanied by features of oxidative stress in tendon cells, and reduction of collagen production 10.Fluoroquinolones rank amongst the topmost frequently used antibiotics11, raising the concern that fluoroquinolones may increase the risk of the formation of aortic aneurysms and dissections particularly given that these aortic pathologies are associated with changes in collagen structure and content12.Collagen constitutes a major extracellular matrix component of the aortic wall, particularly of variants type I and III18. Given the widespread use of fluoroquinolones, any plausible drug-related risk of aortic aneurysms and dissections should be investigated thoroughly. The main objective of this present study was to appraise real-world evidence of the association between fluoroquinolone and the occurrence of aortic dissections or aneurysms.The incidence of aortic dissections and aneurysms are also increasing, potentially conferring profound life-threatening consequences to patients if left untreated27. The risk of bias assessments can be found in Tables The systematic search revealed 159 unique titles, 2 additional articles were manually sourced from reference lists which also met the inclusion criteria. 18 were included after title and abstract screening, and reviewed in their entirety. Nine were excluded due to various reasons as shown in Fig. Characteristics of all 9 studies are shown in Table Fluoroquinolone exposure was defined differently in most studies according to various prescription databases but range from 60 to 180 days. For instance, Daneman’s cohort study defined exposure risk as up to 30 days after fluoroquinolone use. Lee’s case control study categorised exposures into current fluoroquinolone exposure within 60 days of index date, recent exposure within 60–365 days before index date, and any exposure for 3 or more days in the 1-year period before index date. Pasternak’s cohort study defined exposure to fluoroquinolones as a 60-day period from start of treatment, with secondary analysis investigating subsequent 60 days (days 61 to 120). Further subdivision of the 60-day risk period into 10 day intervals was conducted to assess number of events per interval. Both pharmacovigilance studies by Meng and Sommet did not provide a timeframe for the at risk window.3 studies utilised administrative diagnostic codes to identify aortic aneurysms and dissections. The primary outcomes were collagen-associated severe toxicities in Daneman’s study, and first occurrence of aortic aneurysm or dissection in inpatients in both Lee’s and Pasternak’s study.P < 0.00001; I2 = 48%). Meta-analysis of another 4 studies reflected that current use of fluoroquinolones was associated with a statistically significant increased odds of aortic aneurysm . Finally, meta-analysis of 5 studies showed a significantly increased odds of aortic dissection or aneurysm  with current use of fluoroquinolones compared to their nonuser counterparts . Meta-analysis of another 5 studies reflected that current use of fluoroquinolones was associated with statistically significant increased odds of aortic aneurysm . Finally, meta-analysis of 7 studies showed a significantly increased odds of aortic dissection or aneurysm  with current use of fluoroquinolones compared to their nonuser counterparts  and any prior users , as well as covariate adjusted estimates for past exposure  and any prior users  were found to be statistically significant.The number needed to treat to harm for the various aortic pathologies is summarized in Table The risk of bias was assessed using the Newcastle–Ottawa scale. Overall, the risk of selection and exposure bias were low. However, the overall comparability was deemed to be inadequate because the studies failed to control for all important risk factors of aortic aneurysm and dissection, particularly smoking. The assessment of publication bias was not meaningful due to the small number of studies, and hence was not performed. Results of the assessments can be found in Tables There is moderate evidence from this meta-analysis demonstrating the heightened risk of aortic aneurysm or aortic dissection in patients treated with fluoroquinolones. We believe, to our knowledge, this to be the first meta-analysis including the highest number of studies analyzing this relationship. Furthermore, we have performed additional analysis to comprehensively generate the numbers needed to harm based on a wide spectrum of assumed population baseline incidences of aortic aneurysms and dissections.28. Chief of all molecular players is matrix metalloproteinases (MMPs), where its dysregulation propagates extracellular matrix degeneration31. Cellular studies of smooth muscle cells derived from aortic aneurysms demonstrate an increased expression of MMP-9 and MMP-232, both of which potentiate collagenolytic activity34. These corroborated with animal studies showing an increased expression of MMP-9 and MMP-2 in cornea tissue35 and MMP-2 in tendon tissue36 upon administration of ciprofloxacin. Hence, the destruction of collagen and connective tissue by fluoroquinolones in the aortic wall might portend the development of aortic aneurysm and dissection.These findings may be supported by biological plausibility, where fluoroquinolones have been shown to induce epigenetic changes, and augment collagen maturation21; one study defined it as 30 days after start of treatment19. In particular, Pasternak and colleagues21 propounded this association to be the most significant in the first 10 days post-treatment, suggesting that this phenomenon might occur acutely during the active treatment phase. Albeit preliminary, this finding is consistent with in vitro studies demonstrating prompt expression of MMPs in tendon cells after ciprofloxacin administration36. The seemingly acute nature of the risk period is observed in other pathologies. For instance, fluoroquinolone-induced tendon rupture occurred between 2 and 31 days with a median of 7 days37. Similarly, the highest risk of fluoroquinolone-associated retinal detachment was within 5 days of treatment38.An important temporal aspect of our findings is the timing of this association, where the risk of aortic dissection and aortic aneurysm was increased with current use of fluoroquinolones. Two studies defined this as 60 days after start of treatment20. One limitation of the available data is that there is little known about the impact of past exposure or whether there is a cumulative dose effect, and hence we were unable to weight the doses of historical doses versus current doses differently. Next, confounding factors are inevitable in any observational study. Although the original studies provided adjusted estimates for a spectrum of possible confounders employing propensity score method, this does not eliminate residual confounders including smoking status and other cardiovascular risk factors. Moreover, two20 out of three studies only adjusted for a limited number of covariates, hence potentially missing out several other potential confounding factors. In addition, there could be a possibility of protopathic bias, where clinical symptoms of aortic aneurysm and dissection are misinterpreted as infection, necessitating antibiotics treatment. However, this appears unlikely given the low risk of such misdiagnosis in real-life settings39. In addition, there could be a risk of detection bias, as elegantly pointed out by Lee and colleagues20. Given the propensity of imaging examinations such as computed tomographic scans ordered during acute infections, this increases the probability of newly diagnosed aortic pathologies. One other methodological flaw consistent in the original studies was the lack of an active comparator. Whilst Pasternak and colleagues21 used amoxicillin as an active comparator to limit confounding factors associated with indication (infection), two other studies compared fluoroquinolone use with no use of antibiotics20.However, our findings must be interpreted in the context of known limitations. First, there were no randomized controlled trials in this study. However, it is not entirely true that observational studies have no role in exemplifying a causal association between an exposure and outcome. Moreover, it is unlikely there will ever be a randomized human trial investigating the association between fluoroquinolone exposure and aortic pathology from practical and ethical standpoints. Only one study compared risks of aortic aneurysm and dissection between individuals with past exposure/any prior users of fluoroquinolones, and nonusers21. A limitation of our meta-analysis is that cardiovascular risk factors were not controlled for uniformly in the studies included in the analysis. In this light, we propound that this relationship cannot be proven causal given the aforementioned. Nonetheless, clinicians should continue to prescribe fluoroquinolones if clinically indicated, and we are not advocating cessation of their used based on a theoretical risk of aortic dissection or aortic aneurysm development. Further evidence is warranted to accurately elucidate the pathophysiology of how this may occur mechanistically. With strong statistical association, our findings suggest a causal relationship between the use of fluoroquinolone and increased risk of aortic aneurysm and dissection. Further research is needed to corroborate with these current findings. However, given the numbers needed to harm, this should not change the contemporary evidence-based practice on the use of fluoroquinolone. This information should be used for purposes of patient counselling. If the patient is met with a condition that has alternative suitable antibiotic of same efficacy these options should be discussed.Although several factors lend support to the strength of the association, including biological plausibility; consistent epidemiological evidence; and analogous findings from other pathologies, further research is warranted in other populations to establish a firm conclusion. Furthermore, it is unclear whether the association is driven by aortic aneurysm or aortic dissection, although Pasternak and colleagues argued it could be the former40. The study protocol was registered on the PROSPERO International Prospective Register of Systematic Reviews (registration number CRD42020212150).This review was performed in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelinesAny randomized or non-randomized study  that investigated the association between fluoroquinolone use regardless of indication, and risk of aortic dissection and/or aortic aneurysm were included. The controls were limited to unexposed patients or patients receiving other types of antibiotics. The following designs were excluded: case reports/series; non-English; animal studies. Studies that did not report extractable data including odds ratio; relative risk; hazard ratio; or raw data, were excluded. Conference abstracts were considered only if sufficient data was available for meaningful synthesis and analysis.The primary outcomes of interest were development of aortic dissection or aortic aneurysm amongst patients who: 1) have taken fluoroquinolones in the last 