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Rickard L. Whether use of antidepressants is related to the risk of developing lower-grade WHO grades and higher-grade WHO grade 4 glioma was investigated in this study. A registry-based case—control study was performed with glioma case patients and age-, sex-, and geographically matched control participants who were diagnosed in Sweden during Conditional logistic regression was used to analyze whether selective serotonin reuptake inhibitors SSRIs or non-SSRIs were associated with the risk of developing lower- or higher-grade glioma in the study population. Our results show that use of antidepressant medication was not associated with the risk of developing glioma. We also performed a meta-analysis in which the data set from the present study was combined with results from 2 previous epidemiologic studies to answer the same questions. In conclusion, it remains possible that antidepressants may have common monoaminergic mechanism s that reduce the risk of developing glioma. Malignant gliomas are a complex and heterogenous group of deadly brain tumors that differ vastly in aspects such as histological grade of malignancy, molecular subgrouping, and metabolic patterns. Depression and antidepressant medications are commonly used in the general population and may be even more common among patients with glioma. The first relevant epidemiologic study to investigate the risk of glioma in relation to depression and its treatment 15 used a sample of patients with glioma and population-based participants and found that use of tricyclic antidepressants TCAs was inversely associated with the risk of developing glioma in a time- and dose-dependent manner. In that study, however, the trend was not statistically significant. Selective serotonin reuptake inhibitors SSRIs were not significantly associated with the risk of developing glioma in any of the studies. Meta-analysis of these 2 studies showed that use of antidepressants was associated with a reduced risk of glioma when all groups of antidepressant medications and all glioma grades 2 , - 4 were entered in 1 analysis. One possible interpretation of existing data may be that associations are global and related to monoaminergic dimensions of the brain biochemical environment. However, the extent to which such observations generalize across study settings and whether they are specific to certain tumor grades or different classes of pharmacological substances remains obscure. To address this issue, we here report further data derived from Swedish national population-based registers on the association, if any, between use of antidepressant medications and glioma incidence, and we add these new data to a new meta-analysis. All data used in this study were obtained from the RISK North database, which links data from national cancer quality registers to demographic and health care registers by using the unique personal identity number every Swedish citizen possesses. The National Quality Registry for brain tumors is a database containing clinical data on patients with brain tumors and is a collaboration between different health care regions in Sweden. The completeness of registration for the National Quality Registry for Brain Tumors varied significantly among the 6 different health care regions in the country. The regions that met this requirement were north, middle, and southeastern regions and the Stockholm-Gotland region. Coverage was validated through comparison with data in the Swedish Cancer Register, to which all cancer cases are to be reported by legal mandate but which does not contain clinical information other than diagnosis. In investigations of differences in risk of developing glioma in northern and southern regions of the country, all non-northern regions were considered southern regions. Cases derived from the database included patients with glioma WHO grades diagnosed between and and were according to the construction of the RISK North database originally identified from the National Quality Registry for Brain Tumors. Included patients were older than 18 years, had a histologically verified glioma diagnosis, and consented to registration in the National Quality Registry for Brain Tumors. No exclusion criteria were used. Control participants derived from the database in the present study included individuals without a glioma diagnosis. Control participants were matched to case patients with regard to age, sex, and geographic region at the time of the glioma diagnosis of the index case matched on calendar time. Information about age and sex of the patients and the control participants was gathered from the Swedish Population register from Statistics Sweden. Because age and sex are the only well-established and common epidemiologic factors besides exposure to ionizing radiation related to development of glioma, matching on other variables was not considered relevant. These patients are included in the descriptive data but not the case—control analyses. Information