Several psychiatric disorders have been associated with an increased risk of developing a neurodegenerative disease and/or dementia. Attention-deficit/hyperactivity disorder (ADHD), a neurodevelopmental disorder, has been understudied in relation to dementia risk. We summarized existing literature investigating the risk of incident neurodegenerative disease or dementia associated with ADHD.We searched five databases for cohort, case–control, and clinical trial studies investigating associations between ADHD and neurodegenerative diseases/dementia in May 2023. Study characteristics were extracted by two independent raters, and risk of bias was assessed using the Newcastle Ottawa Scale. Search terms yielded 2,137 articles, and seven studies (five cohort and two case–control studies) ultimately met inclusion criteria. Studies examined the following types of neurodegeneration: all-cause dementia, Alzheimer’s disease, Parkinson’s and Lewy body diseases, vascular dementia, and mild cognitive impairment. Heterogeneity in study methodology, particularly covariates used in analyses and types of ratios for risk reported, prevented a meta-analysis and data were therefore summarized as a narrative synthesis. The majority of studies (4/7) demonstrated an overall low risk of bias.The current literature on risk of developing a neurodegenerative disease in ADHD is limited. Although the studies identified present evidence for a link between ADHD and subsequent development of dementia, the magnitude of the direct effect of ADHD on neurodegeneration is yet to be determined and better empirically designed studies are first needed. Furthermore, the mechanism of how or why ADHD is associated with an increased risk of developing a neurocognitive disorder is still unclear and should be explored in future studies.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022348976, the PROSPERO number is CRD42022348976. DementiIn 2019, it was estimated that 55 million people were living with dementia worldwide, a number that is expected to increase to 78 million by 2030 and 139 million by 2050 , 5. AddiAlthough age is the strongest risk factor for dementia , 8, demeIn the last decade, studies have emerged identifying attention-deficit/hyperactivity disorder (ADHD), one of the most common neurodevelopmental disorders, as a new psychiatric condition that additionally may increase the risk of later development of dementia , 17. ADH2.This study was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines . The rev2.1.To identify relevant articles, we used key words and medical subject headlines see  to searcInclusion criteria were: (1) study design was either cohort study, clinical trial, or case–control study, (2) participants were adults (aged 18+) with ADHD diagnosed using standardized clinical criteria, and (3) outcome was a neurodegenerative disorder and/or dementia diagnosed using standardized clinical criteria. Studies were excluded if the study population was comprised only of people <18 years of age, or if the publication was a systematic review, meta-analysis, conference abstract, book, book chapter, editorial, case study, case series, opinion, or dissertation/thesis.2.2.Adults who received a clinical diagnosis of ADHD per standardized criteria, defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM)  or the IThe primary outcome was the development of a neurodegenerative disorder or dementia . Outcomes were defined using relevant standardized clinical criteria: DSM or ICD codes, or validated consensus criteria [e.g., the National Institute on Aging criteria for AD , the DLB2.3.Titles and abstracts of studies retrieved using the above search strategy were each screened by two of six raters who were blinded to others’ ratings, to ascertain inclusion criteria. All articles either not fulfilling all inclusion criteria, or fulfilling any of the exclusion criteria, were excluded. Manuscripts were assessed independently, and disagreements were resolved between the two screening raters. Potentially eligible studies were retrieved, and the full text was then further assessed for eligibility by two independent raters. All disagreements were resolved through discussion between the two raters.2.4.Two review authors independently extracted data from retained studies into a standardized form for assessment of study quality and evidence synthesis. Any discrepancies were identified and resolved through discussion, arbitered by a third author where necessary. Extracted information included: aims, setting, population, methodology (including inclusion and exclusion criteria), recruitment and study completion rates where applicable, operationalized definitions of ADHD (exposure) and neurodegeneration and/or dementia (outcome), number of exposed (ADHD) and unexposed (control) participants as well as their characteristics , total number of outcomes where applicable, odds/risk ratios – crude and adjusted – reported including variables that were controlled or covaried for, and related information for assessment of the risk of bias. Missing data regarding exposure and outcomes for three studies –32 were 2.5.Each study included was independently assessed by two researchers using the Newcastle-Ottawa Quality Assessment Scale (NOS) for case–control and cohort studies . The NOS2.6.We planned to synthesize the effect measures  collected from the final selected studies through a meta-analysis. This would provide us with a pooled estimate (weighted average) of the effect measures , and we would be able to obtain an overall/summary estimate of the association between our exposure (ADHD) and outcome (neurodegenerative disorders/dementia). Furthermore, we wanted to specify in the meta-analysis if the odd ratios/risk ratios reported in the individual studies were crude or adjusted, and what factors were adjusted for in the individual studies.2.7.We planned to undertake the following subgroup analyses to see if effect measures vary across these factors: by age, by gender, by ethnicity, by neurodegenerative disease subtypes , by study design , by study quality, and by diagnostic criteria applied .3.3.1.A total of 2,173 potential records were identified, of which 36 were duplicate articles that were subsequently removed see , 35–38, 3.2.3.2.1.Five cohort studies met inclusion criteria , 35–37. Participants across the studies ranged from younger adults 30’s) to older adults (60’s). Only one study  reported’s to old3.2.2.The potential risk of bias, quantified using the NOS for cohort studies, is shown in 3.3.3.3.1.Two case–control studies met inclusion criteria , 38; oneThe two case–control studies reported on AD , PD 38)38), and 3.3.2.The potential risk of bias, quantified using the NOS for case–control studies, is shown in 3.4.The planned meta-analysis was not feasible as there was an insufficient number of homogeneous studies to calculate a pooled risk ratio. Of all seven studies, only four studies reported crude ratios (of which two were case–control and two were cohort studies) and all calculated different ratios for risk . Furthermore, each study controlled or covaried for different factors: two adjusted for demographics (sex and birth year) , 37, whi4.This is the first systematic review examining the risk of incident neurodegenerative disease or dementia associated with ADHD. From the literature search, only a few cohort and case–control studies were identified that examined this association, all with different populations and methodologies. Although the study differences prevented data synthesis, the individual results tentatively suggest a link between ADHD in adults and development of neurodegeneration or dementia.Results show that ADHD is differentially associated with all-cause and subtypes of dementia. Interestingly, the highest ratio was found for VaD, where people with ADHD had a 6-fold higher risk than controls after adjustment for covariates. VaD is defined as severe cognitive impairment compromising daily functioning and evidence of cerebrovascular disease on imaging . Adults reduced risk for developing PD relative to participants who had not been prescribed stimulants  may be misinterpreted as signs of MCI or early AD . AlthougAll-cause dementia was the most variable in terms of risk, where adjusted hazard ratios ranged from 0.98–4.01. It has been suggested people with ADHD have an increased risk of overall health problems, and that ADHD itself leads to the development of factors or disorders that can compromise health and which are, in and of themselves, risk factors for dementia , 55. AlmIt should be noted that the prevalence of ADHD in all studies (from 0.19–16.7%) is markedly different than the global prevalence which is approximately 3% in adults , 62. Thi4.1.While the individual results suggest there is a link between ADHD and development of a subsequent neurodegenerative disease/dementia, we were unable to determine the pooled risk of developing a neurodegenerative outcome due to the marked heterogeneity of the studies. The main challenge to the synthesis of data was the use of different ratios to assess risk – three studies calculated hazard ratios, three studies calculated odds ratios, and one study calculated an incidence rate ratio – and not all studies reported crude or unadjusted ratios. It will be essential for future studies to report crude ratios along with any adjusted analyses to facilitate data synthesis for future meta-analyses.Another challenge to data synthesis was the definition of exposures and outcomes used in each study. The definitions of both ADHD and neurodegeneration, despite being mostly classified by ICD codes, were different across studies. This has also been extensively discussed in our previous critical review of these studies . For exaLastly, as discussed earlier, it is important to control for known risk factors for dementia and those that may be mediating or confounding the relationship between ADHD and dementia risk, such as comorbid psychiatric disorders or vascular factors. It is also important to include demographic factors including age, sex, race/ethnicity, as well as socioeconomic factors such as education, income level, and relationship/social support. While age is the strongest risk factor for dementia , 8, sex Overall, the challenges to performing a meta-analysis highlight the need for improved methodology in assessing the link between ADHD and neurodegeneration, as well as improved study reporting.4.2.a priori to ensure that diagnoses of both exposure and outcomes were valid and reliable.Our strict inclusion/exclusion criteria led to the exclusion of half the studies that were identified through abstract screening. ADHD must have been diagnosed using standardized  criteria, which led to exclusion of three studies: two used genetic scores (polygenic risk scores) to determine ADHD status and one study used a retrospective questionnaire for ADHD symptoms. The outcomes must have been defined by standardized or consensus criteria, which, for example, led to exclusion of one study examining MCI defined using only a screening battery. We justified this 5.This is the first systematic review to examine the relationship between adult ADHD and future development of a neurodegenerative disease or dementia. Our review