1 year; 2) are currently taking fluoroquinolones for active treatment, limited up to 60 days within index date.A systematic search was performed in the following databases: Medline; EMBASE; and the Cochrane library from inception on 30th September 2020. An exhaustive combination of the following ‘MeSH’ and ‘non-MesH’ terms were used: aortic dissection; aortic aneurysm; fluoroquinolones; quinolones. The full search strategy is available upon request from IW.Three reviewers  independently screened and assessed the studies for potential inclusion in two stages: (1) title and abstract screen; (2) full-text review of those titles included in the first stage. Data extraction was also performed independently by three reviewers  using a standardized proforma. The following data were abstracted: study design, demographics, country and dataset, type of fluoroquinolones, indication for fluoroquinolones, selection criteria, controls, unadjusted hazard ratios (HR) or odds ratio (OR), propensity-score adjusted HR, propensity-score matched HR, and covariate-adjusted HR. Conflicts were resolved by consensus, or by appeal to a fourth senior author (AC).For studies with outcomes of interest reported but not specific to fluoroquinolone exposure, the corresponding authors were contacted for acquisition of raw data. A response was anticipated for two weeks before a decision was made on the eligibility of the study.41.The reference lists of included studies were also scrutinized to pursue references of identified citations, in an effort to identify high quality resources in obscure locations that could have been overlooked in our search strategy42. In brief, the assessment of case–control studies includes 8 domains: (1) adequate case definition; (2) representativeness of cases; (3) control selection; (4) definition of controls; (5) comparability of cases and controls on the basis of design or analysis; (6) ascertainment of exposure; (7) non-responses rate; (8) similar method of ascertainment for cases and control. The assessment of cohort studies also includes 8 domains: (1) selection of non-exposed cohort; (2) representativeness of cases; (3) ascertainment of exposure; (4) demonstration that outcome of interest was absent at start of study; (5) comparability of cohort on the basis of design or analysis; (6) assessment of outcome; (7) length of follow-up; 8) adequacy of follow-up of cohorts. Based on the aforementioned, the studies will be scored against a maximum of 9 points.The Newcastle–Ottawa Scale for Quality Assessment for cohort and case–control studies was employed to assess the risk of bias of included studies2 statistic value of less than 50%), in order to also account for qualitative heterogeneity which may not have been evident from the I2 value alone. Conditional odds ratios (ORs) (which was the effect measure in these studies)24 were taken to be interchangeable with the hazard ratios since the likelihood functions of the conditional logistic model is mathematically identical to the stratified Cox model when estimated under partial likelihood. The incidence rate ratios and hazard ratios were likewise taken to approximate one another owing to the functional similarities between the Poisson and Weibull regressions, while the relative risk was assumed to approximate the hazard ratio since right-censoring due to loss to follow-up was likely to be minimal because the exposure-time and follow-up duration were short. As such, the main effect measure in our analyses was the incidence rate ratio.Meta-analyses were done assuming the random effects model to account for both within-study and between-study heterogeneity. The random-effects meta-analysis was employed even when quantitative heterogeneity was low  by taking the ratio of the pooled ROR of the three fluoroquinolones divided by the ROR of cefuroxime (the negative control). Notably, this approach is similar to that of the study by Maumus-Robert et al.23 which reported an “amoxicillin-adjusted” odds ratios, where Maumus-Robert et al. calculated as the ratio of ORs for fluoroquinolones divided by OR for amoxicillin). The 95% confidence intervals for the adjusted reporting ORs were calculated assuming a lognormal distribution for the adjusted OR, as follows:For the study by Meng et al.The pooled standard error can be calculated as:The 95% confidence intervals of the AOR can then be calculated as: exp[ln(AOR) + /- 1.96 * SEpooled].23. The Maumus-Robert study also reported an amoxicillin-adjusted OR of 2.44 (95% CI: 1.31 to 4.57)23. Using our formula above, we are able to reverse-engineer the adjusted OR, obtaining an amoxicillin-adjusted OR of 2.45 (95% CI: 1.31 to 4.58). Notably, our estimate of the adjusted OR is nearly identical to that of the exact OR provided by Maumus-Robert et al.23 Hence, these formulae were likewise applied to the Meng 2019 study to estimate the cefuroxime-adjusted OR.For example, the Maumus-Robert study reported an OR of fluoroquinolones of 3.23 (95% CI: 1.85 to 5.64) and an OR of amoxicillin of 1.32 (95% CI: 0.99 to 1.76)The number needed to treat to harm, and its 95% CI was also assessed to estimate an absolute measure of effect. The number needed to treat to harm is the number of patients who need to be treated with fluoroquinolones for 1 additional patient to have an adverse event. The baseline risk was obtained from the unexposed group in the population-based studies.Ethical approval was not required for this systematic review and meta-analysis.Supplementary Information.


Background: The adult population in lead-related occupations or environmentally exposed to lead may be at risk for renal impairment and lead nephropathy. This meta-analysis aims to determine the impact of blood lead level (BLL) on renal function among middle-aged participants. Methods: Cross-sectional, longitudinal, or cohort studies that reported BLL and renal function tests among adult participants were retrieved from PubMed, Scopus, and ISI Web of Science. Relevant studies were included and assessed for quality using the Newcastle–Ottawa Scale (NOS). The pooled mean BLL of participants with a high BLL (≥30 µg/dL), moderate BLL (20–30 µg/dL), and low BLL (<20 µg/dL) was estimated using the random effects model. The pooled mean differences in BLL, blood urea nitrogen (BUN), creatinine, uric acid, and creatinine clearance between the exposed and non-exposed participants were estimated using the random effects model. Meta-regression was performed to demonstrate the association between the effect size (ES) of the pooled mean BLL and renal function. Heterogeneity among the included studies was assessed using the Cochrane Q and I2 statistics. Cochrane Q with a p value less than 0.05 and I2 more than 50% demonstrated substantial heterogeneity among the studies included. Publication bias was assessed using the funnel plot between the effect size and standard error of the effect size. Results: Out of 1657 articles, 43 were included in the meta-analysis. The meta-analysis demonstrated that the pooled mean BLL in the participants with a high BLL, moderate BLL, and low BLL was 42.41 µg/dL : 42.14–42.67, I2: 99.1%), 22.18 µg/dL , and 2.9 µg/dL , respectively. The mean BLL of the exposed participants was higher than that of the non-exposed participants (weighted mean difference (WMD): 25.5, p < 0.0001, 95% CI: 18.59–32.45, I2: 99.8%, 17 studies). The mean BUN  and mean creatinine  in the exposed participants were higher than those in the non-exposed participants. The mean creatinine clearance in the exposed participants was lower than that in the non-exposed participants (standard mean difference (SMD): −0.544, p = 0.03, 95% CI: −1.035–(−0.054), I2: 96.2%). The meta-regression demonstrated a significant positive effect of BLL on BUN . Conclusions: BLL was observed to be associated with abnormal renal function test parameters, including high BUN, high creatinine, and low creatinine clearance. Moreover, BUN seemed to be the most valuable prognostic marker for lead-induced renal impairment. Therefore, regular checks for renal function among lead-exposed workers should be a priority and publicly promoted. Lead is a heavy metal and toxicant to the human body . The mosBlood lead level (BLL) is widely used as a biomarker for lead exposure because it reflects the current exposure to lead . AlthougEvidence from epidemiological studies has demonstrated an association between BLL and lead nephropathy, where even BLL below 10 µg/dL can cause harmful effects on renal function ,10. A prA previous meta-analysis of BLL in Iranian lead workers demonstrated that the highest mean BLL was 72.58 µg/dL [95% CI: 26.06–119.10] among lead-zinc mine workers . MoreoveThe systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . The proThe search terms in combination with the Boolean operator (“blood lead” OR “lead exposure” OR “lead toxicity” OR “lead poisoning”) AND  and (adult OR “middle-aged” OR worker) were used to retrieve potentially relevant studies in three databases: Medline, Scopus, and ISI Web of Science. The keywords “lead”, “renal”, and “middle-aged” were checked with the Medical Subject Heading (MeSH term) to identify the relevant search terms. The searches were performed on 15 January 2020. The search terms are provided in The inclusion criteria for this study included any cross-sectional, longitudinal, or cohort studies that reported on BLL and renal function among adult participants. The exclusion criteria excluded any studies with the following characteristics: animal models, case control studies on chronic kidney diseases or end-stage renal disease or patients with diabetes mellitus at enrollment, non-English language studies, studies with a small sample size (fewer than 10 participants) including case reports/case series/comments/errata/correspondences/short reports, in vitro studies, studies where the data on BLL or renal function tests could not be extracted, studies using the same data or participants for a different research question, and studies that measured co-exposure of lead and other metals.Any studies that met the eligibility criteria were selected by two independent authors . Any disagreement between the two authors in selecting the studies was resolved by discussion for consensus. Data extraction was also performed by two independent authors . The following data were extracted from the included studies: name of the first author, publication year, study site, year that the study was conducted, and participant data, including mean age, gender, BLL, BUN, creatinine, uric acid, creatinine clearance or estimated glomerular filtration rate (eGFR), and the status of renal impairment (if applicable). The data were extracted into a standardized pilot datasheet for further analysis.The quality of the included studies was assessed using the Newcastle–Ottawa Scale (NOS) to assess the quality of non-randomized studies in meta-analyses . The NOSThe primary outcome of this study was to explore the association between BLL and renal function. The secondary outcome was the pooled mean difference in BLL between the exposed and non-exposed participants. The third outcome was the pooled mean difference