Why the study?
The study explored the individual and combined effects of serum tumor necrosis factor-alpha levels and employment status on suicidal behavior in patients with depressive disorders receiving pharmacologic treatment.
Does the combination of serum TNF-alpha levels and employment status predict suicidal behavior in patients with depressive disorders?
Does the combination of serum TNF-alpha levels and employment status predict suicidal behavior in patients with depressive disorders?
Integrating biological markers like sTNF-alpha with socio-economic factors such as employment status can improve the assessment and management of suicide risk in patients with depressive disorders.
Answers are grounded in this paper and cite their sources.
Employment status with sTNF-α may aid suicide risk assessment in depression; hypothesis-generating for combined biomarker-socioeconomic models.
OBJECTIVE: This study explored both the individual and combined effects of serum tumor necrosis factor-alpha (sTNF-α) levels and employment status on suicidal behavior (SB) in patients with depressive disorders undergoing pharmacologic treatment. METHODS: Baseline measurements of sTNF-α levels were taken, and employment status was determined. Over a 1-year period of stepwise pharmacotherapy, SB was monitored and categorized into increased suicidal severity and fatal/non-fatal suicide attempts. Logistic regression models adjusted for relevant covariates were used to analyze the individual and interactive associations between sTNF-α levels, employment status, and these two forms of SB. RESULTS: Unemployment was significantly associated with both forms of SB, whereas sTNF-α levels alone did not show a significant correlation. However, lower sTNF-α levels combined with employment were associated with the lowest incidence rates of both SB categories, demonstrating significant interactive effects after adjustment. CONCLUSION: The study demonstrates that the prospective associations of sTNF-α levels for SB is enhanced when combined with employment status in patients receiving pharmacological treatment for depressive disorders. These findings suggest that integrating biological markers with socio-economic factors can improve the assessment and management of suicide risk.
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Kim et al. (2025) studied this question.
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