regarding depression diagnosis was gathered from the Swedish inpatient register from A separate sub-analysis was made for TCAs. Considering that there is evidence suggesting geographic disparities in cancer incidence in Sweden, 23 we also investigated if there was a difference in risk of developing higher- or lower-grade gliomas between northern and southern parts of the country. Last, meta-analyses of antidepressants and the risk of glioma were performed. Depression itself can sometimes be a presenting symptom of glioma 24 ; therefore, patients who were prescribed antidepressants before their glioma diagnosis, in some cases, may already have had prediagnosis symptoms of glioma. We attempted to eliminate this issue by defining exposure to antidepressants in case patients and control participants as at least 1 prescription of antidepressants issued from the start of the Swedish Prescribed Drug Registry in up to 1 year before glioma diagnosis. For control participants, the same principle, as well as method, was used for assessment of exposure to antidepressant medication. Antidepressant exposure and risk of glioma were investigated for 2 main groups: those prescribed an SSRI and those prescribed a non-SSRI antidepressant. We did not exclude individuals from analyses based on exposure to other parallel prescriptions or conditions; thus, individuals with multiple antidepressant medications ie, both SSRIs and non-SSRIs will cause an overlap between groups. Similarly, control participants for 1 type of substance might have been exposed to other substances. The distribution of antidepressants among patients with glioma and control participants is presented in Table S1. A meta-analysis of the risk of developing glioma associated with antidepressants was performed. Citation lists of eligible studies were also searched. These 2 studies, as well as our present study, were included in the meta-analysis see Table S2 for additional characteristics of the studies. All studies included were of good quality when assessed according to the Newcastle-Ottawa Scale 24 , 25 for case—control studies see Table S3 for a detailed assessment of each study. Four meta-analyses were performed. These meta-analyses used up to 10 sets of case—control data from the studies described see Table S4 for further details. The first meta-analysis investigated the risk of developing glioma in relation to antidepressant use in 8 sets of case—control data, which included all data sets from previous studies, as well as data sets investigating SSRI and non-SSRI use that we included in the present study. The fourth meta-analysis investigated TCA use and risk of glioma. A meta-analysis investigating disparities for different tumor grades was not possible because 1 of the studies Walker et al 15 had not included tumor grade. The variables included in the conditional logistic regression were age, sex, geographic region, and calendar time. A subgroup analysis was performed for TCA use. Multivariable unconditional regression was used to test for differences between northern and southern regions of the country. Statistical analyses were performed using R, version 4. The meta-analyses were performed in SPSS, version Effect sizes used in the meta-analyses were gathered from the natural logarithmic value of the OR in each case—control data set. This study was performed in line with the principles of the Declaration of Helsinki. Data on glioma case patients and control participants were included in our study. Of the patients with glioma, The mean total length of prescriptions of SSRIs, according to the data we used, was The mean total length of prescriptions of non-SSRIs in our material was More baseline characteristics for case patients and control participants are listed in Table 1. Baseline characteristics of glioma case patients and control participant in Sweden In our data set, patients with glioma had received SSRI treatment. Among these, 83 patients developed higher-grade glioma and 52 developed lower-grade glioma. The risk of developing higher-grade glioma or lower-grade glioma in relation to SSRI use did not differ between northern or southern parts of the country. Of the patients with glioma who had received non-SSRI treatment, 73 developed higher-grade glioma and 27 developed lower-grade glioma. The risk of developing higher-grade glioma or lower-grade glioma in relation to non-SSRI use did not differ between northern or southern parts of the country. In this subgroup, 14 patients developed higher-grade gliomas and 7 developed lower-grade gliomas. There appeared to be no difference between the northern and southern part of Sweden in terms of developing lower-grade or higher-grade glioma with respect to a depression or anxiety diagnosis. Forest plot showing a meta-analysis, using a random-effects model, of antidepressants and risk of developing glioma in epidemiologic studies in the United Kingdom, Denmark, and Sweden published The x -axis is shown using a log scale. Forest plot showing a meta-analysis, using