in BUN, creatinine, uric acid, and creatinine clearance between the exposed and non-exposed participants. The fourth outcome was the pooled mean BLL among participants with a high BLL (≥30 µg/dL), moderate BLL (20–30 µg/dL), and low BLL (<20 µg/dL). Cutoff values of <20 µg/dL, 20–30 µg/dL, and >30 µg/dL were used to indicate lead exposure among participants, as previously described by Lim et al. .2 statistics. Cochrane Q with a p value less than 0.05 and I2 more than 50% demonstrated substantial heterogeneity among the included studies [The mean BLL reported in the included studies was used to analyze the pooled mean BLL among the exposed participants. However, as the non-exposed participants were a low-risk group and showed a low BLL, the mean BLL of non-exposed or controls was not estimated in this study. The median with rank or interquartile rank of BLL and renal parameters reported in the included studies was transformed into the mean and standard deviation (SD), as reported elsewhere . The uni studies . Of the Overall, 1657 articles were retrieved from the searches of three databases. After removing 676 duplicate articles, 981 articles were screened for potentially relevant articles through title and abstract screening. As a result, 754 articles were excluded due to their having no relevance to the present study. The full texts of the 227 articles that remained were examined according to the eligibility criteria, and 184 articles were excluded . FinallyThe 43 included studies were published between 1987 and 2020 and were conducted in 18 countries in 4 regions. Most of the studies were conducted in Asia , America , Europe , and Africa . In Asia, the studies were conducted in the Republic of Korea , India , China , and Taiwan , and the remaining 5 studies (25%) were from Thailand, Turkey, Iran, Japan, and Singapore. In America, the studies were conducted in the United States of America , and 2 studies (18.2%) were conducted in Brazil and Mexico. In Europe, the studies were conducted in Belgium  and Sweden , and 2 studies (25%) were conducted in the Netherlands and United Kingdom. In Africa, the studies were conducted in Nigeria  and South Africa . Most of the included studies were cross-sectional studies , and the rest  were cohort, longitudinal, or retrospective studies. Most of the studies determined BLL in exposed and non-exposed participants , population-based surveys , and BLL in only in exposed participants . The characteristics of the included studies are shown in The quality of the included studies is shown in 2: 99.1%), whereas the pooled mean BLL in the participants with moderate and low mean BLL was 22.18 µg/dL  and 2.9 µg/dL , respectively. The characteristics of the exposed participants divided into three groups are shown in The pooled mean BLL was estimated from all 43 studies ,58,59,60p < 0.0001, 95% CI: 18.59–32.45, I2: 99.8%). Subgroup analysis demonstrated that the difference in BLL between exposed and non-exposed participants was larger for those with high mean BLL , whereas the difference between exposed and non-exposed participants was smallest for those with a low mean BLL .The pooled mean difference in BLL between the exposed and non-exposed participants was estimated using the mean BLL from 17 studies ,51,56,59p < 0.0001, 95% CI: 1.11–3.80, I2: 95.8%)  . Three sp < 0.0001, 95% CI: 0.76–2.55, I2: 76%)   , I2: 96.2%)  . The poo: 76.8%) . The poo: 91.6%) . The poo: 96.2%) .p = 0.022, coefficient: 0.75, constant: −3.7) (p = 0.989)   of renal function test parameters (dependent variable) and mean BLL (independent variable). The meta-regression of BUN (weighted mean difference) and mean BLL was performed using the data from 10 studies ,47,49,59t: −3.7) . The met= 0.989) . The met: 0.034) . No sign: 0.034) .p < 0.728), indicating no publication bias across the included studies.The funnel plot between the effect size (weighted mean difference) and standard error of the effect size demonstrated the likelihood of asymmetry . TherefoThe present meta-analysis demonstrated that the mean BLL among participants with high BLL was 42.41 µg/dL, moderate BLL was 22.18 µg/dL, and low BLL was 2.90 µg/dL. The mean BLL was significantly higher in lead-exposed participants than in non-exposed participants for all 18 included studies. This finding was similar to a meta-analysis performed in Iran, which demonstrated high mean BLL in Iranian lead-exposed workers . MoreoveThe pooled mean difference in BLL between the exposed males and females showed that the mean BLL in the exposed males was higher than that in the female participants. A significant difference in gender was clearly observed in a study by Staessen et al.  and WangThe present meta-analysis demonstrated the difference in the mean BUN, serum creatinine, and mean creatinine clearance in lead-exposed participants compared to non-exposed participants. In addition, the present meta-analysis showed that the mean BUN was significantly higher in lead-exposed participants than in non-exposed participants, especially in participants with high and moderate mean BLL. These results demonstrated that an increase in BLL could induce renal impairment among exposed participants. The difference in BUN was clearly observed in five included studies ,39,49,59The present meta-analysis showed that the mean creatinine was significantly higher in lead-exposed participants than in non-exposed participants, especially in participants with a high mean BLL. The higher mean creatinine among the exposed participants with a high mean BLL was clearly demonstrated in four studies ,15,16,59Creatinine clearance has been widely used to determine GFR. It is commonly used in routine laboratory work for evaluating renal function. This study demonstrated that the mean creatinine clearance was significantly lower in lead-exposed workers than in non-exposed participants. This finding was observed in the studies by Alasia et al. , GennartUric acid is the product of purine metabolism; moreover, it is derived from the degradation of a cell or nucleic acid within a cell, and elimination of uric acid occurs in the proximal tubule and distal tubule . A previIn addition to renal impairment induced by lead, lead exposure also increased the severity of underlying diseases, especially in susceptible populations with hypertension, diabetes mellitus, and chronic kidney disease . MoreoveThe present study had limitations. First, there were a limited number of included studies based on the eligibility criteria, which limited the study to adult or middle-aged participants. Second, the relationship between BLL and work duration was not assessed due to data unavailability among the included studies. Third, there are several factors that affect the progression of lead nephropathy in addition to lead, including individual susceptibility, race, and the pattern of lead exposure . These mBLL was associated with abnormal renal function test parameters, including high BUN, high creatinine, and low creatinine clearance. Moreover, BUN seemed to be the most valuable prognostic marker for lead-induced renal impairment. Therefore, regular checks for renal function among lead-exposed workers should be important and publicly advocated for.


The variability of blood pressure (BPV) has been suggested as a clinical indicator for cognitive dysfunction, yet the results from clinical studies are variable. This study investigated the relationship between BPV and the risk of cognitive decline or dementia. Bibliographic databases, including PubMed, Scopus, and Embase, were searched systematically for longitudinal cohort studies with BPV measurements and neuropsychological examinations or dementia diagnosis. A traditional meta‐analysis with subgroup analysis, and a further dose‐response meta‐analysis were conducted. Twenty cohort studies with 7 924 168 persons were included in this review. The results showed that a higher systolic BPV (SBPV), when measured with the coefficient of variation (SBP‐CV) or standard deviation (SBP‐SD), was associated with a higher risk of all‐cause dementia diagnosis but not incidence of cognitive decline on neuropsychological examinations. In subgroup analysis, the effect was more prominent when using BPV of shorter timeframes, during shorter follow‐ups, or among the elderly aged more than 65 years. No dose‐response relationship could be found. Our study suggested possible positive associations between SBPV and the risk of dementia. Further studies are required to validate these findings. The participants had both BPV measurements and global cognitive decline or dementia monitoring in a longitudinal manner.2.2.3Any measure of SBPV or DBPV obtained from ambulatory, home, or visit‐to‐visit BP monitoring was eligible. The BPV indices included the following three categories: overall variability, variability between consecutive visits, and the extremes in values on a single visit. Overall variability was assessed using standard deviation (SD), coefficient of variation (CV), and variance independent of the mean (VIM). Variability between consecutive visits was assessed with average real variability (ARV), and the extremes in values on a single visit was assessed with full range (difference between the maximum and the minimum).2.2.4The primary outcome was the incidence of all common types of dementia, including Alzheimer's disease and vascular dementia, verified by licensed physicians or related professionals or medical records. The secondary outcome was the incidence of cognitive decline across any period, obtained by standardized neuropsychological tests, including Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Cambridge Cognition Examination (CAMCOG), etc., at least twice.2.3Three bibliographic databases, PubMed, Scopus, and Embase, were searched on May 11, 2021, without limitations on the publication date. Bibliographies of the included studies and relevant publications were also manually searched for eligible studies. The search string used was as followed, (“blood pressure variability” OR “beat‐to‐beat” OR “24‐hour blood pressure monitoring” OR “visit‐to‐visit” OR “ambulatory blood pressure monitoring” OR “home blood pressure monitoring”) AND .2.4After removing duplicate studies, two reviewers (T.J.C. and J.T.Y.) independently screened the titles and abstracts. The full text was retrieved for further assessment. The reviewers then independently assessed the full articles according to the inclusion/exclusion criteria. Disagreements were resolved by consensus and by consulting with a third reviewer (HMC).2.5The two reviewers independently extracted study characteristics and outcome data from the included studies. We only extracted the numbers derived from the fully‐adjusted model in each study. The variables adjusted were listed in Table 2.6Risk of bias was independently assessed by the two reviewers according to the Quality in Prognostic Factor Studies (QUIPS).2.7dosresmeta R package with a linear model.meta R package. Subgroup analysis and sensitivity analysis were performed when the meta‐analysis contained more than two studies. The traditional meta‐analysis and the leave‐one‐out meta‐analysis