provides preliminary results that a diagnosis of ADHD may be a risk factor for the later development of a neurodegenerative disease or dementia. The mechanism of how or why ADHD is associated with an increased risk of developing a neurocognitive disorder is still unclear and should be explored in future studies. Due to the heterogeneity of studies included, no meta-analysis of data was possible, and we were unable to determine the pooled risk for developing a neurodegenerative disease or dementia in people with ADHD. This highlights the need for more stringent and well-defined studies, and we advocate for improvements in study methodology and statistical analyses to further advance this research.The original contributions presented in the study are included in the article/SB and BC conceived the research question and designed the study. PT conducted the literature search. SB, MC, PT, DS, and BC screened titles and abstracts for inclusion in the study. SB and BC screened full texts for final inclusion into the study, extracted data, and rated each manuscript for quality. SB wrote the first draft of the manuscript. MC, PT, DS, and BC contributed substantially to drafting the article and revising it critically for intellectual content. All authors have read and agreed to the published version of the manuscript.This review received no specific grant from any funding agency. SB receives salary support from a Canadian Institutes of Health Research Fellowship. MC receives salary support from a Mathison Centre Postdoctoral Fellowship and an O’Brien Institute for Public Health Postdoctoral Scholarship. PT receives salary support from the Alzheimer’s Association. DS receives grant funding from the Canadian Institutes of Health Research – Canadian Consortium on Neurodegeneration in Aging, the Alzheimer’s Association, and the University Health Foundation – Alberta Roche Collaboration in Health. BC’s research program is supported by the Canada Research Chairs Program.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 meta-analysis also showed a higher risk of major adverse cardiovascular events (MACEs) in patients with a low PNI . Moreover, advanced age, diabetes mellitus, and high Global Registry of Acute Coronary Events risk scores were associated with a high risk of all-cause mortality, whereas a high body mass index was associated with a low risk of all-cause mortality. The results showed an association between a low PNI and an increased risk of long-term mortality in patients undergoing coronary interventions for ACS. Further randomized controlled trials are necessary to confirm these findings.The predictive value of the prognostic nutritional index (PNI) for the long-term prognosis of patients with acute coronary syndrome (ACS) remains uncertain. Medline, Embase, Cochrane Library, and Google Scholar were searched from inception until January 2023 to study the relationship between all-cause mortality risk and PNI in patients receiving percutaneous coronary intervention for ACS . Thirteen observational studies were included in this meta-analysis. Analysis of seven studies using PNI as a categorical variable showed a pooled hazard ratio (HR) of all-cause mortality of 2.97 (95% CI 1.65 to 5.34,  Although improvements in interventional and antithrombotic treatments, secondary prevention, and risk factor modification during the past decade have decreased the short-term mortality rate, such as in-hospital and 30 days mortality after myocardial infarction, to approximately 5–8% after myocardial infarction3, the relatively high long-term mortality 4 highlights the need to identify high-risk patients and modify the risk factors at an early stage. Malnutrition, which is commonly observed in patients with acute coronary syndrome (ACS), can lead to reduced immune function and increased inflammation, which negatively impacts disease outcomes and increases the risk of complications6. Indeed, poor nutritional status has been identified as an independent risk factor for the development and progression of ACS7. Therefore, recognizing and addressing the issue of malnutrition in patients with ACS is of paramount importance in enhancing overall patient outcomes and alleviating the burden of complications.Despite the dramatic reduction in cardiovascular disease-related mortality over the last few decades, ischemic heart disease continues to be the leading cause of death worldwide13. Although a low PNI score  has been shown to be related to increased morbidity and mortality in patients with malignancy, its role as an indicator of the long-term outcome in patients receiving coronary interventions for ACS remains controversial16. In a recent study, Chen et al. demonstrated the potential benefits of incorporating PNI into the Global Registry of Acute Coronary Events (GRACE) score for the prediction of long-term all-cause mortality in patients diagnosed with ACS16. In contrast, Basta et al.7 utilized the Controlling Nutritional Status (CONUT) score as a measure of nutritional status and observed that it exhibited a more robust and significant association with all-cause mortality than the PNI in patients with ST-segment elevation myocardial infarction (STEMI).The Prognostic Nutritional Index (PNI), which combines two nutritional markers, namely serum albumin and total lymphocyte count, has been validated in evaluating the nutritional and inflammatory status of critically ill patients to predict outcomes such as the length of hospital stay, postoperative delirium, and mortality and morbidity in cancer and non-cancer surgical settingsBased on the evidence mentioned above, we propose that PNI could serve as a dependable factor for evaluating and predicting long-term outcomes in patients with ACS. To further explore this potential, we conducted a meta-analysis incorporating updated data from published studies. The primary aim of our research was to investigate the association between PNI and the risk of all-cause mortality in patients undergoing percutaneous coronary intervention (PCI) for ACS. The secondary outcomes included (1) the correlation between a low PNI and the risk of major adverse cardiovascular events (MACEs)/major adverse cardiac and cerebrovascular events (MACCEs), and (2) the relationship between other predictors and the risk of all-cause mortality.Details of the protocol registration are available in the International Prospective Register of Systematic Reviews (PROSPERO) (Registration Number: CRD42023392205). We performed this meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist.The eligibility criteria for the current study were as follows: (1) studies focusing on individuals with various types of ACS  undergoing PCI. Patient demographics, comorbidities, and study design  were not subjected to any restrictions in this meta-analysis; (2) studies investigating the correlation between PNI and all-cause mortality or MACEs/MACCEs with a long-term follow-up; and (3) studies with data available for the calculation of hazard ratio (HR).We excluded studies that (1) only reported in-hospital outcomes; (2) included patients undergoing cardiac surgery; (3) were presented as case reports, review articles, conference abstracts, or letters; and (4) did not involve PCI.The Embase (Ovid), Medline (Ovid), Cochrane Library, and Google Scholar databases were searched from inception to January 17, 2023, using the following search terms: (“prognostic nutrition index” OR “PNI”) AND . Details of the search strategies are summarized in Supplementary Table The association between a low PNI and the risk of all-cause mortality served as the primary outcome, while the secondary outcomes included (1) the correlation between a low PNI and the risk of MACEs/MACCEs, which was defined based on individual studies, and (2) the relationship between other predictors and the risk of all-cause mortality. The data retrieved from the eligible studies included the first author’s name/published year, country, study design, patient population and number, sex distribution, mean or median age at baseline, PNI cutoff values for defining low or high PNI, and follow-up period. In our data extraction process, for studies that categorized patients into tertiles or quartiles based on PNI, we collected data from the lowest and highest tertiles or quartiles. By focusing on extreme groups, we aimed to minimize the impact of potential confounding variables that could exist in the middle tertile or quartile. For studies that provided both unadjusted and adjusted data, we collected adjusted data for analysis.18 to assess the quality of non-randomized studies. The NOS evaluates three key aspects: selection of study groups, comparability of these groups, and ascertainment of exposure and outcome. Each study was assigned a star rating for each category, with higher stars indicating better quality. Each study included in our systematic review was independently assessed by two reviewers using these criteria to evaluate methodological quality. Discrepancies in the quality assessment were resolved through discussion and consensus. As previously reported, a study with an overall NOS score of ≥ 7 was regarded as high-quality18.In the current meta-analysis, we used the Newcastle–Ottawa Scale (NOS)Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology, the certainty of evidence for each outcome fell into the following four categories: very low, low, moderate, or high. Risk of bias and certainty of evidence assessments were performed by two independent reviewers, with disagreements settled through consultation with a third author.To assess the agreement between the two independent reviewers, we calculated the kappa statistic, which is a commonly used measure to quantify the inter-rater agreement for categorical data. The kappa statistic ranges from − 1 to 1, with 1 indicating perfect agreement, 0 indicating agreement due to chance, and values of − 1 indicating complete disagreement. A kappa statistic of 0.8 or higher is generally considered to be in good agreement, while a kappa statistic of 0.6 or higher is considered to be fair agreement.2 statistic was applied, with statistical significance set at I2 > 50%19. When significant heterogeneity was found for the primary outcome, the sources of heterogeneity were identified using meta-regression analysis based on sample size, PNI cut-off value, and length of follow-up. A sensitivity analysis was conducted to confirm the robustness of the outcome by sequentially removing one study at a time. Funnel plots were visually examined to identify the risk of publication bias when more than 10 datasets were included in the pooled analysis20. Statistical p was set than 0.05.The data analysis was performed using two software tools: Review Manager (RevMan) version 5.4 and the “metaphor” package in R software version 4.2.1. A random-effects model was used for all the analyses. We made a predetermined decision to employ a random-effects model for outcome evaluation, regardless of the presence or absence of statistical heterogeneity, based on the assumption that heterogeneity might exist across the included studies. The association of PNI with long-term outcomes was calculated using the PNI value as a continuous  or categorical  variable. If several