a random-effects model, of selective serotonin reuptake inhibitors and risk of developing glioma in epidemiologic studies in the United Kingdom, Denmark, and Sweden published Forest plot showing a meta-analysis, using a random-effects model, of nonselective serotonin reuptake inhibitors antidepressants and risk of developing glioma in epidemiologic studies in the United Kingdom, Denmark, and Sweden published Forest plot showing a meta-analysis, using a random-effects model, of tricyclic antidepressants and risk of developing glioma in epidemiologic studies in the United Kingdom, Denmark, and Sweden published In this study, no significant association between the use of antidepressants and glioma incidence was found in any of the subgroups. Several explanations for this global result and for the lack of associations in subgroup analyses are possible. First, the findings may be caused by pharmacodynamic mechanisms common to all or most antidepressant medications, which would, in such cases, most likely involve aspects of monoaminergic transmission. Second, the associations could be a result of methodological or statistical artifacts such as chance findings or confounding. This could be consistent with the fact that findings, albeit significant, were very modest in size. The reason for this is that much of the data were not included in the meta-analyses that took both tumor grade and type of medication into account. Despite the long-standing hypothesis that protective outcome against gliomas may be specific to TCAs, neither our study nor the comprehensive meta-analysis presented here supports this notion. Although a nonsignificant trend toward a decreased risk of glioma in non-SSRI and TCA users was observed in the meta-analyses, we noted moderate heterogeneity in glioma risk among studies. The inherent diversity within glioma subtypes and variations in follow-up duration may have contributed to this heterogeneity. Our findings show different risks associated with non-SSRI and TCA antidepressant use: a higher risk for higher-grade gliomas and a lower risk for lower-grade gliomas, albeit without statistical significance. These findings might be taken to suggest that the variability among glioma subtypes may have implications for the nature of associations between antidepressants and glioma risk. Larger studies with higher resolution with regard to tumor type and substance are needed to further establish whether such a relationship exists. Furthermore, the possibility of protective effects for specific substances, such as fluoxetine, 26 cannot be excluded based on the present data. There are possible mechanistic explanations that, albeit speculative, may make biological sense regarding the negative association between antidepressants in general and gliomas described in the present meta-analysis. Perhaps most important among these is that the mitochondrial enzyme monoamine oxidase A, which is involved in the degradation of monoamines, including serotonin, is inhibited by most antidepressant medications. It may also be noted that there are also possible points of interaction between monoaminergic transmission and gliomas that may be cause for caution in using antidepressant medications in this context. Most important here, from a clinical point of view, may be the influence of serotonin on angiogenesis. This might offer one possible explanation for the paradoxical observation that antidepressants are negatively associated with glioma incidence, whereas use of antidepressants by patients with glioma appears to be negatively associated with survival. The sample size and the national registry—based study design can be considered strengths of the present study. To our knowledge, this study is the first of its kind to investigate higher- and lower-grade glioma separately. Last, our study included our data in meta-analyses and thus enabled investigation of global associations of antidepressants as well as those for specific subgroups. Our study also has several important limitations. For example, we did not account for dose of antidepressants, time used, or the possible confounding of the overlap between SSRI and non-SSRI groups among exposed cases. We chose not to exclude cases of overlap; eg, individuals who used both SSRIs and non-SSRIs in our analyses, in the interest of retaining maximal power in our analyses. This group was included, furthermore, in the interest of maximizing statistical power, broadly defined. However, the fact that we were unable to ascertain that these case patients did not systematically differ from those treated pharmacologically ie, by being less severe , does limit their value as controls, unfortunately. However, more specific associations that may be unique to a specific subcategory of antidepressants or gliomas of a certain level of malignancy could not be demonstrated. One possible explanation for these findings could be that they mirror pharmacological mechanisms common to most or all antidepressants, such as an alteration of the balance