were conducted using the inverse variance method and the random effects model.Studies with sufficient quantitative results were further analyzed by two‐step meta‐analysis. First, a traditional meta‐analysis was employed to integrate the most‐adjusted hazard ratio (HR) or odds ratio (OR) in each outcome from the highest versus lowest BPV groups of different BPV indices across different studies, using RevMan 5.4 . For groups showing significant associations, a further dose‐response meta‐analysis was conducted using the 2 statistics, where an I2 > 60%, was considered highly heterogenous.metafor R package, for outcomes integrated from more than two studies.The heterogeneity among included studies was evaluated by the Cochrane Q‐test, with a significance level of 0.05, and I33.1We obtained 2485 records in total on our database search. Using the PRISMA flowchart Figure , 20 studThe characteristics of included studies are shown in Table 3.2The risk of bias was assessed with the QUIPS tool Figure  and 2B. 3.32 = 78%; SBP‐SD: HR = 1.31  I2 = 70%), whereas SBP‐VIM and DBP‐CV demonstrated no significant association. Alzheimer's disease and vascular dementia had no significant associations with any analyzed BPV index. All primary results for HRs of dementia risk had high heterogeneities (I2 = 66%‐90%), except for the analysis on SBP‐VIM versus vascular dementia risk (I2 = 16%). Subgroup analysis according to different BPV timeframes . All subgroup analysis and sensitivity analysis were not conducted due to the limited study number.Results on the incidence of cognitive decline are shown in the lower part of Table 3.5p = .1246; SBP‐SD: p = .088).Further dose response analysis was conducted between the risk of all‐cause dementia and SBP‐CV or SBP‐SD. As shown in Figure 3.6The funnel plots and subsequent Egger tests were only conducted for those groups with > 2 studies Figure . The res4This study included 20 cohort studies with a total of 7 924 168 participants; we conducted a traditional meta‐analysis from eight and further dose‐response analysis from three included studies. As shown in the Table We identified that higher SBPV, particularly SBP‐CV and SBP‐SD, was potentially associated with a higher risk of dementia with HRs around 1.3–1.4. In the subgroup analysis according to different BPV timeframes, different outcome follow‐up durations, and the mean age of participants in included studies, a consistent trend was found for the associations between BPV and dementia risk, which is more prominent in groups with shorter BPV timeframes, shorter follow‐up durations, and an older age. Sensitivity analysis remained robust for meta‐analysis with sufficient included studies of more than three. The dose‐response meta‐analysis demonstrated no significant dose‐response between SBPV and all‐cause dementia risk. The heterogeneity is high in most of our analyses.4.1Higher SBPV was significantly associated with higher all‐cause dementia risk but was not specifically associated with the dementia subtypes included in our study, Alzheimer's disease and vascular dementia. In addition, the association between SBPV and dementia risk was more prominent in subgroups with shorter follow‐up duration for cognitive performances and with older ages. The possible mechanism accounting for this finding remains to be elucidated. For the other outcome of interest, the incidence of cognitive decline, was not analyzed for almost all BPVs due to limited data report.For DBPV, in some of the included studies, the effect estimates of DBPV were not provided because of the statistically insignificant results on cognitive dysfunction Table ; therefoOur systematic review represents the summarized totality of evidence by including the most comprehensive and updated studies, as compared with a previous review.4.2Since the SD of BP was related to mean BP, CV and VIM were further utilized for BPV indices to adjust for mean BP.No association was observed between all DBPV indices and dementia risk of all types or incidence of cognitive decline. The statistically insignificant finding between overall DBPV and dementia risk of all types or incidence of cognitive decline might imply that DBPV plays a less important role in cognitive dysfunction.4.3In both SBP and DBP, the variability derived from a shorter timeframe was associated with stronger associations with all‐cause dementia risk in this study. This might shed some light onto the different clinical correlation of BPV estimated with different timeframes.4.4Most of the data in the included studies showed statistically significant trends between BPV and cognitive dysfunction; however, in our meta‐analysis, the high heterogeneity across those studies gave rise to statistically insignificant pooled effect estimates in most of our analyses Table . This he4.5BPV could be considered as a comprehensive reflection of the interaction between cardiovascular physiological responses  and environmental settings , although the exact details are not yet completely understood. Certain vascular diseases  were found to be associated with SBPV,4.6The strengths of our study are, first, this is the largest meta‐analysis of cohort studies providing insights into the prognostic value of BPV in cognition. Second, a wide range of different BPV indices was studied from the perspective of different BPV statistical indices comprising overall variability, variability between consecutive visits, and extreme values on a single visit, and a broad‐spectrum of BPV timeframes ranging from short‐term, mid‐term, to long‐term ones. Third, dementia risk and incidence of cognitive decline, the outcomes of interest in our study, were of clinical importance, since they posed a significant threat to care burden.However, there were some limitations in this study for the interpretation of results. First, because of the different characteristics of the study populations included in this meta‐analysis, the comorbidity composition difference between the included studies may be a significant source of heterogeneity Table . The quaNone.Tzu‐Jung Chiu: Conception and design of the study, acquisition and analysis of the data, drafting and revising the manuscript. Jiunn‐Tyng Yeh: Conception and design of the study, acquisition and analysis of the data, drafting and revising the manuscript. Chi‐Jung Huang: Conception and design of the study, analysis and interpretation of the data, drafting and revising the manuscript. Chern‐En Chiang: Conception of the study, analysis and interpretation of the data, revising the manuscript. Shih‐Hsien Sung: Conception of the study, analysis and interpretation of the data, revising the manuscript. Chen‐Huan Chen: Conception of the study, analysis and interpretation of the data, revising the manuscript. Hao‐Min Cheng: Conception and design of the study, acquisition, analysis and interpretation of the data, drafting and revising the manuscript. All the author approved the final version of the manuscript and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.Supporting informationClick here for additional data file.


Debate on the potential carcinogenic effects of meat intake is open and the relationship between meat consumption and risk of prostate cancer remains uncertain. This meta-analysis was conducted to summarize earlier prospective studies on the association of meat consumption with risk of prostate cancer.I-square (I2). A funnel plot and Egger's test was used to detect publication bias. Linear and non-linear dose-response analyses were performed to estimate the dose-response relations between meat intake and risk of prostate cancer.Relevant studies were identified by exploring PubMed/Medline, Scopus, Web of Science, EMBASE, and Google Scholar databases up to December 2020. Fixed-effects and random-effects meta-analyses were used for pooling the relative risks (RRs). Heterogeneity across studies was evaluated using the Q-statistic and I2 = 1.5%, P = 0.43) and “advanced prostate cancer” . However, the association between processed meat and “advanced prostate cancer” was not significant in the random-effects model: 1.12 . A linear dose-response analysis indicated that an increment of 50 grams per day of processed meat intake might be related to a 4% greater risk of “total prostate cancer” . “Total meat intake” was marginally associated with all outcomes of prostate cancer risk .Twenty-five prospective studies were included in this meta-analysis. Totally, 1,900,910 participants with 35,326 incident cases of prostate cancer were investigated. Pooling the eligible effect sizes, we observed that high consumption of processed meat might be associated with an increased risk of “total prostate cancer” (RR: 1.06; 95% CI: 1.01, 1.10; This systematic review and meta-analysis of prospective studies indicated that increased consumption of “total meat” and “processed meat” might be associated with a higher risk of prostate cancer.https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=230824, identifier: CRD42021230824. Prostate cancer is the second most frequent cancer and the fifth leading cause of cancer death among men worldwide , 2. It iOlder age, African-American descent, and family history are the established risk factors for prostate cancer. Diet is one of the most modifiable risk factors for prostate cancer . ConsumpThis systematic review and meta-analysis presented based on PRISMA guideline . The proStudies were included in this systematic review and meta-analysis if they met the following criteria: (1) publications done on men > 18 years old; (2) those that assessed consumption of red or processed meat as the exposure; (3) examined high vs. low meat consumption; (4) investigated risk of prostate cancer as the outcome; and (5) nested case-control, case-cohort, and prospective cohort studies.We excluded duplicate citations and those that did not meet our inclusion criteria. Studies that assessed consumption of meat, chicken, or fish intake together were excluded (some studies that considered white meat as part of the processed meat were not excluded). We also did not include studies that investigated the incident symptomatic benign prostatic hyperplasia as the outcome. In addition, case-control, cross-sectional, ecological design, reviews, editorials, commentaries, and letters were not included as well.The following information was extracted with a standardized data collection form by two reviewers (SNM and AA): the first author's last name, name of the study cohort, country, participants' age (mean or range), number of participants, number of cases, years of follow up , method of assessment of meat intake, the main exposure and outcome of interest, comparisons, the relevant effect size  and 95% confidence intervals (CIs), and covariates used for adjustment. Any disagreements in data extraction between the two reviewers were consulted with the leading investigator (AE).