Associations between depression and cancer risk among patients with diabetes mellitus: A population‐based cohort study

BACKGROUND: The co‐occurrence of depression and diabetes mellitus has been linked to an increased risk of developing cancer. This study aimed to investigate whether depression further amplifies the risk of cancer among individuals with diabetes. METHODS: This population‐based matched cohort study utilized Taiwan's National Health Insurance claims database. A total of 85,489 newly diagnosed diabetic patients with depressive disorders were selected, along with 427,445 comparison subjects. The matching process involved age, sex, and the calendar year of diabetes onset. The average follow‐up duration for the two cohorts was 6.4 and 6.5 years, respectively. The primary outcome of interest was the occurrence of overall cancer or cancer at specific anatomical sites. RESULTS: The adjusted hazard ratios for overall cancer incidence were 1.08 (95% CI, 1.05–1.11). For site‐specific cancers, depression exhibited significant associations with oropharyngeal, esophageal, liver, gynecological, prostate, kidney, and hematologic malignancies among patients with diabetes. Notably, a severity‐response relationship was observed, indicating that patients with recurrent episodes of major depressive disorders exhibited a higher incidence of cancer compared to those diagnosed with dysthymia or depressive disorder not otherwise specified. Furthermore, the strength of the association between depression and cancer risk was more pronounced among younger patients with diabetes as opposed to older adults. However, no significant relationship was observed between adherence to antidepressant treatment and cancer risk. CONCLUSIONS: The findings of this study indicate a significant association between depression and an elevated risk of cancer among individuals diagnosed with diabetes. Future investigations should replicate our findings, explore the effects of pharmacological and non‐pharmacological treatments on cancer risk, and identify the underlying mechanisms.