categories of PNI values were provided in a study, the lowest and highest categories of PNI were used for the risk calculation. To evaluate the degree of heterogeneity among the samples, the I29. The calculated kappa statistic for the two-step selection process yielded a value of 0.89, indicating a substantial agreement between the two reviewers in selecting studies for inclusion in the systematic review. Of the 314 potentially relevant records initially identified 24, Korea (n = 2)28, Italy (n = 1)7, and Spain (n = 1)6. A total of 16,579 patients were included, with a male proportion of 51.6% and 81%, respectively. Seven of the analyzed studies explicitly stated that they excluded patients with active infections27. Conversely, in the remaining six studies, there was no explicit mention of the criteria regarding the exclusion of patients with active infection29. In seven studies, the initial diagnosis of myocardial infarction included STEMI (n = 4)28 and NSTEMI (n = 3)29. Another six studies included patients with ACS without mentioning the type of myocardial infarction24. The mortality rate varied widely across the included studies (range: 3.6–19.6%), with a pooled mortality rate of 7.5% (95% CI 5.6–10.0%) . For patients with a low PNI, the pooled HR of all-cause mortality was 2.97      with the risk of all-cause mortality was available in seven studiesp = 0.0002, I2 = 87%, six studies, 6616 patients, certainty of evidence: very low) 25 with PNI as a categorical variable  (three studies)24 or as a continuous variable (three studies)28. Using PNI as a categorical variable , a meta-analysis showed a higher risk of MACEs in patients with a low PNI   Other predictors of all-cause mortality are summarized in Table This meta-analysis, which involved 13 retrospective studies including 16,579 patients receiving PCI for ACS followed from 12 to 67.2 months, showed a positive correlation between a low PNI, either as a categorical or continuous variable, and an increased risk of all-cause mortality. Likewise, our analysis of six studies focusing on MACEs/MACCEs revealed increased risks of these long-term complications in patients with a low PNI. The robustness of the evidence was supported by consistent results of the sensitivity analyses. In addition, our study demonstrated a significant association between other risk factors, namely advanced age, diabetes, and high GRACE risk scores, and elevated long-term mortality in patients with ACS. Interestingly, high body mass index was associated with a reduced risk of all-cause mortality. Taken together, our study showed that poor nutritional status, as reflected by a low PNI, correlated with an increased risk of mortality and long-term complications in patients receiving PCI for ACS.30. Consistently, the current study demonstrated a negative correlation between BMI and mortality risk. Therefore, our findings provide robust evidence supporting the significance of a low PNI as a specific red flag for predicting poor outcomes in patients with ACS after coronary interventions. Prior studies have shown that the pathophysiological mechanisms by which nutrition is linked to ACS are complex and multi-faceted32. For instance, chronic low-grade inflammation triggered by malnutrition can exacerbate the development of coronary artery disease33. In addition, malnutrition can increase oxidative stress in the body, thereby contributing to the development of ACS34. Oxidative stress, the accumulation of reactive oxygen species, causes damage to cells and tissues, including the coronary arteries34. Furthermore, an inadequate supply of nutrients, such as glucose and amino acids, can lead to cardiac muscle dysfunction35. Previous investigations have identified poor nutrition, which has been frequently ignored as an important risk factor for negative cardiac remodeling and endothelial dysfunction38. Moreover, poor nutritional status can result in muscle wasting and impaired immune function, which negatively impacts recovery from ACS and increases the risk of complications such as infections39. Lastly, malnutrition may predispose to disturbances in lipid metabolism and increase the levels of certain lipids , thereby affecting the equilibrium among different lipids in the circulatory system in favor of cardiovascular diseases40. Therefore, malnutrition can significantly impact the development and progression of ACS. Understanding the mechanisms by which malnutrition contributes to ACS is important for implementing appropriate preventive and therapeutic strategies.An analysis from the Korea Acute Myocardial Infarction Registry (KAMIR) reported an independent negative association between body mass index and risk of long-term cardiovascular events in patients with ACS41. Considering that the PNI is computed by summing the serum albumin (g/L) and five times the total lymphocyte count (109/L), it is possible that the observed association between low PNI values and increased mortality rates in the present meta-analysis could, in part, be attributable to a diminished lymphocyte count. The comparative effectiveness of PNI in predicting mortality in patients with ACS remains to be fully elucidated when compared with other nutritional indices. For instance, Basta et al. reported that the CONUT index, which includes serum albumin, total cholesterol levels, and total lymphocyte count, was superior to the PNI in predicting all-cause death in patients with STEMI7. Additionally, the proportion of patients at risk of malnutrition, as evaluated using the CONUT index, was higher than that assessed using the PNI index (60% vs. 52%)7. Further large-scale studies are required to comprehensively address these important issues.A previous study reported that lower lymphocyte count was associated with an elevated risk of long-term mortality and cardiovascular readmissions42, it would be of interest to investigate the individual performance of albumin as a prognostic indicator and compare it with that of the PNI. A meta-analysis, which included eight studies comprising 21,667 ACS patients, revealed that ACS individuals with low serum albumin levels were at an elevated risk of long-term mortality (risk ratio:1.75)43. In the current meta-analysis, we found that a low PNI was associated with significantly increased long-term mortality risk (hazard ratio: 2.97). While it may not be entirely rational to directly compare the predictive strengths of the two parameters , these findings suggested that the use of PNI to predict long-term outcome may be favorable.As a previous study demonstrated an association between low serum albumin levels and adverse outcomes in patients with STEMI44. Although GRACE risk scores that consist of hemodynamic parameters and electrocardiographic and laboratory information have been used and validated for the prediction of both all-cause mortality and MACEs in patients with acute myocardial infarction45, nutritional status was not taken into consideration. An observational study has shown enhanced accuracy in predicting long-term outcomes in individuals with ACS by combining three nutritional scores, namely the CONUT, NRI, and PNI scores, with the GRACE risk score6. Similarly, another study demonstrated that a combination of PNI and GRACE score significantly improved the prediction of long-term mortality in patients undergoing coronary interventions for ACS16. However, the results of most studies have been derived from a limited number of participants with heterogeneous characteristics46. Therefore, although patients with CAD in a poor nutritional status might generally have a worse prognosis29, there is no pooled evidence showing the sensitivity of these indices for the prediction of long-term outcomes in this patient population. Our meta-analysis is the first to investigate the association of a low PNI with the risk of all-cause mortality as well as MACEs/MACCEs.In addition to PNI, risk assessment scores, including the Geriatric Nutritional Risk Index (GNRI), CONUT score, Nutritional Risk Index (NRI), Subjective Global Assessment (SGA), and Nutritional Risk Screening, have been introduced to predict the outcomes of patients diagnosed with CADThe current meta-analysis has several limitations that deserve consideration. First, our analysis was based solely on observational studies, which inherently carry a risk of bias and confounding factors. The lack of randomized controlled trials may limit the strength of our conclusions and warrants caution when interpreting the results. Second, the severity of myocardial injury varied among individual studies, with four and three focusing on STEMI and NSTEMI, respectively, while all the others did not mention the type of MI in their participants. Because of the limited number of studies, subgroup analysis was not conducted to investigate the relationship between low PNI and mortality based on the severity of myocardial injury. Third, despite the identification of advanced age, diabetes, and high GRACE risk scores at baseline as risk factors for long-term mortality in patients with ACS in the current meta-analysis, their predictive values may be weak because of the limited number of studies that provide relevant data for the estimation of effect size. Fourth, while we attempted to address potential confounders by collecting adjusted data from studies that provided both unadjusted and adjusted estimates, residual confounding may still exist because of unmeasured or unknown variables across the included studies. For example, other confounding factors, such as smoking, family, and drug history were not included. Fifth, active infection may have a potential influence on PNI, albumin and lymphocyte levels. In the current meta-analysis, six studies did not explicitly mention the exclusion of patients with active infections. Consequently, there is uncertainty regarding whether patients with infections were included in their study cohorts, which may have introduced potential confounding factors. Finally, although combining the conventional risk scores  and malnutrition may help differentiate ACS patients who are at high risk of mortality from MACEs/MACCEs, the feasibility of such a combination approach was not evaluated in the current meta-analysis because of a lack of relevant information in individual studies.This meta-analysis showed that patients with a low PNI who underwent coronary interventions had an elevated risk of long-term mortality and MACEs/MACCEs. In addition, other risk factors, namely advanced age, diabetes, and high GRACE risk scores, were correlated with elevated long-term mortality in patients with ACS, while a high body mass index was associated with a reduced risk of all-cause mortality. The results of our meta-analysis provide clinical practitioners with an additional tool for assessing the risks of patients with ACS, going beyond conventional cardiovascular risk factors. PNI showed potential as a straightforward and readily available prognostic indicator, facilitating risk stratification and guiding personalized patient management strategies. To reinforce the evidence base and achieve a more comprehensive understanding of the role of PNI in ACS outcomes, further studies, including randomized controlled trials, are required.Supplementary Information.