“Red meat” was defined as the consumption of red meat and unprocessed red meat. “Processed meat” was defined as the consumption of sausages, bacon, hamburger, ham, lunch meat, hot dogs, cured meat, cold meat, smoked beef, and processed poultry, poultry sausage. “Red and processed meat” was considered as the sum of red meat and processed meat. In addition, “total meat” was defined as the sum of red meat, processed meat, and meat (in publications where meat consumption had not been defined to be red or white meat). The studies had defined the outcome in different ways. In the current meta-analysis, studies with the outcome of prostate cancer, total prostate cancer, all prostate cancer, and prostate cancer diagnosis were included in the category of “total prostate cancer.” In addition, “advanced prostate cancer” in this study was defined as advanced prostate cancer, high-stage prostate cancer, lethal prostate cancer, fatal prostate cancer, non-localized or high-grade cancer, and metastatic prostate cancer.Based on our initial search, 1,940 studies were found. Based on screening for title and abstract, a total of 1,908 articles were excluded and 32 articles remained to be assessed for eligibility. After evaluation, 6 further studies were excluded due to the following reasons: three cohort studies with the same population in other publications including NIH-AAPR cohort , 17, andThe quality of each study was assessed using the Newcastle-Ottawa Scale (NOS). To ensure that the scoring of studies is unbiased, scoring was done by two independent investigators (SNM and AA). This scale includes three parameters for quality assessment: selection, comparability, and outcomes for cohort study. Each study can receive a maximum of four stars for selection, two stars for comparability, and three stars for the outcome. Therefore, in total, each study can achieve a maximum of 9 stars . We defiI-square (I2) were used to evaluate heterogeneity across the studies. Significant heterogeneity between studies was indicated if I2 > 50%. Subgroup analyses were used to find the possible sources of heterogeneity. Between-study heterogeneity was assessed using a fixed-effects model. These analyses were done based on predefined criteria, including country, study quality, and adjustment for energy intake, smoking, alcohol consumption, and family history of cancer. For one study , smoking (n = 14), energy intake (n = 13), body mass index (BMI) (n = 13), family history of cancer (n = 9), and education (n = 7). Out of 25 studies, 11 studies were of high quality (NOS ≥ 7) (n = 14) (Characteristics of included studies are provided in tion n = . Out of NOS ≥ 7) , 38, 44 (n = 14) , 39–43. (n = 14) , 40, 43,(n = 14)  or race Considering red meat consumption as the exposure, we found that four studies reported a positive association with risk of total prostate cancers , 29, 40.Twenty-five articles were included in this meta-analysis. We performed the analysis based on red meat, processed meat, red and processed meat, and total meat  consumption separately. In addition, in each group, the analyses were done separately for total prostate cancer and advanced prostate cancer. However, a pooled analysis for all outcomes of prostate cancer was also performed.I2 = 40.5%, P = 0.05). There was no evidence of publication bias (Egger's test P = 0.173). The results from the subgroup analyses revealed that adjustment for energy intake, alcohol consumption, and family history of cancer had influenced the association of “red meat intake” and risk of “total prostate cancer”  and no evidence of publication bias (Egger's test P = 0.857). Findings from subgroup analyses are provided in Totally, nine publications examined the association between consumption of “red meat” and risk of “advanced prostate cancer” , 33–36. I2 = 1.5%, P = 0.43) (P = 0.06). The influence of a publication bias on the findings was examined using the ‘trim and fill' analysis. After imputing four hypothetically missing effect sizes in this analysis, the results were still statistically significant in the fixed-effects model , but not in the random-effects model . Findings from subgroup analyses are provided in To investigate the association between “processed meat intake” and risk of “total prostate cancer,” 13 studies were included , 40, 44. = 0.43) . PublicaI2 = 58.8%, P = 0.01) (P = 0.569). Subgroup analyses were conducted to find the sources of between-study heterogeneity  . However = 0.01) . Egger'sogeneity . SubgrouI2 = 42.1%, P = 0.05). We found no evidence of publication bias among the included studies (Egger's test P = 0.551). Based on subgroup analyses, we found that country and adjustment for alcohol consumption might explain between-study heterogeneity . No evidence of publication bias was observed by Egger's test (P = 0.292). We performed subgroup analyses to assess sources of between-study heterogeneity. In the subgroup analyses, we found that country and adjustment for alcohol consumption might describe between-study heterogeneity   and risk of “total prostate cancer” , 43, 44. = 0.01) , but not = 0.01) . Results = 0.01) .I2 = 63.3%, P = 0.002) (P = 0.269). Based on subgroup analyses, we observed that adjustment for alcohol consumption and family history of cancer influenced the association between “total meat intake” and risk of “advanced prostate cancer.” When we did subgroup analysis based on studies that did or did not control for alcohol consumption, we found an increased risk of “advanced prostate cancer” with “total meat consumption” in studies that did adjustment for alcohol intake , while in other studies, there was no significant association . In addition, analysis based on studies that controlled for family history of cancer revealed no significant association in studies that did adjustment for this variable , while others reached a significant positive association between “total meat intake” and risk of “advanced prostate cancer”   ; however= 0.002) . The Egg7, 1.28) .I2 = 58.4%, P < 0.001) in the fixed-effects (P = 0.240).Twenty-two studies had investigated the association between “total meat intake” and “all outcomes of prostate cancer” , 39–44. -effects , and 1.0-effects , indicatSubgroup analyses were done to investigate possible sources of heterogeneity. We observed that adjustment for energy intake and alcohol consumption, and study quality score were the possible sources of heterogeneity .Findings from sensitivity analyses in each of the above-mentioned meta-analyses revealed that none of the single studies had a significant effect on the pooled effect size.I2 = 0.0%, P = 0.51)  . No othe = 0.51) , 9–15.In this systematic review and meta-analysis of prospective studies, we found that total meat intake was marginally associated with all outcomes of prostate cancer risk. This association was more evident about processed meat consumption. Although a significant weak relationship was observed between red meat consumption and risk of total prostate cancer in the fixed-effects model, there was no such significant association between red meat consumption and risk of advanced prostate cancer.There were an estimated 1.3 million new cases of prostate cancer and 3,59,000 deaths worldwide in 2018 –14. In lAlthough we did not observe a significant association between red meat intake and risk of advanced prostate cancer, a significant weak relationship between red meat consumption and risk of total prostate cancer was seen in the fixed-effects analysis. Previous studies reported no significant association between red meat intake and risk of total and advanced prostate cancer –14. DiscWhen we combined red and processed meat intake, no significant association was found with total and advanced prostate cancer. This might be attributed to the inclusion of studies that examined both red meat and processed meat intakes, and lack of inclusion of studies that examined only red meat or processed meat consumption.The present meta-analysis has several strengths overs previous meta-analyses. This study pooled effect sizes from 22 papers to investigate the link between total meat intake and risk of all outcomes of prostate cancer for the first time. In addition, we included five new big cohort studies in this meta-analysis. Furthermore, additional studies were included in the linear and non-linear dose-response analyses in the current study. Moreover, both random-effects and fixed-effects models were done in this study to investigate more accurate association between meat intake and prostate cancer. Also, further subgroup analyses, as compared with earlier studies, was performed in this analysis. Finally, in additional to linear dose-response analysis, we did non-linear dose-response analysis in this study as well, while previous studies have only performed linear dose-response analysis.The relationship between meat consumption and risk of prostate cancer can be explained by several potential mechanisms. Heme iron in red and processed meat  and N-niThis study has several strengths. For the first time, we performed a non-linear dose-response association between meat intake and risk of prostate cancer. We included only prospective studies in this meta-analysis. Therefore, the probability of recall and selection bias is minimized, however, one should consider lost to follow-up in each individual study. In the current analysis a few studies have reported number of people lost to follow-up. This should be considered in the interpretation of our findings. In the sensitivity analysis, our findings were stable and robust. Most included studies had controlled for confounders such as age, energy intake, and smoking. We had some limitations in this meta-analysis as well. In most studies, FFQ has been used to assess food intake, therefore, measurement error and misclassification of study subjects was possible. We did not examine the association between cooking methods of meat and prostate cancer. In some studies, processed poultry was also included in total processed meat.In conclusion, we found that total meat intake might be poorly associated with all outcomes of prostate cancer. Consumption of processed meat might be associated with an increased risk of total and advanced prostate cancer. Also, we observed a weak relationship between red meat consumption and risk of total prostate cancer, but not with advanced prostate cancer. Given some significant, albeit weak, associations between meat consumption and risk of different types of prostate cancer, recommendations on the consumption of meat should be done cautiously. In addition, consumption of processed meat intake, due to its detrimental effects on human health, should be reduced. Policymakers might use the current findings to make policies about reducing the production and availability of processed meats. In addition, it seems that subsidizing red and processed meats should be shifted toward healthier animal protein options such as white meat and dairy products. In order to increase consumer awareness, the possible risks of consuming processed meat could be mentioned in nutrition labels.The original contributions presented in the study are included in the article/SN-M, AS-M, and AA contributed to the conception, design, literature search, statistical analyses, data interpretation, and manuscript drafting. BL contributed to the conception, design, and manuscript drafting. AE contributed to the conception, design, statistical