of monoaminergic neurotransmitters such as serotonin. From a clinical point of view, the associations seen here are small and may not warrant changes in prescription practices of antidepressant medications. Supplementary material is available at American Journal of Epidemiology online. Distinct metabolic hallmarks of WHO classified adult glioma subtypes. Neuro Oncol. Google Scholar. The World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. The WHO classification of tumors of the central nervous system: a summary. Tumor microenvironment in glioblastoma: current and emerging concepts. Neurooncol Adv ; 5 1 :vdad Monoamines in glioblastoma: complex biology with therapeutic potential. Sarrouilhe D , Mesnil M. Serotonin and human cancer: a critical view. Depression and quality of life in patients with gliomas: a narrative review. J Clin Med ; 11 16 Depression and survival of glioma patients: a systematic review and meta-analysis. Clin Neurol Neurosurg. Schildkraut JJ. The catecholamine hypothesis of affective disorders: a review of supporting evidence. Am J Psychiatry. The psychological neuroscience of depression: implications for understanding effects of deep brain stimulation. Scand J Psychol. Role of monoamine-oxidase-A-gene variation in the development of glioblastoma in males: a case control study. J Neurooncol. Repurposing drugs for glioblastoma: from bench to bedside. Cancer Lett. Antidepressants with anti-tumor potential in treating glioblastoma: a narrative review. Fundam Clin Pharmacol. Fluoxetine, an antidepressant, suppresses glioblastoma by evoking AMPAR-mediated calcium-dependent apoptosis. Tricyclic antidepressants and the incidence of certain cancers: a study using the GPRD. Br J Cancer. Use of tricyclic antidepressants and risk of glioma: a nationwide case-control study. Acta Oncol. Brain tumors in Sweden: data from a population-based registry Accessed August 26, Risk factors for childhood and adult primary brain tumors. The Nordic prescription databases as a resource for pharmacoepidemiological research--a literature review. Pharmacoepidemiol Drug Saf. The first decade with the Swedish prescribed drug register - a systematic review of the output in the scientific literature. Basic Clin Pharmacol Toxicol. When depression hides a brain tumor: a case of glioblastoma. Newcastle-Ottawa scale: comparing reviewers' to authors' assessments. Targeting glioblastoma signaling and metabolism with a re-purposed brain-penetrant drug. Cell Rep. Different effects of SSRIs, bupropion, and trazodone on mitochondrial functions and monoamine oxidase isoform activity. Antioxidants ; 12 6 Inhibition of monoamine oxidase activity by antidepressants and mood stabilizers. Neuro Endocrinol Lett. MAO inhibitors and oxidant stress in aging brain tissue. Eur Neuropsychopharmacol. Oxidative damage and major depression: the potential antioxidant action of selective serotonin re-uptake inhibitors. Redox Rep. Effects of long-term antidepressant treatment on oxidative status in major depressive disorder: a week follow-up study. Prog Neuropsychopharmacol Biol Psychiatry. Antioxidative enzyme activities and lipid peroxidation in major depression: alterations by antidepressant treatments. J Affect Disord. Association of antidepressant drug use with outcome of patients with glioblastoma. Int J Cancer. Antidepressants and survival in glioma—a registry-based retrospective cohort study. Neuro-Oncology Practice. Depression and glioblastoma, complicated concomitant diseases: a systemic review of published literature. Neurosurg Rev. Anxiety and depression in glioma patients: prevalence, risk factors, and their correlation with survival. Ir J Med Sci. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Sign in through your institution. Advanced Search. Search Menu. Article Navigation. Close mobile search navigation Article Navigation. Article Contents Abstract. Supplementary material. Conflict of interest. Data availability. Journal Article Corrected proof. Antidepressant drugs and risk of developing glioma: a national registry-based case-control study and a meta-analysis. Charlotte Malmberg , Charlotte Malmberg. Oxford Academic. Barbro Numan Hellquist. Sajna Anand Sadanandan. Wendy Yi-Ying Wu. Beatrice Melin. Corresponding author: Rickard L. Revision received:. Corrected and typeset:. Select Format Select format. Permissions Icon Permissions. Abstract Whether use of antidepressants is related to the risk of developing lower-grade WHO grades and higher-grade WHO grade 4 glioma was investigated in this study. Table 1 Open in new tab. Mean age SD , years Table 2 Open in new tab. No SSRI. Table 3 Open in new tab. No non-SSRI. Table 4 Open in new tab. Figure 1. Open in new tab Download slide. Figure 2. Figure 3. Figure 4. Google Scholar Crossref. Search ADS. Google Scholar PubMed. For commercial re-use, please contact journals. Issue Section:. Download all slides. Supplementary data. Views 1, More metrics information. 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Umea buying MDMA pills