When meta-analyses whose primary reports included only randomized controlled trials were pooled, there was no significant association between Vit-D intake and cancer risk . In subgroup analysis, Vit-D consumption was associated with a significant decrease in colorectal and lung cancer incidence . Taken together, both Vit-D intake and higher 25(OH)D levels may provide remarkable benefits in terms of cancer incidence and mortality; however, careful evaluation according to cancer types is critically important and recommended.It is a well-established fact that inadequate Vitamin D (Vit-D) levels have negative effects on the development and progression of malignant diseases, particularly cancer. The purpose of this paper was to elucidate the effects of Vit-D intake and serum 25-hydroxyvitamin-D (25(OH)D) levels on cancer incidence and mortality, the current evidence in this field, and the biases of this evidence, using the meta-meta-analysis method. Meta-analyses focusing on Vit-D intake, serum 25(OH)D levels, and cancer risk/mortality were identified. A structured computer literature search was undertaken in PubMed/Medline, Web of Science (WoS), and Scopus electronic databases using predetermined keyword combinations. Primary and secondary meta-meta-analyses were carried out, combining odds ratios (ORs), risk ratios (RRs), and hazard ratios (HRs) for outcomes reported in selected meta-analyses. A total of 35 eligible meta-analyses (59 reports yielded from these studies) assessing the association between Vit-D and cancer incidence and/or mortality were included in this study. In the pooled analysis, higher Vit-D intake and serum 25(OH)D levels were associated with lower cancer risk : 0.90–0.96,  Cancer, which is a complicated group of malignant disorders characterized by abnormal cell proliferation and an uncontrolled cell cycle, remains a major cause of death globally, regardless of human development levels, in countries all over the world ,2,3,4. AVitamin D (Vit-D) was identified as a pro-hormone that provides a range of health benefits, from bone health to immune function, and plays critical roles in biological processes in human metabolism ,7. It isp > 0.05). Similarly, two recent meta-analyses evaluating Vit-D intake and cancer risk reported that Vit-D intake did not decrease the overall cancer incidence  . Se. Se28]. The Risk of Bias in Systematic Reviews (ROBIS)  29] too too29] t® to systematically document key qualitative and quantitative data from the incorporated studies.Primary and secondary meta-meta-analyses were carried out combining OR, RR, and HR for outcomes reported in selected meta-analyses. Initially, an analysis was performed that summarized all existing data into a single pooled estimate. After initial pooling, subgroup analyses were executed to evaluate the heterogeneity of outcomes and to examine the effects of Vit-D intake and serum 25(OH)D status in different cancer and study types. Pooled effect sizes (ES) and ORs, RRs and/or HRs were calculated at 95% confidence intervals (CI) for all groups in primary and secondary meta-meta-analyses. A predefined spreadsheet was created using Microsoft Excelp < 0.10) test [p < 0.05) and I2 statistics . The I2 statistics describe the observed percentages based on the variance in the true effects. In the assessment of I2 values, a result of 25% indicated low heterogeneity, 50% indicated moderate heterogeneity, and 75% indicated high heterogeneity, adhering to established conventions in the field of evidence synthesis [p < 0.05 level. Meta-meta-analysis statistical calculations were performed employing Prometa3® [Egger’s linear regression asymmetry  test , schemat10) test , which p10) test . The hetynthesis . In the rometa3® , along wrometa3® , followiThe robustness of the outcomes was evaluated through sensitivity analyses. In the sensitivity analyses, each individual study was excluded separately from the pooled analysis to assess its impact on the overall results, and then the change in ES was examined. Studies reporting outliers are identified by this method. When necessary, these studies are excluded from the pooled analysis and the confidence intervals are strengthened.A graphical representation in the form of a bubble chart was generated for each systematic review, allowing for a visual depiction of the scientific evidence and facilitating an understanding of the information. The review information was structured and illustrated using a three-dimensional approach as follows:1. Study population (bubble size and bubble color): The size of each bubble is structured to be directly proportional to the sample size of the original studies included in each of the systematic reviews. Moreover, studies with a relatively large sample, studies with a medium sample, and studies with a relatively small sample were colored separately.2. Impact (x) axis: The meta-analyses were categorized and organized based on their respective publication years, providing a chronological framework.3. Strength of results (y-axis): The structure of the analysis was based on the number of primary studies included in each review, providing a quantitative representation of the research encompassed by each study.n = 399), Scopus (n = 567), and WoS (n = 326)), and 184 of these studies were removed without review due to duplicate records. After the duplicate records were removed, the studies (n = 1108) yielded were evaluated by examining the titles and abstracts. In this preliminary review, 1067 ineligible pieces of research were excluded from the study. The full texts of 49 papers were evaluated in detail, including 41 articles in the main search and 8 articles in the citation search. After all reviews, 59 reports from 35 papers [A total of 1292 papers were identified in the preliminary scans of the relevant databases  , and analyses were conducted utilizing the random effects model. The study reports did not demonstrate any evidence of publication bias, as indicated by the results of Egger’s linear regression asymmetry test  and Begg and Mazumdar’s rank correlation test   a. Signif= 0.207) b. The rep < 0.001) . Hence, the meta-meta-analysis was conducted employing the fixed effects model. The evaluation of the funnel plot did not demonstrate any evidence of publication bias among the included studies in the analysis  a. The heanalysis b. The sep < 0.001) . Therefore, analyses were executed utilizing a random effects model. The study reports showed no evidence of publication bias based on the results of Begg and Mazumdar’s rank correlation test  D levels and cancer risk found that higher serum 25(OH)D levels were associated with lower cancer risk  a. Consid= 0.384) b. The se= 0.384) . p < 0.001). However, among the studies included in the analysis, a meta-analysis [p = 0.059) and Begg and Mazumdar’s rank correlation test  suggested that there may be publication bias in a study’s report. Therefore, this study [p < 0.001), as depicted in df = 6, I2 = 21.7%, p = 0.263), and the meta-meta-analysis was performed using the fixed effects model. The study reports showed no evidence of publication bias, as indicated by the results of Egger’s linear regression asymmetry test  and Begg and Mazumdar’s rank correlation test  D levels and cancer-related mortality, it was found that higher serum 25(OH)D levels were associated with a 33% reduction in mortality  b. The roIn order to measure the sensitivity of the analyses and the robustness of the results, subgroup analyses were carried out in terms of Vit-D intake (low and high intake) and serum 25(OH)D levels (low and high levels). p = 0.300) . The relationship between Vit-D intake and cancer mortality was evaluated with data from a total of seven reports. Accordingly, it was concluded that Vit-D intake was associated with a significant reduction in total cancer mortality .In the secondary meta-meta-analyses, subgroup analyses were performed according to study types  and cancer types. Meta-meta-analyses were conducted if there were at least three studies for different cancer types in the subgroup analyses. Accordingly, in the pooled analysis of studies evaluating Vit-D intake and total cancer risk, it was observed that Vit-D intake did not cause a remarkable change in cancer risk  . In subgp = 0.178). In colorectal cancer, the analysis results strongly suggested that higher serum 25(OH)D levels were associated with a lower risk of colorectal cancer  D levels and two specific types of cancer. As seen in < 0.001) .p = 0.320). However, there was a significant association between Vit-D intake and an 11% reduction in cancer-related mortality  as shown in Meta-analyses whose primary reports included only RCTs were also pooled in subgroup analyses. Accordingly, there was no significant association between Vit-D intake and cancer incidence  axis. The y-axis indicates the number of primary studies that were selected and included in the related meta-analyses. Studies with relatively large samples, studies with medium samples, and studies with relatively small samples are colored separately. The bubble chart associated with the mapping of the meta-analysis of 32 from 35 studies on Vit-D is presented in It is established that Vit-D deficiency and inadequate serum 25(OH)D levels are important risk factors for many cancers ,12,13,14p > 0.05; RR = 0.98, 95% CI: 0.94–1.02, p > 0.05; RR = 0.99, 95% CI: 0.93–1.06, p > 0.05) [p < 0.05; OR = 0.96, 95% CI: 0.93–0.98, p < 0.05). Boughhanem et al. [p < 0.05), while this association was not confirmed in prospective cohort studies . Similar to these current meta-meta-analyses, we found no significant difference between Vit-D intake and total cancer risk in pooled analyzes of RCTs in our study . However, in a pooled analysis of observational studies, intake of Vit-D was associated with a 10% lower risk of cancer .The most recent meta-analyses ,36,48,58 > 0.05) ,20,57. I > 0.05)  and Lopem et al. , on the p > 0.05). Similarly, two recent (2022) meta-analyses evaluating Vit-D intake and cancer risk suggested that Vit-D intake did not reduce the overall cancer incidence  [p < 0.05; RR = 0.81, 95% CI: 0.71–0.93, p < 0.05, respectively). Similarly, in many meta-analyses that included observational epidemiological studies, high Vit-D intake or high serum 25(OH)D levels have been associated with a reduced risk of several types of cancer, such as colorectal [p < 0.001). However, when only meta-analyses of RCTs were included in the pooled analysis, there was no significant association between Vit-D intake and cancer incidence. The majority of the studies included in our research (77.1%) were also observational studies. Therefore, based on these findings, it can be inferred that these results can be attributed to the data gathered from observational studies included in this research.The results of current primary studies and meta-analyses regarding serum 25(OH)D levels and Vit-D intake have revealed conflicting reports. In particular, meta-analyses focusing on RCTs have reported no remarkable evidence of a significant association between Vit-D intake and cancer. For example, in a meta-analysis of RCTs by Goulão et al.  that inv > 0.05) ,20. Cont > 0.05)  in 2019 lorectal ,14,21, llorectal , ovarianrecent 20 meta-analorectal ,24. Similorectal ,55,58,60lorectal ,46,48. SAnother critical issue to address and discuss is the investigation of the reasons behind the discrepancies in findings observed between RCTs and observational studies. One considerable reason for the differences is that the primary endpoint in most of the primary