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The impact of depression on risk of malignant glioma: A nationwide cohort studyopen access

Authors
Eun, JinUm, Yoo HyunHan, KyungdoJoo, Won-IlYang, Seung Ho
Issue Date
Feb-2025
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Glioma; Depression; Depressive disorder; Cohort studies; Malignant glioma
Citation
JOURNAL OF PSYCHOSOMATIC RESEARCH, v.189
Journal Title
JOURNAL OF PSYCHOSOMATIC RESEARCH
Volume
189
URI
https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/50623
DOI
10.1016/j.jpsychores.2024.111982
ISSN
0022-3999
1879-1360
Abstract
Background: Malignant glioma (MG) is a malignant brain tumor with a fatal prognosis. Depression is on the rise in society, and its negative association on prognosis of glioma patients is known. This study aimed to investigate the correlation between depression and MG risk by analyzing data from the Korean National Health Insurance System (NHIS). Methods: A retrospective cohort study utilized NHIS data starting with 4,234,415 individuals aged 20 and above who had undergone health check-ups in 2009. Excluding 65,146 for cancer diagnosis, missing data, or a one-year lag period, 3,856,362 individuals were analyzed. Those diagnosed with depression per ICD-10 codes F32 or F33 before the check-ups formed the depression group, while the MG group was identified by ICD-10 code C71. Results: Depression was found to have a significant association with glioma risk (hazard ratio 1.127, 95 % confidence interval 1.101-1.347), even with adjustment for age, sex, income, body-mass index (BMI), smoking, drinking, regular exercise, diabetes mellitus, hypertension and dyslipidemia. Furthermore, the severity of depression had a greater influence on MG incidence. Finally, subgroup analysis according to MG status revealed factors such as income, regular exercise, chronic kidney disease, and BMI to exhibit significant differences related to depression in the no-glioma group, but not in the glioma group. Conclusions: These results suggest that depression may be associated with development of MG.
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College of Natural Sciences (Department of Statistics and Actuarial Science)
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