analyses, data interpretation, manuscript drafting, and supervised the study. All authors approved the final manuscript for submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The apolipoprotein C3 (APOC3) polymorphism has been reported to predispose to non-alcoholic fatty liver disease (NAFLD). However, the results remain inconclusive. This meta-analysis aimed to provide insights into the association between APOC3 polymorphisms and NAFLD risk.Studies with terms “NALFD” and “APOC3” were retrieved from PubMed, Web of Science, CNKI and Wanfang databases up to August 1, 2019. Pooled odds ratio (OR) and 95% confidence interval (95% CI) for the association of APOC3 polymorphisms and NAFLD risk were calculated using fixed and random-effects models.A total of twelve studies from eleven articles were included. Of them, eight studies (1750 cases and 2181 controls) reported the strong association of variant rs2854116 with NAFLD and six studies (1523 cases and 1568 controls) found the association of rs2854117 polymorphism with NAFLD. Overall, a statistically significant association between rs2854116 polymorphism of APOC3 gene and NAFLD risk was found only under dominant model. However, association of rs2854117 polymorphism with NAFLD risk was not detected under all four genetic models. In sub-group analysis of NAFLD subjects based on country, no association among them in China was detected. Besides, four studies analyze the association between the two polymorphisms and clinical characteristics in all subjects or NAFLD patients, and we also failed detect any association between the wild carriers and variant carriers.The meta-analyses suggests that the rs2854116 polymorphism but not rs2854117 polymorphism in APOC3 gene might be a risk factor for NAFLD among Asians. That is, individuals with CT+CC genotype have higher risk of developing NAFLD. However, studies with sufficient sample size are needed for the further validation. Non-alcoholic fatty liver disease (NAFLD) is one of the most common cause of liver disease worldwide with prevalence varying from 15% to 40% in general population depending on the demographic area The apolipoprotein C3 gene (APOC3) is a member of the APOA1/C3/A4/A5 gene cluster and located on chromosome 11q23, an area in strong linkage with lipid metabolism We searched the PubMed, Web of Science, CNKI and Wanfang database before August 1, 2019, by using the key subjects “apolipoprotein C3 or APOC3” AND “genetic polymorphism or polymorphisms or variant” AND “non-alcoholic fatty liver disease or NAFLD”. Studies were restricted to human populations and studies written in other languages except for English were also considered. Additional studies were identified by a hand search of references of original or review articles on this topic.Studies were included according to the following criteria: (1) studies with clear diagnostic criteria, (2) studies that evaluatd the association between the APOC3 polymorphisms and NAFLD, (3) studies in a case-control design, and (4) studies with detailed genotype frequency of cases and controls or providing the necessary data to calculate genotype frequency. Studies were excluded when they were: (1) case-only study, case reports, and review articles, (2) studies without the raw data of the APOC3 genotype, and (3) repetitive publications.For each study, the following data were extracted independently by two investigators: the first author's name, year of publication, country of origin, age, gender, study design, diagnostic criteria of NAFLD, number of cases and controls, and HWE in controls  and analysis were carried on independently. The results obtained by those two investigators were compared, and disagreements were discussed among all authors and resolved with consensus.The risk of NAFLD associated with the two polymorphisms of the APOC3 gene was estimated for each study by odds ratio (OR) and 95% confidence interval (95%CI). A χ2-test-based Q statistic test was performed to assess the between-study heterogeneity All statistical analyses were performed using software Cochrane Collaboration RevMan 5.2 and STATA package version 12.0 .After an initial search, a total of 118 published articles relevant to the topic were identified. According to the inclusion criteria, 15 studies with full-text were included in this meta-analysis and 103 studies were excluded. Because the study by Cai et al For rs2854116 polymorphism, 8 case-control studies with 1750 cases and 2181 controls were identified. Overall, a significant association was detected under dominant model , however, there was no significant difference in APOC3 genotype distribution between NAFLD and control  , Table 2In addition, four studies with 2384 subjects reported the clinical characteristics in the study groups. No significant association was observed between the polymorphism and clinical characteristics  , Table 3For rs2854116 polymorphism, significant heterogeneity between studies was observed in overall comparisons under recessive and CC versus TT models . For rs2854117 polymorphism, no significant heterogeneity between studies was observed in overall comparisons. Then, sensitivity analysis, after removing one study at a time, was performed to evaluate the stability of the results. The results was not changed when any single study was omitted, confirming the stability of the results.Begg's funnel plot and Egger's test were performed to assess the potential publication bias in the available literature. The shape of funnel plots did not reveal any evidence of funnel plot asymmetry . Egger'sNAFLD is one of the most common liver disordersRecently, the APOC3 polymorphisms have been investigated the association with many diseases, such as metabolic syndrome In this(our) study, the potential correlation was also analyzed between the two polymorphisms and clinical characteristics. Four studies were enrolled and the combined results showed that there was no significant difference between the wide-type genotype and the variant genotypes in either all study groups or NAFLD group. Since only few studies reported the available data, this result should be interpreted with caution, and more studies are needed.Heterogeneity between studies is very common in the meta-analysis of genetic association studies Some limitations of this meta-analysis should be addressed. First, due to incomplete raw data or publication limitations, some relevant studies could not be included in our analysis. Second, the number of published studies, especially for Indian population was not sufficiently large for a comprehensive analysis, and some studies with small sample size may not have enough statistical power to explore the real association. Third, our results were based on unadjusted estimates, and lacking of the necessary information  for the date analysis may cause serious confounding bias.In summary, this meta-analysis suggested that APOC3 rs2854116 polymorphism is associated with NAFLD risk. Individuals with CT+CC genotype had an increased risk of NAFLD. Studies with large sample zise are needed to validate our findings.


Over the last twenty years, innovations in the treatment of childhood cancer have increased survival rates. However, female childhood cancer survivors (CCS) are prone to late reproductive aftereffects, including premature ovarian insufficiency (POI). Nonetheless, patients might experience different side effects on fertility according to the type of diagnosed cancer and subsequent treatment. Anti-Müllerian hormone (AMH) is currently used in reproductive medicine to screen for impaired ovarian reserves. However, it does not represent the gold standard in oncofertility. In this systematic review and network meta-analysis of age-matched case–control studies, we evaluate the role of AMH for ovarian reserve screening according to the type of childhood cancer and determined which group of survivors are more prone to POI by means of direct and indirect comparisons among the CCS cohorts.Background: Female childhood cancer survivors (CCS) might have impaired ovarian reserves, especially after alkylating agents or radiotherapy. The purpose of this systematic review and network meta-analysis is to evaluate the role of serum anti-Müllerian hormone (AMH) for ovarian reserve screening and the risk of premature ovarian insufficiency (POI) according to the subtype of childhood cancer. (2) Methods: PRISMA-NMA guidelines were followed. We carried out a network meta-analysis based on a random effects model for mixed multiple treatment comparisons to rank childhood cancers effects on fertility by surface under the cumulative ranking curve (SUCRA). Studies were selected only if they had an age-matched control group. Quality assessment was performed using Newcastle–Ottawa Scale. The co-primary outcomes were mean AMH levels and the incidence of POI. (3) Results: A total of 8 studies (1303 participants) were included. Women treated for a neuroblastoma during infancy were more likely to be ranked first for impaired AMH levels (SUCRA = 65.4%), followed by mixed CCS (SUCRA = 29.6%). The greatest rates of POI were found in neuroblastoma survivors (SUCRA = 42.5%), followed by acute lymphoid leukemia (SUCRA = 26.3%) or any other neoplasia (SUCR A = 20.5%). (4) Conclusions: AMH represents a trustworthy approach for ovarian reserve screening. Direct and indirect comparisons found no differences in mean AMH levels and POI risk between subtypes of CCS and healthy controls. SUCRA analysis showed that female neuroblastoma survivors were more at risk for reduced serum AMH levels and increased risk of POI. Therapies for cancer experienced during infancy or adolescence are known to harm fertility due to direct and indirect damage to the ovaries, with a significant loss of the ovarian reserves . EvidencTherefore, it is crucial to identify women at risk of developing POI to manage further complications. Different methods are being used in clinical practice to assess ovarian reserves: antral follicle count (AFC), ovarian volume, and serum levels of follicle stimulating hormone (FSH), estradiol, and inhibin B. FSH, estradiol, and inhibin B are all part of the feedback system, which makes their serum levels dependent on each other. The use of oral contraceptives and menopausal hormone therapy (MHT) leads to several difficulties in the interpretation of FSH and female sex steroids levels for gonadal status. In addition, the ovarian function needs to be significantly decreased to have a critical raise of FSH levels, which cannot be used as a sentinel for anticipating premature menopause ,12. BecaFor this reason, there was a need for a less invasive ovarian reserve marker, especially in young women who suffered from a childhood cancer.Anti-Müllerian hormone (AMH) is secreted by granulosa cells of growing pre- and early antral ovarian follicles. It has been remarked as an indirect measure of the “ovarian reserves”, the available set of primordial follicles retrievable in both ovaries at any time from birth to menopause . The serAlthough AMH has been certified as a valid marker for ovarian reserves, it is not still used as gold standard in follow-up programs for