studies included in the meta-analyses of RCTs did not focus on cancer incidence or cancer-related death. Furthermore, another contributing factor to the discrepancies between RCTs and observational studies may be that the participants included in the RCTs were not specifically selected from groups known to have a higher risk of Vit-D deficiency. Hence, due to the absence of participants specifically at higher risk for Vit-D deficiency in the RCTs, a notable effect of Vit-D intake may not have been observed in this group. Additionally, the differences in the specific dosing protocols employed in RCTs versus observational studies contribute to the differences between the findings of these two types of studies. Furthermore, another significant factor is that the majority of RCTs did not measure serum 25(OH)D levels at the conclusion of the study to evaluate the actual impact of Vit-D. Therefore, it is crucial to thoroughly consider and take into account these confounding factors when interpreting and comparing the results comparing RCTs and observational studies.p < 0.001). This result also suggested that serum 25(OH)D levels are a better indicator for cancer risk. A total of seven meta-analyses assessing serum 25(OH)D levels and cancer-related mortality were pooled and analyzed. Accordingly, the results of the analysis revealed that higher serum 25(OH)D levels were associated with 26% lower mortality . Similarly, in a pooled analysis of a total of eight meta-analyses evaluating Vit-D intake and cancer-related mortality, higher Vit-D intake was associated with 11% lower mortality . These results also confirmed that serum 25(OH)D levels are a better indicator for cancer-related mortality.In a pooled analysis of a total of 18 reports evaluating serum 25(OH)D level and cancer risk, we observed that higher 25(OH)D levels were associated with lower cancer risk , whereas Vit-D intake was associated with a significant decrease in cancer risk in colorectal and lung cancer . Our results are compatible with the literature [In subgroup analyses, it was found that Vit-D intake did not significantly reduce or increase total cancer risk  and reassessing analyses with increased power. It also simplified the researcher’s task of evaluating these studies together, as it gathered the meta-analyses examining Vit-D intake, serum 25(OH)D levels, and cancer risk/mortality under one umbrella. Although this paper provides valuable evidence, it has several limitations that are worth considering. One limitation of this paper is the possibility of variations in patient selection and treatment protocols across the primary studies included in the meta-analyses. This could lead to heterogeneity across the studies, potentially affecting the overall conclusions. Another limitation of this investigation is the lack of an evaluation of the impact of the treatments received by cancer patients. The effect of treatments, such as chemotherapy and radiation therapy, on the relationship between Vit-D intake and cancer mortality, was not considered. Furthermore, the primary reports included in the meta-analyses within this study selected patients from various countries and geographical regions, which could lead to variations in Vit-D status and cancer incidence/mortality rates due to differences in diet, lifestyle, and other factors. This could impact the generalizability of the study’s conclusions to different populations.In conclusion, this meta-meta-analysis of meta-analyses provided strong evidence indicating a significant association between Vit-D intake and serum 25(OH)D levels with cancer incidence and mortality. Taken together, both Vit-D intake and higher 25(OH)D levels may provide significant benefits in terms of cancer incidence and mortality, but careful evaluation on the basis of cancer types is recommended. Furthermore, it is crucial to implement accurate confounding controls in future research, particularly RCTs. Future research should place emphasis on enhancing study designs, incorporating larger sample sizes, implementing more precise confounding controls, and exploring the potential dose–response relationship between Vit-D intake and oncology outcomes. Continual evaluation of the evidence is critical in assessing the changing epidemiological landscape in studies of Vit-D and cancer, as well as in providing a solid basis for medical guidelines and clinical decision-making. The findings of this study may provide a solid basis for individual decision-making regarding Vit-D in the context of cancer.


Firefighting is a hazardous occupation that is associated with an increased risk of select cancers. The number of studies has grown in recent years allowing for a synthesis of findings.Following PRISMA guidelines, multiple electronic databases were searched to identify studies on firefighter cancer risk and mortality. We computed pooled standardized incidence risk (SIRE) and standardized mortality estimates (SMRE), tested for publication bias, and conducted moderator analyses.Thirty-eight studies published between 1978 and March 2022 were included for final meta-analysis. Overall, cancer incidence and mortality were significantly lower for firefighters  compared to the general population. Incident cancer risks were significantly higher for skin melanoma , other skin cancers , and prostate cancer . Firefighters showed higher mortality for rectum , testis , and non-Hodgkin lymphoma . There was evidence of publication bias for SIRE and SMRE estimates. Some moderators explained variations in study effects, including study quality scores.Firefighters are at higher risk for several cancers; to the extent that some  are screening amenable, more study into firefighter-specific recommendations for cancer surveillance is needed. Moreover, longitudinal studies with more detailed data on the specific length and types of exposures are necessary, as well as on unstudied subtypes of cancers  are needed. Firefighting is a hazardous occupation that is associated with an increase in the risk of select cancers. Hazards include direct and indirect exposure to known and suspected carcinogens. Firefighters may inhale, ingest, or have skin contact with known carcinogens such as polycyclic aromatic hydrocarbons (PAH) and benzene . ExposurAlthough numerous studies have been conducted, generalizable and comparative assessments are complicated by considerable variations in study design, time period, geographic location, measurement of exposure, definition of firefighter roles, and classification of cancer diagnoses, among other study characteristics. Further complications may arise from small sample sizes and time-related variables such as changes in safety regulations and types of firefighter exposures. Due to these challenges faced by primary researchers, meta-analysis has been used as a valuable tool for understanding the overall relationship between firefighting and cancer and further delineates the differential (or moderating) effects.However, previous meta-analyses on this topic reveal mixed findings. For example, LeMasters et al.  found fiAdditionally, chronological and geographical overlap in participants was found across firefighter cancer studies, demonstrating the dependency issues in study effects when conducting meta-analysis. The Jalilian et al.’s  meta-anawww.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42019110520.Lastly, a number of new studies examining firefighter cancer risk and mortality have been published since the Jalilian et al.’s  and Sotevia EBSCO. Second, we performed citation searches using various online search engines including Embase, Web of Science Core collection, Google Scholar, and SCOPUS. Third, we searched multiple websites including government, cancer registries, and the Cochrane Library. Keywords being used in all our searches are a combination of the following terms:  & . All Mesh terms used in our searches can be found in Appendix 1. Two independent reviewers were responsible for determining if studies were eligible with a third author confirming any discrepancies in whether a study met eligibility criteria.Relevant studies were located by searching multiple sources. First, a series of comprehensive electronic searches were conducted using multiple databases including ERIC, PsychINFO, ProQuest Dissertation & Theses, PUBMED, and MEDLINE To be included in the current meta-analysis, a study must meet the following inclusion and exclusion criteria, including:A study must be empirical and quantitative;A study must be based on human research;A study population must be firefighters;A study must be related to firefighters’ cancer incidence or mortality;A study must be written in English;A study must provide cancer incidence and/or mortality from firefighters that are largely geographically and chronologically independent from those included other studies;The study comparison group must be the general population A study must report sufficient statistics that enable us to compute effect size and its associated standard error.in situ cases were excluded in data analyses (6), source of occupation designations  (7), type of incident that firefighters attended (8), sample characteristics , and (9) study characteristics . The two coders independently read the included studies and extracted study information from the 38 studies included in the meta-analysis based on the final coding instrument through REDCap (see Appendix 2 for REDCap coding sheet). Intraclass correlation (ICC) calculated for each category indicated good to excellent level of inter-coder reliability, yielding a range from .73 (type of research design) to 1.00 (study location). Any discrepancies discovered in the coding stage were corrected based on the additional review by the first author before data analysis.Each study initially considered for the present meta-analysis was reviewed and coded, including (1) design characteristics  (2), outcome type  (3), cancer coding system  ICD-8, ICD-9, ICD-10, International Classification of Disease for Oncology (ICD-O), ICD-O-2, ICD-O-3, Surveillance, Epidemiology, End Results (SEER) codes, and others) (4), cancer sites (5), whether The primary effect size measures used in the current meta-analysis were (1) standardized incidence ratio (SIR) and (2) standardized mortality ratio (SMR) depending on study designs used in the primary studies. We calculated pooled incidence risk estimates (SIRE) and mortality risk estimates (SMRE) as described below.First, the reported SIR value was directly extracted from each study. When it was not reported, the SIR value was computed by dividing the observed number of firefighters with cancer by the expected number of the reference population with cancer. The computed SIR value was transformed to its logarithm by taking the log of the computed SIR value, whose standard error value was computed by taking a square root of 1/E1 + 1/E2, where E1 and E2 are the expected frequencies of firefighters and reference population with cancer. If only 95% confidence intervals around the reported SIR value are given, the standard error was computed using: (UL – SIR)/1.96, where UL is an upper level of 95% confidence interval and SIR is the reported SIR value.Second, the reported SMR value and its associated standard error were directly extracted from each study. When it was not reported, the SMR value was computed by dividing the observed number of firefighters’ mortality due to cancer by the expected number of the reference population’s mortality due to cancer. The computed SMR value was transformed to its logarithm by taking the log of the computed SMR value, whose standard error value was computed by taking a square root of 1/O, where O is the observed number of firefighters’ mortality due to cancer. If only 95% confidence intervals around the reported SMR value are given, the standard error was computed using: (UL – SMR)/1.96, where UL is an upper level of 95% confidence interval and SMR is the reported SMR value.e) to the power of the estimates.All the parameter estimates  computed in the meta-analysis were transformed back to the original scale by taking exponential : Begg and Mazumdar’s rank correlation test  for funnAs many studies reported effect sizes in relation to multiple cancer sites, more than one effect sizes were extracted from a single study, leading to the violation of independence assumption for the meta-analysis . Before Two content experts (first and last authors) independently rated 38 studies using the Risk of Bias and Precision of Observational Studies (RTI) item banks and Newcastle-Ottawa Quality Assessment Scale (Newcastle-Ottawa). These scales were examined by the independent reviewers on a sample of studies not included in the final analysis to ensure consistent assumptions and criteria were employed. Slight modifications were then made to the original quality assessments to better align with the methods of the studies evaluated, and some items were removed that were not relevant. Then, the Many-facet Rasch Measurement Model (MFRM) was used to estimate the latent quality score of each assessment, which is expressed on a standard score (z-score) with a mean of 0 .totalQ under the assumption that all total number of effects (k) were from the sample population. If totalQ was found to be statistically significant, the overall effect was estimated under the random-effects model, where between-study variance was estimated using Restricted Maximum Likelihood (REML) estimation method  were performed to identify source of variability in SIRs or SMRs. In particular, the mixed-effects model with a categorical predictor was adopted when a within-study variation (withinQ) is found to be statistically significant after controlling for the moderator. When the mixed-effects model was used, the additional between-study variance after controlling for moderator was estimated using the REML method and then incorporated. Otherwise, the fixed-effects analysis with a categorical predictor was performed. In these moderator analyses, the significant modelQ suggests that study effects  significantly differ depending on subgroups. Moderators used in the current meta-analysis include (1): cancer sites (2), whether in situ cases were excluded in data analyses (3), participant characteristics , and (4) study characteristics . More details about random-effects or mixed-effects model can be found in Raudenbush  (2), cancer coding system (3), cancer sites (4), whether in situ cases were excluded in data analyses  (5), source of occupation designations  (6), type of incident that firefighters attended  (7), participant characteristics , and (8) study characteristics .A total of 38 independent studies published between 1978 and 2022 were coded in a number of study characteristics including (1): outcome type  and SMR . Therefore, we have some evidence supporting the potential publication bias in the included studies for both SIRE and SMRE.k = 20, 95% CI: 1.08 - 1.21), other skin cancers , and prostate cancer  when compared to the reference population. However, no significant differences in standardized incidence rates were found for other cancer sites between firefighters and the reference population. Also, incidence rates were significantly lower among firefighters for esophagus , liver , larynx , lung , colorectal , lymphatic and hematopoietic tissue , and all cancers . No other significant differences in standardized incidence rates were found for other areas of cancer site between firefighters and reference groups.k = 10, 95% CI: 1.02-1.36), testis  and non-Hodgkin lymphoma , when compared to the reference population. Also, mortality rates were significantly lower among firefighters for all cancers , stomach , colon , liver , larynx , bone , brain , Hodgkin’s disease , lip, oral cavity, and pharynx , lymphatic and hematopoietic tissue . However, no significant differences in standardized mortality rates were found for other cancer sites between firefighters and reference groups.modelQ(1) = 27.91, p <.01), 2) whether studies included female participants or not (modelQ (1) = 19.61, p <.01), 3) whether patients with non-malignant tumors were included or not (modelQ (1) = 37.61, p <.01). First, the pooled estimate of SIRE was found to be significantly increased by 29% when quality score rated using Newcastle-Ottawa Quality Assessment Scale was increased by 1 . Second, the pooled SIRE for males was significantly lower than those for females . Third, SIRE was significantly lower when participants with non-malignant tumors  were included .Results from the mixed-effects model suggest that several moderators were found to explain variations in SIREs. Significant moderators include: 1) quality score rated using Newcastle-Ottawa Quality Assessment Scale (modelQ (1) = 66.70, p <.01), 2) whether studies included female participants or not (modelQ(1) = 11.58, p <.01) and 3) study location (modelQ(1) = 11.16, p <.01). First, the pooled estimate of SMRE was found to be significantly increased by 55% when quality score rated using Newcastle-Ottawa Quality Assessment Scale was increased . Second, the pooled SMRE for males was significantly higher than those for females when compared to general population . Third, the pooled SMRE extracted from non-US studies  was significantly higher than those from US studies .Results from the mixed-effects model suggest that several moderators were found to explain variations in SMREs. Significant moderators include: 1) quality score rated using Newcastle-Ottawa Quality Assessment Scale . Other skin cancer incidence rate was also significantly higher in firefighters . Firefighters are exposed to a number of carcinogens associated with melanoma and/or other skin cancers including polycyclic aromatic hydrocarbons (PAHs), Polychlorinated Biphenyls (PCBs), and benzene . Often wIn the present meta-analysis, incident prostate cancer was significantly higher in firefighters  while mortality was similar to that of the general population . Of note, studies in other populations have documented associations with PAH, PCB, and heavy metal exposures with prostate cancer risk . MoreoveIn the present meta-analysis, incident rectal cancer was not significantly higher in firefighters  while there was significantly increased risk of death due to rectal cancer . Other investigators have suggested that there is a possible association between rectal cancer mortality and firefighting , howeverIn the present meta-analysis, incident testicular cancer was not significantly higher in firefighters  while there was a significantly higher risk of death due to testicular cancer . Firefighters are exposed to Polychlorinated Biphenyls and Polybrominated Biphenyls (PCBs) ; howeverThe present meta-analysis suggests lower risk  for non-Hodgkin lymphoma among firefighters  while a significant increased risk of death was observed on the basis of just two pooled studies . Again, some caution is required to interpret our findings given discrepancies in the pooled effects for incidence and mortality. There is “limited” evidence from studies of non-Hodgkin lymphoma risk to support the Group 1 designation , conductIn the present meta-analysis incident brain and central nervous system cancers were not significantly higher in firefighters  while there was a significant increased risk of death due to this heterogeneous group of cancers . This cancer grouping is characterized by a large number of histologically distinct subtypes, only a subset of which may be associated with firefighting-related occupational exposures , 42. LeaPrevious meta-analytic studies of firefighter cancer risk either did not complete formal moderator analyses or conducted analysis with a limited number of variables. Uncovering sources of variability in study effects  can be useful for researchers in that it will enhance the interpretability and generalizability of meta-analytic results, which is estimated based on more consistent study effects. In this meta-analysis, we identified several moderators that explained considerable amount of between-study variability in effects. Jalilian et al.’s documented evidence of moderate to strong heterogeneity for several site-specific cancers including buccal cavity and pharynx, brain and nervous system, esophagus, larynx, lung, melanoma, skin, prostate, and kidney .Not only have we expanded the number of moderator variables examined, but also, we undertook a comprehensive assessment of study quality as a moderator using two quality assessment tools. Soteriades et al.’s meta-analysis included a smaller number of studies and did analyses categorized by level of study quality . Such subgrouping presumably reduced heterogeneity in effects, but at the expense of the number of studies included in their subgroup analyses across specific cancer sites. For analyses based on “good studies”, the number of studies ranged from 1 to 14 for cancer incidence, and from 2 to 24 for cancer mortality. We found that study quality ratings using the Newcastle-Ottawa Quality Assessment Scale explained variations in SIRE and SMRE estimates, suggesting that SIRE and SMRE estimates are likely to be higher as study quality score is increased. Careful consideration of optimal future study designs examining firefighter cancer risk is needed to capture risk levels more accurately in this occupational group.The identification of other important moderators helps researchers to give careful consideration to the optimal design of future firefighter cancer studies  as well as help to contextualize the present meta-analysis findings. For instance, our moderator analyses also found significantly lower pooled cancer incidence effects for males than females, while pooled cancer mortality was higher for males than females, when compared to general population. One possible explanation for these differential effects is that the proportionately smaller number of female firefighters, when included in select individual studies, resulted in large, but unstable effect size estimates in incidence studies, while lower pooled effects in female mortality studies could reflect differences in aggregate lifetime carcinogenic exposures since women started joining the workforce only in recent decades in the US and elsewhere . CautionTwo meta-analyses conducted by independent research teams were published in 2019 , 8. TherOverall, there was some agreement for an increased risk of several cancers across the two meta-analyses as well as findings from the present analysis. For example, pooled SIRE estimates for incident prostate cancer were significantly higher in previous two meta-analyses, which ranged from 1.09 and 1.20. The range of pooled SMRE estimates for non-Hodgkin lymphoma mortality was significantly higher than general population in all three meta-analyses, which ranged from 1.20 to 1.44. Finally, the range of pooled SMRE estimates for rectal cancer mortality were significantly higher in all three analyses, which ranged from 1.16 to 1.36. Except for the pooled estimate of rectal cancer mortality found in the Soteriades et al.’s meta-analysis (SMR = 1.18 95% CI: 1.02-1.36), our