female childhood cancer survivors (CCS) .To date, AMH has been used especially in the work-up of women undergoing in vitro fertilization ,17. HoweThe aim of this systematic review is to evaluate the differences between AMH levels and risk of POI in women who survived cancer during childhood or adolescence, compared to healthy controls, and to establish whether there are differences among the subtypes of malignancies by means of direct and indirect comparisons.Cochrane Handbook for Systematic Reviews of Interventions [This network meta-analysis was conducted in accordance with the ventions  and the ventions . It follElectronic databases  were searched from the inception of each database to June 2021. Search terms used were a combination of text words and medical subject headings (MeSH), including: “Anti-Mullerian Hormone” or “Antimullerian Hormone” or “AMH” and “female cancer survivors” see . CINAHL,There were no restrictions for the geographic location or language of the original papers. In addition, the reference lists of all eligible studies were screened to assess studies not captured by electronic searches. The electronic search and the potential eligibility of the investigated studies were checked in an independent manner by two researchers (M.T. and G.R.). Any potential disagreement was resolved by discussion with a third reviewer (N.C.).Inclusion criteria were the following: prospective cross-sectional or retrospective case–control studies that included CCS women that were screened for AMH levels and/or POI and compared to age-matched healthy controls. Studies were excluded if they did not consider a control group or did not report at least one outcome of interest or lacked follow-up records with incomplete data.The abstraction forms were carefully built for this network meta-analysis. The key characteristics recorded included: patient descriptors, study duration, setting, details of treatment, features of the treatment, outcomes evaluated, features of the control group, results, and quality elements. All the abstracts were reviewed and classified by two researchers (G.R. and M.L.V.) independently. The agreement for possible relevance was reached by consensus; the same two researchers carried out a full-text evaluation of the selected papers and independently extracted relevant data concerning the trial characteristics and the outcomes of interest. All the inconsistencies were examined by the reviewers and consensus was reached by asking a third author (P.D.F.). If necessary, unpublished data was obtained by directly contacting the authors of the original studies whenever the study methodology indicated that other outcome data were recorded. The first co-primary outcome of this network meta-analysis was the mean AMH levels, defined as the serum blood levels of AMH retrieved from the blood samples of female CCS and healthy controls during the early follicular phase (day 2 to 5) of the menstrual cycle or randomly in the case of prolonged amenorrhea (no menses for at least 6 months). The second co-primary outcome was the rate of POI in CCS and controls, defined as absence of menarche or premature depletion of ovarian follicles before 40 years of age.In cohort studies eligible for this meta-analysis, the risk of bias in each of the available papers was assessed using the Newcastle–Ottawa Scale (NOS) criteria . AccordiTo establish comprehensive pooled estimates of the effects on ovarian reserve and the subsequent POI risk of the different treatments for the subtypes of childhood cancers, we performed a quantitative meta-analysis regarding respective parameters based on the Bayesian theorem. This statistical method evaluates both direct and indirect data from trials using a common comparator to obtain estimates of the effects according to the kind of treatment based on multiple intervention comparisons ,20.All data analysis and graphical renderings were performed using STATA version 14.1 . For the evaluated outcomes, to statistically confirm the overall consistency assumption among the networks of the meta-analysis, the command <network meta inconsistency> was used. Subsequently, for the local test on loop inconsistency, the SIDE (separating indirect from direct evidence)-splitting method, by means of the command <network sidesplit all> was executed. When there was no inconsistency in both the global and the local tests, the consistency model was accepted. In this case, the consistency assumption suggested that the direct and indirect comparisons showed significant results, and the differences between the data analysis and results were likely related only to the effects of the intervention or random-based errors.2) index was used for assessing potential heterogeneity. I2 degrees of 0%, 25%, 50%, and 75% were considered thresholds for absent, low, intermediate, and high heterogeneity, respectively. In the cases of significant heterogeneity, sensitivity analyses were carried out to understand relevant sources of heterogeneity.The summary measures were reported as odds ratio (OR) for categorical variables, mean difference (MD) for continuous variables using a 95% of confidence interval (CI), and adopting the random effects model of Der Simonian and Laird. Higgins I-squared ). The SUCRA is a numeric representation of the overall ranking, and it sums up each treatment effect by a percentage, ranging from 0 to 100%. The higher the SUCRA value and the closer to 100%, the higher the likelihood that a therapy is at the top rank or one of the top ranks as the most influential treatment; the closer the SUCRA value is to 0, the more likely that a therapy is of being placed at the bottom rank, or one of the bottom ranks, describing it as a less influential treatment .A total of 251 studies were originally identified through the database searches. Of those, 95 were removed as duplicates. After title and abstract screening, 133 studies were subsequently removed . A totalWomen were followed in the included trials starting in 1964 and 2017. All studies included women who were diagnosed with solid or hematologic tumors during their childhood or adolescence. The studies were conducted in Europe and Asia. An age-matched control group was used for comparisons in every paper. All participants fully recovered from the pathology with no signs of relapse at the enrolment. Four studies compared an unselected cohort of female CCS to age-matched healthy controls ,25,26,28Inclusion and exclusion criteria provided by cohort studies included in the network meta-analysis are reported in Using the NOS criteria, all evaluated trials reported high scores, ranging from a minimum of 6 to a maximum of 9. The comparability of cohorts reached the maximum score based on controls for age as most important factor and based on BMI as the additional factor. The detailed point-by-point assessment is depicted in Seven studies ,25,27,28p = 0.416). p = 0.900). The SIDE analysis showed that there were no substantial differences between direct and indirect comparisons in the closed loops considered for the network  see  and no sp = 0.211) indicated no significant publication bias in this network meta-analysis.For this primary outcome, the Egger’s test . A publication bias judged by the Egger’s test (p = 0.476) was not apparent for this outcome.The SIDE analysis demonstrated no significant differences between direct and indirect comparisons in the closed loops analyzed in the network  see  with no The forest plot b showed Analyzing the interval plot, there were no significant differences among the risk of POI between the different pathologies or healthy controls c.Taking all together, according to the SUCRA ranking plot d, there This systematic review and network meta-analysis of cohort studies showed that AMH is a reliable indirect way to evaluate the ovarian reserve in CCS. In women who survived a CCS or hematologic neoplasia, AMH levels do not show differences from the healthy population. However, healthy controls showed a reduced risk of POI relative to neuroblastoma survivors, and chances of being diagnosed with POI are higher in a mixed CCS population rather than in survivors of neuroblastoma, acute lymphoid leukemia, or thyroid cancer.Gonadal function should be regularly tested during the long-term follow-up of female CCS ,29. HoweTo date, AMH and AFC have shown the best trustworthiness as screening tests for ovarian reserves. However, a test with a 100% sensitivity or specificity for ovarian reserves does not exist ,33. In aPrevious studies have researched the fluctuations AMH levels before, during, and after treatment for cancer in young women . In someConcerning the effects of 131-I used for differentiated thyroid cancer, AMH levels in long-term follow-up women seem unaffected by the therapy . QuantitAlthough Nies et al.  describeFor women who survived a childhood neuroblastoma, Utriainen et al.  showed tRoshandel et al.  found thVan der Kooi et al.  investigThis systematic review and network meta-analysis has several limitations. First, the number of qualified papers was relatively small, with small sample sizes. Second, additional outcomes and subgroup analysis were not evaluated due to retrieved data from original studies, since only two studies performed subgroup analyses according to the subtype of therapy. Although all the included trials followed strict protocols, for most papers, data were retrospectively collected, leading to possible biases. However, due to the nature of the disease, it would be impossible to perform randomized trials; for this reason, such research should be considered the best evidence that can be achieved.In fact, a strength of our study is the quality of selected papers, since only papers with an overall low risk of bias were included in the network meta-analysis. Another strength of the study is the wide range of geographical areas covered by the available research, extending the possible generalization of the results. An additional robustness of this quantitative synthesis is the inclusion of only age-matched cohort studies, avoiding confounders of purely observational studies without controls.In conclusion, AMH represents a valuable method for evaluating the ovarian reserves in female CCS. According to this network meta-analysis, there were no significant differences between treated CCS and healthy controls for every subtype of childhood cancer and no differences between indirect comparisons of evaluated treatments. However, according to the SUCRA analysis, neuroblastoma survivors during infancy seem more prone to have impaired AMH levels, followed by unselected female CCS. The risk of developing a POI is, indeed, notable in every CCS, since direct and indirect comparisons showed no differences between subtypes of cancer treatments. In addition, SUCRA analysis showed that such risk should be considered especially when total body or localized RT is performed and in the case of a childhood neuroblastoma. However, further comparative studies between different therapeutic strategies are needed to compare therapeutic regimens, doses, as well as RT subtypes in female CCS to avoid the risk of impaired ovarian reserves and POI.