estimates were lowest.Both the present  and Jalilian et al.’s meta-analyses (95% CI: 1.21-1.45) demonstrated significantly higher risk for incident melanoma; Soteriades et al.’s finding was not statistically significant . In contrast, testicular mortality estimate was significantly higher in the present meta-analysis , but not in the Soteriades et al.’s , although the pooled estimates were similar in magnitude. Jalilian et al. did not report a summary estimate for testicular mortality. Brain and central nervous system cancer mortality rates were significantly higher in the present  and in the Soteriades et al.’s meta-analyses , while they were not in the Jalilian et al.’s , although similar in magnitude.k = 12), but fewer in both Jalilian et al.’s (k = 9) and Soteriades et al.’s (k = 7). Also, some of more recent studies that were included in the present meta-analysis showed lower risk testicular cancer incidence.Risk of testicular cancer incidence was not found to be significant in the present analysis  whereas both the Jalilian et al.  and the Soteriades et al. found significantly higher risk . Reasons for such discrepancy are uncertain. No study has considered differences between seminomas and non-seminoma types of testicular cancer. However, more estimates were used in the present meta-analysis  (Determining if elevations in cancer risk documented effects) , 56. In effects)  to the GOther investigators have proposed and applied different frameworks for evaluating the causality or likelihood of cancer risks associated with firefighting that includes some of the following features: 1) consistency of reported epidemiologic findings, 2) assessment of study quality, confounders, misclassification and bias, and 3) consideration of the biologic plausibility of carcinogenic and other chemical exposures as drivers of increased cancer risk , 34, 39.It is therefore important to note that completion of meta-analytic analysis of study findings is just one element of a comprehensive assessment of cancer risk that may be determined to be causally linked to exposures associated with firefighting.Results of the present analysis, combined with the other recent meta-analytic reviews and the recent IARC review clearly document elevated cancer risk in firefighters, supporting the need for additional work identifying and implementing best practices to reduce the carcinogenic exposures which occur during and after fire suppression activities –60. Addivia careful selection of papers with respect to geographic region and years covered was imprecise as we balanced the need for inclusion of otherwise eligible studies against avoiding the inclusion of effect sizes drawn for similar cohorts of firefighters. It was not possible to completely eliminate study overlap so some dependency effects may remain in our analysis.There are study limitations that require some caution for interpretation. First, our analysis included only a small number of studies that estimated the amount of carcinogenic exposure firefighters faced ; but becDespite these limitations, we were able to minimize the inflation of type I error rates that might arise from dependency in effects by undertaking careful inspection of individual study designs for the possibility of dependency in effect sizes. In addition, we performed a variety of moderator analyses to better understand sources of the observed variations . Finally, we carefully investigated all included studies and selected the most independent study effects to avoid overlap with respect to geographic region and years covered by each study.Despite differences between our study and others, our results reinforce the associations between firefighting and cancer. This occupational group faces many unique hazards and exposures, and more research employing high-quality study designs, such as the ongoing National Firefighter Registry  and the The original contributions presented in the study are included in the article/All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Pancreatic cancer is a globally frequent cause of death, which can be caused by many factors. This meta-analysis was performed to assess the correlation between pancreatic cancer and metabolic syndrome (MetS).Publications were identified by searching PubMed, EMBASE, and the Cochrane Library for studies published until November 2022. Case-control and cohort studies published in English that provided information on the odds ratio (OR), relative risk (RR), or hazard ratio (HR) of metabolic syndrome and pancreatic cancer were included in the meta-analysis. Two researchers separately retrieved the core data from the included Random effects meta-analysis was conducted to summarize the findings. Results were presented as relative risk (RR) and 95% confidence interval (CI).P<0.001), and gender differences were also observed . Moreover, an increased risk of developing pancreatic cancer was strongly linked to hypertension, poor high-density lipoprotein cholesterol, and hyperglycemia . However, pancreatic cancer was independent of obesity and hypertriglyceridemia .MetS showed a strong association with an increased risk of developing pancreatic cancer (RR1.34, 95% CI1.23–1.46, Although further prospective studies are required for confirmation, this meta-analysis indicated a strong relationship between MetS and pancreatic cancer. Regardless of gender, a greater risk of pancreatic cancer existed in people with MetS. Patients with MetS were more likely to develop pancreatic cancer, regardless of gender. Hypertension, hyperglycemia, and low HDL-c levels may largely account for this association. Further, the prevalence of pancreatic cancer was independent of obesity and hypertriglyceridemia.https://www.crd.york.ac.uk/prospero/, identifier CRD42022368980. HowePubMed, Embase, and the Cochrane Library databases were systematically searched for pertinent studies that were published between the creation of the database and November 1, 2022. The following search terms were used: (‘pancreatic carcinoma’ OR ‘pancreatic cancer’ OR ‘pancreatic adenocarcinoma’ OR ‘pancreatic neoplasms’) AND (‘metabolic syndrome’ OR ‘Metabolic X Syndrome’ OR ‘Dysmetabolic Syndrome X’ OR ‘MetS’). Furthermore, the reference lists of qualified articles were visually examined for any additional pertinent studies.Based on the inclusion and exclusion criteria listed below, two researchers screened the retrieved publications independently, and discrepancies were settled by consensus. The following inclusion criteria were applied: (1) the publication that was written in English and was a cohort study or a case-control study; (2) data on the relative risk (RR), odds ratio (OR), or hazard ratio (HR) with a 95% confidence interval (95%CI) were available; (3) when multiple publications were produced from the same data, only the most comprehensive paper was selected.Exclusion criteria for this study were as follows: (1) letters, case reports, reviews, expert opinions, or editorials were excluded; (2) excluded if they lacked critical data; (3) excluded if they failed to mention MetS and diagnostic criteria for PC explicitly; or (4) they were duplicates of other studies. Additionally, case-control studies were excluded from the meta-analysis but included in the systematic review.The Newcastle-Ottawa Scale (NOS) for quality evaluation of cohort studies and case-control studies was used to independently evaluate study quality . The NOSThe names of the first authors, the year the study was published, the country where the investigation was done, the duration of follow-up, the total number of patients, and the criteria for the definition of MetS were all retrieved separately by the two researchers for each study that was accessible. Using the most adjusted model, we derived the pooled risk estimates and associated 95%CIs. A discussion was used to settle any disagreements. To assess the effects of MetS components on the risk of developing PC, risk estimates were also gathered for each individual MetS component.2 statistic was used. Low, moderate, and high levels of heterogeneity were estimated to be 25%, 50%, and 75%, respectively. To assess publication bias, the Egger test and funnel plotting were performed. When at least ten original publications were included, a P value < 0.05 showed publication bias. STATA (version 16.0) was used for conducting all analyses, and statistical significance was established at P< 0.05.Using pertinent risk estimations, the relative risks (RR), hazard ratios (HRs), incident rate ratios, standardized incidence ratios (SIRs), and their 95%CIs were employed to evaluate the relationship between MetS and PC risk. From the multivariable models of the original studies, adjusted risk estimates were generated. Additionally, we assessed how each component of the metabolic syndrome affected the risk of PC on an individual basis. Sensitivity analysis was also carried out to test whether any of the studies had shown a significant impact on the outcome. Using the random-effects model, the outcomes of the retrieved papers were combined. In order to evaluate the statistical heterogeneity across studies, the IA complete summary of the fundamental characteristics of each study that was included in this research is provided in P<0.0001, I2 = 38.8%)     can boost PC cell invasion and proliferation  and VEGF, which were mediated by P38 MAPK. Moreover, elevated hyperglycemia feration . Meta-anferation , which wferation , 29–31, feration . Resistiferation . Therefoferation . This coferation  but not feration  or Singaferation . Asians feration . These oElevated triglyceride levels and reduced HDL-c are the components of MetS. Previous studies on dyslipidemia and the risk of PC produced controversial results , 38, 39.MetS is reversible. In patients with MetS, and the lifestyle-modification intervention was successful. It resulted in easing the condition and decreasing the severity of associated abnormalities  . PreviouHowever, this meta-analysis has some limitations. First, like any other meta-analysis, residual confounding from the original studies cannot be eliminated. After correcting for the majority of significant confounding factors, residual or unknown confounders may persist. Because each trial was adjusted for a unique set of variables, meta-analyses may have been heterogeneous. Second, the comprehensiveness of this study was limited by the relatively small number of pertinent publications, which precluded analyses for other relevant characteristics, including age and ethnicity. Third, the metabolic components were not directly assessed using the same technique, which may result in high heterogeneity between studies. However, the sensitivity analysis and subgroup analysis showed the robustness of our outcomes.In conclusion, our meta-analysis revealed that MetS showed a remarkable correlation with a high risk of developing PC in both genders, with a higher risk in females as compared to males. Low HDL-c levels or hyperglycemia may be primarily responsible for the higher risk of PC in individuals with MetS. However, obesity and hypertriglyceridemia do not increase the risk of PC.The original contributions presented in the study are included in the article/All authors contributed to the study’s conception and design. LZ was in charge of material preparation, data collection, and analysis. SL wrote the first draft of the paper. JFL contributed to the writing, revision, and review of the manuscript. GT reviewed the manuscript. All authors contributed to the article and approved the submitted version.


Stroke represents a prominent global health issue, exhibiting the third highest incidence of disability and a significant burden on both healthcare and the economy. Stress hyperglycemia, an acute reaction of the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system, leading to adverse outcomes and mortality. Several previous studies have indicated that stress hyperglycemia, as evaluated by the stress hyperglycemia ratio (SHR), significantly increases the risk of adverse outcomes and mortality in stroke patients. However, there is a lack of further investigation into the influence of dynamic changes in stress hyperglycemia on the clinical outcomes of acute ischemic stroke (AIS) patients. Consequently, we performed a meticulous analysis, considering dose-response relationships from existing studies, to ascertain the correlation between dynamic changes in stress hyperglycemia and the susceptibility to adverse outcomes in patients with AIS.Q-test. The Newcastle-Ottawa Scale (NOS) tool was employed to evaluate the risk of bias of the included studies.This investigation was prospectively registered in PROSPERO and adhered to the PRISMA guidelines. A comprehensive search was performed across English and Chinese databases. A two-sided random-effects model was employed to consolidate the odds ratios (ORs) of the highest vs. lowest categories of SHR. Restricted cubic spline (RCS) models were employed to estimate potential non-linear trends between SHR and the risk of adverse outcomes in AIS patients. Egger's test was utilized to assess publication bias. Heterogeneity was evaluated using Cochran's I2 = 52.3%, P < 0.001), a 3.11-fold increased risk of 3-month mortality , a 2.80-fold increased risk of 1-year mortality , a 3.90-fold increased risk of intracerebral hemorrhage (ICH) and 4.57-fold increased risk of symptomatic ICH (sICH) , a 1.73-fold increased risk of neurological deficits , and a 2.84-fold increased risk of stroke recurrence . It is noteworthy that, except for hemorrhagic transformation (HT) and stroke recurrence, the remaining adverse outcomes exhibited a “J-shaped” non-linear dose-response relationship.The final analysis incorporated a total of thirteen studies, which were published between 2019 and 2023, encompassing a participant cohort of 184,179 individuals. The SHR exhibited a significant association with the risk of various adverse outcomes. Specifically, a higher SHR was correlated with a 2.64-fold increased risk of 3-month poor functional outcomes (OR: 2.64, 95% CI 2.05–3.41, In summary, our findings collectively suggest that increased exposure to elevated SHR is robustly linked to a heightened risk of adverse outcomes and mortality in individuals with AIS, exhibiting a non-linear dose-response relationship. These results underscore the significance of SHR as a predictive factor for stroke prognosis. Therefore, further investigations are warranted to explore the role of SHR in relation to adverse outcomes in stroke patients from diverse ethnic populations. Furthermore, there is a need to explore the potential benefits of stress hyperglycemia control in alleviating the physical health burdens associated with AIS. Maintaining a lower SHR level may potentially reduce the risk of adverse stroke outcomes.https://www.crd.york.ac.uk/prospero/, identifier: CRD42023424852. Stroke is a major global health issue, being the second leading cause of death and third leading cause of disability worldwide . In 2019In AIS patients, hyperglycemia can be triggered by an acute stress response from the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system . This hyOur prior research has unequivocally demonstrated that a higher SHR is significantly associated with an elevated risk of adverse outcomes, mortality, early neurological deterioration (END), hemorrhagic transformation (HT), and infectious complications, regardless of diabetes history and treatment methods . NonetheThe current study adhered to the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) . AdditioA systematic search of eligible studies was conducted in several databases, including PubMed, Embase, the Cochrane Library, the China National Knowledge Infrastructure (CNKI), Wan Fang, and the Chinese VIP Information (VIP) database. The search encompassed the period from the inception of the databases up until the end of July 2022, with language restrictions set to English and Chinese. It should be noted that, based on our previous study  studies had to be published in a peer-reviewed journal; (b) publication had to be in either English or Chinese languages; (c) the exposure of interest had to be different stress hyperglycemia levels assessed by SHR; (d) the study had to investigate adverse outcomes related to stroke; (e) the availability of odd ratios (ORs) or hazard ratios (HRs) with corresponding 95% confidence intervals (CIs) for different endpoints; (f) the reported results had to be adjusted for relevant covariates. On the other hand, studies were excluded if they were in the form of reviews, letters, commentaries, conference abstracts, or case reports, as they did not meet the criteria for inclusion in the analysis.Two reviewers conducted the data extraction process independently, using a predefined form that included the following information: first author's name, publication year, country, age, sex, number of participants and cases for different endpoints, SHR levels, endpoints, duration of follow-up, and covariates adjusted in the multivariable analysis. If a study reported multiple adjustment models, only the model with the highest number of adjusted covariates was included.Furthermore, the quality assessment of the included studies was performed using the Newcastle-Ottawa Scale (NOS) . The NOSThe 3-month poor functional outcome was assessed by modified Rankin Scale (mRS), and the standard of the scale can be found in the p-values .The NOS tool was used to assess the methodological quality of the included studies, and they all received a median score of 8 stars, with an inter-quartile range ranging from 8 to 9 stars. This indicates that all studies were considered to be of high quality. The detailed assessment of the methodological quality for each study can be found in We first performed a dose-response meta-analysis on SHR's effects on AIS adverse outcomes in all individuals and specifically non-diabetics. RCS models further indicated a “J-shaped” non-linear relationship between SHR and adverse outcomes like poor functional outcomes at 3 months, mortality at 3 months and 1 year, END, HT, and stroke recurrence. However, this trend was not observed for HT and stroke recurrence. Notably, the worst outcomes were most linked to the highest SHR group, as studies often categorized SHR into tertiles or quartiles.Shi et al.  found inVarious equations, such as FGB (mmol/L)/HbA1c (%), have been commonly used to calculate the SHR to assess the relationship between glycemic control and stroke outcomes. However, it is crucial to acknowledge the potential limitations associated with this equation, particularly concerning comorbidities known to affect HbA1c levels, such as hemoglobinopathies or anemia. Comorbid conditions like hemoglobinopathies or anemia can significantly impact HbA1c measurements, rendering the use of the FBG/HbA1c equation less reliable in certain cases. These conditions can lead to variations in HbA1c levels that may not accurately reflect long-term glycemic control. Therefore, caution is necessary when interpreting SHR values in individuals with such comorbidities, as they may result in an overestimation or underestimation of the true association between glycemic control and stroke outcomes. Researchers and clinicians must be aware of these potential confounding factors and consider them when utilizing SHR as a metric to evaluate the relationship between diabetes management and stroke risk. Alternative methods or adjustments may be needed in specific patient populations to ensure a more accurate assessment of glycemic control in relation to stroke outcomes.SHR provides a more precise measure of stress-induced hyperglycemia by adjusting for prior diabetes history and baseline blood glucose levels, thus better indicating disease prognosis , 53. EarThe pathophysiological mechanisms underlying the association between SHR and stroke severity as well as prognosis in patients with acute ischemic stroke are still not fully elucidated. A particular study employed correlation analysis to shed light on this relationship, revealing that higher SHR levels are predominantly linked to increased stroke severity and heightened inflammatory responses upon admission . These fChina, due to its population and rising risk factors, is witnessing a surge in AIS incidence. Multiple studies from China have detailed the relationship between stress hyperglycemia and AIS outcomes , 46–51. While Perez-Vega et al.  indeed dTo the best of our current knowledge, this dose-response meta-analysis represents a pioneering effort in exploring the impact of dynamic fluctuations in stress hyperglycemia on susceptibility to adverse outcomes among individuals with AIS. Our findings unequivocally establish a positive association between the Stress-Hyperglycemia Ratio (SHR) and the risk of adverse outcomes in AIS patients. Furthermore, we have observed a distinct “J-shaped” non-linear dose-response pattern, indicating that elevated SHR is significantly correlated with an increased likelihood of 3-month poor functional outcomes, 3-month and 1-year mortality, as well as neurological deficits. These conclusions are in alignment with prior research, thereby deepening our understanding of the influence of dynamic changes in stress hyperglycemia on the risk of adverse outcomes in AIS patients. In summary, these investigations provide invaluable insights into the intricate relationship between stress hyperglycemia and AIS patient outcomes, underscoring the critical importance of implementing effective glycemic management strategies within this specific population. Further research endeavors are warranted to delve into the complex interplay between glucose control approaches and prognosis among stroke patients originating from diverse ethnic backgrounds and populations.Our study has several limitations that merit consideration. Firstly, a majority of the included studies possessed a retrospective cohort study design, which lacks the advantages of randomized controlled trials, notwithstanding their substantial sample sizes. Secondly, the predominant representation of studies conducted by Chinese researchers limits the generalizability of our findings to other ethnicities and countries. To gain a more comprehensive understanding of the relationship between stress hyperglycemia and adverse outcomes in AIS patients, it is imperative to include studies from diverse populations. Thirdly, the dose-response meta-analysis incorporated only two studies reporting stroke recurrence after AIS, highlighting the urgency for further research focusing on this intriguing theme. Fourthly, the reporting of adverse outcomes exhibited heterogeneity owing to variations in the duration of follow-up among the included studies, which could contribute to the overall heterogeneity observed in the analysis. Lastly, The substantial heterogeneity between stress hyperglycemia and the risk of 1-year mortality and ICH is high, and in principle, performing a subgroup analysis or meta-regression would indeed be an ideal approach to explore potential sources of this heterogeneity. However, due to the limited number of studies included in our analysis, it's not feasible to conduct a robust meta-regression. Insufficient studies could lead to unstable and overly sensitive results in a meta-regression. Nevertheless, despite these limitations, the results of our meta-analysis still offer valuable insights for clinicians when making treatment decisions for AIS patients.In summary, our findings collectively suggest that increased exposure to elevated SHR is robustly linked to a heightened risk of adverse outcomes and mortality in individuals with AIS, exhibiting a non-linear dose-response relationship. These results underscore the significance of SHR as a predictive factor for stroke prognosis. Therefore, further investigations are warranted to explore the role of SHR in relation to adverse outcomes in stroke patients from diverse ethnic populations. Furthermore, there is a need to explore the potential benefits of stress hyperglycemia control in alleviating the physical health burdens associated with AIS. Maintaining a lower SHR level may potentially reduce the risk of adverse stroke outcomes.The original contributions presented in the study are included in the article/Y-WH conceptualized the study. Z-PL and X-SY developed and refined the search strategy. Y-WH and X-SY designed the study. Y-WH drafted the initial manuscript and Z-PL revised it. All authors have made significant contributions to this article and have given their full approval of the submitted version.