Night shift work (NSW) may disturb circadian rhythms. This could influence the risk of breast cancer (BC), but research papers have reported conflicting results. We reviewed, summarized, and combined the results of those studies that measured the effect of long-term nightshift work (≥15 years of NSW) in BC with special attention to menopausal status and time since retirement age. Women with long-term NSW had 13% more risk of BC than women without NSW. Postmenopausal women showed no increased risk, while premenopausal women had a 27% higher risk. Women with a higher probability of recent long-term NSW (women under retirement age) had a 23% higher risk than women without NSW. We concluded that long-term NSW may increase BC risk, especially in women before menopause or shortly after NSW discontinuation.2 = 56.8%, p = 0.002). BC risk increased 4.7% per 10 years of NSW . The pooled estimate for premenopausal BC was 1.27  and for postmenopausal BC 1.05 . For recent long-term exposure, the pooled estimate was 1.23 . Our results indicate that long-term NSW increases the risk for BC and that menopausal status and time since exposure might be relevant.This systematic review discusses long-term NSW and female BC risk, with special attention to differences between pre- and postmenopausal BC, to test the association with recent NSW. The review follows PRISMA guidelines (Prospero registry: CRD42018102515). We searched PubMed, Embase, and WOS for case–control, nested case–control, and cohort studies addressing long-term NSW (≥15 years) as risk exposure and female BC as outcome until 31 December 2020. Risk of bias was evaluated with the Newcastle–Ottawa scale. Eighteen studies were finally included . We performed meta-analyses on long-term NSW and BC risk; overall and by menopausal status; a subanalysis on recent long-term NSW, based on studies involving predominantly women below retirement age; and a dose–response meta-analysis on NSW duration. The pooled estimate for long-term NSW and BC was 1.13 (95%CI = 1.01–1.27; 18 studies, I Many women’s working lives are characterized by some degree of night work, either as permanent shifts or as shifts within rotating work schedules. The European Union defines “night time” as any period of seven or more hours- as defined by national law, which includes the period between midnight and 5.00 a.m. . Two larHumans share with other organisms the fundamental properties of a biological circadian system . Night wIn 2019, the International Agency for Research on Cancer, confirming a previous evaluation, classified NSW as probably carcinogenic to humans . Its decision was based on limited evidence from studies in humans and strong evidence from experimental findings, which showed its effects in immunosuppression, chronic inflammation, and cell proliferation . The tumThis issue has awakened enormous interest, given the global burden of breast cancer (BC)  and the Another important issue that might help to understand the inconsistent results is the possible role of menopausal status in this presumptive association. Pre- and postmenopausal breast cancer have different temporal trends, can differ in their molecular profile, and even have opposite relationships with some of the known risk factors for this tumor, such as obesity  ,24,25.Another possible reason for these discrepancies might be related to a critical point: the lag time between the last NSW exposure and the end of follow-up for the occurrence of BC in some cohort studies ,27. SomeFor this reason, we carried out an overall meta-analysis of observational studies on long-term NSW and BC, a dose–response meta-analysis, and a sub-meta-analysis on recent long-term NSW. Therefore, this meta-analysis allows exploring both factors, the duration of NSW, and recent exposure in BC risk assessment. Given the possible biological differences between pre- and postmenopausal BC associated with long-term NSW, we also carried out subgroup analyses by menopausal status.This review was conducted according to the PRISMA guidelines . The proOur final search strategy was complemented with a manual search based on the references cited in the papers selected for full-text review. Additionally, we also went through the reference lists of the published meta-analyses. We took into consideration results in English, Spanish, German, or French. For this review, we considered eligible all original case–control, nested case–control, and cohort studies that compared, as risk exposure, long-term NSW (defined as ≥15 years) to having never done NSW. These studies had to provide original data and to have female BC risk as the outcome.Two members of our research team  performed the original abstract/title screening, the full-text review, and the data extraction. In case of doubts or disagreements, a third author’s opinion (B.P.G.) allowed reaching a consensus. In the presence of diverse options of risk estimators, we used preferentially those including NSW exposure between 12.00 p.m. and 3.00 a.m. In cohort studies with several reports, we used the latest update if there were new cases or if the analysis was improved in terms of methodology. With respect to exposure ascertainment, we prioritized self-reported individual data over job-exposure matrix estimations. According to our inclusion criteria, we selected studies providing data corresponding to a minimum of 15 years of NSW, without restricting the exposure to a minimum number of nights per month. Authors from two studies were contacted to request additional data about the definition of nonexposure (information received) and mean age at BC diagnosis .The risk of bias of each study was evaluated by two researchers  using the Newcastle–Ottawa scale (NOS) , an eighGlobal meta-analysis of long-term NSW (for ≥15 years) and BC2 statistic [We compared BC risk for women exposed to NSW for ≥15 years to that of unexposed women. We estimated summary risk ratios (RRs) and 95% confidence intervals (CIs) as the measure of effect. Individual effect estimates were extracted to construct a database with the logarithm of the risk estimator reported in each study , or odds ratio (OR)) and its standard error (SE). If SEs were not provided in the publication, we calculated them from the CI, using the formula: SE = (lnCIupper limit-lnCIlower limit)/(2 × 1.96). When the report provided different categories of exposure but not an overall estimator, we calculated pooled RRs and variances using the formulas: lnRR pooled = (lnRR1/Var1 + lnRR2/Var2 + lnRRn/Varn)/(1/Var1 + 1/Var2 + 1/Varn) and Varpooled = 1/(1/Var1 + 1/Var2 + 1/Varn). The proportion of variance due to heterogeneity was estimated by the Itatistic . HeterogTo assess publication bias, funnel plot asymmetry was visually inspected and statistically tested with Begg’s and Egger’s tests . We also carried out two sensitivity analyses: (a) excluding those studies with uncertain exposure definition see  and (b) © version 15 codes  from StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC were used for the meta-analysis and RevMan 5.4 test for differences in the predefined subgroup analyses [Program Codes Specific STATAanalyses .Dose–response meta-analysis2 statistic, which described the proportion of total variation in log-relative risks due to heterogeneity [For studies reporting disaggregated results by duration of NSW, we further conducted a random-effects dose–response meta-analysis of log-relative risks (either adjusted log hazard ratios for cohort studies or adjusted log odds ratios for case–control studies) on mean durations of NSW for each exposure category . The dosogeneity . The dosSubgroup meta-analysis by menopausal statusWe stratified the overall analysis by menopausal status, which was preferentially based on self-reported information. If this information was not available, given cut-off points between age 50 and 55 were accepted to classify women either as pre- or as postmenopausal. Again, a sensitivity analysis was performed, restricting the meta-analyses to those studies with NOS ≥ 7.As the information on the timing of long-term NSW exposure was not readily available in the selected studies, we used an indirect approach based on the analysis of BC before retirement. We classified as having recent NSW those participants in the subgroup of studies in which, either the mean age of the participants at study entry plus the maximum follow-up time (cohort studies) or the mean age at BC diagnosis (case–control studies) was below the country-specific retirement age in that year; this age was obtained from the official government websites of each country or of the Organization for Economic Co-operation and Development . The metThe initial search yielded 1524 records found in PubMed, Embase, and Web of Science. After the selection process, 16 articles with data from 18 research studies were finally included in the global meta-analysis .It is noteworthy to indicate that the early publications of the Nurses Health cohort studies (NHS I and II) ,40,41 weConcerning the timing of exposure ascertainment, in cohort studies, it was mostly performed only at baseline, with just a few studies collecting data of additional years of NSW during follow-up ,47. In nAs regards the duration of exposure, in 10 studies, the risk estimates provided by the authors corresponded to NSW exposures of at least 20 years ,47,48,50The detailed risk of bias assessment for each selected study, according to the Newcastle–Ottawa scale (NOS), is available in the Global meta-analysis on long-term NSW and BC risk2 = 56.8%, p = 0.002). When we took into account study designs, the meta-analysis yielded no association between NSW and BC in cohort studies ; for nested case–control studies, it showed an almost significant risk increase, although with high heterogeneity ; and, finally, in case–control studies, the pooled risk indicated an excess risk of BC among exposed women . We performed sensitivity analyses: (a) excluding the studies with uncertain exposure definition, which showed similar results    ; and (b)031) see .p = 0.03, Begg’s test p = 0.08). The asymmetry was not present in a funnel plot limited to the high-quality studies (NOS ≥ 7) .The funnel plot to evaluate a possible relation between the RR of BC and the study precision showed an imbalance , which w≥ 7) see  , and no significant differences among cohort, nested case–control, and case–control studies (p for interaction between exposure duration and study design = 0.45). Adding a quadratic term to the model for exposure duration did not significantly improve model fit (p = 0.389).The dose–response meta-analysis was based on 16 studies. Risk trends across categories of exposure duration varied substantially from one study to another, although most of them tended to show an increase in risk with rising duration of NSW . The pooSubgroup analysis by menopausal status2 = 32.0%, p = 0.196)  (p = 0.27). However, in our sensitivity analysis, restricted to high-quality studies, the difference between both subgroups was more marked   , mostly = 0.050) , althoug.05) see .2 = 48.4%, p = 0.018) (p = 0.001). The results were similar in all study design groups .This last meta-analysis included data from 15 studies. Among them, data from the NHS1 after 10 years of follow-up could be included, as the biological age of menopause normally is below the retirement age of 65 years . The upd= 0.018)   from those of menopausal status and age.Our global findings are similar to the results of a meta-analysis carried out by Jia et al. , who repOur analyses of long-term NSW suggest that this exposure was associated with BC before retirement or menopause. It is conceivable that, during regular NSW exposure, changes in sex hormone secretion  or otherThe exhaustive literature search, including studies published up to December 2020, allowed us to provide updated estimates of risk associated with long-term NSW, as well as to perform an updated dose–response meta-analysis. In contrast to a previously published report , we inclNotwithstanding, this review also has limitations. The asymmetry of the funnel plot may suggest that our estimates can be affected by publication bias or by differences in the quality of smaller studies that may spuriously inflate their effects . HoweverOur meta-analysis supports the hypothesis that long-term NSW is a risk factor for BC. Even though the possible effect of the publication bias is small, we prudently classify the evidence as low. Among the factors that may modify this risk, which are possible sources of the observed heterogeneity, are menopause and time since last NSW exposure. Both factors point towards higher risks in younger women. In contrast, no association was found between long-term NSW and BC in postmenopausal women. Future investigators on NSW and this tumor should also take into consideration the timing of exposure and the menopausal status at BC diagnosis.