Background: This study aimed to evaluate the potential additive effects of measuring serum interleukin-1 beta (IL-1β) and interleukin-6 (IL-6) on enhancing the predictive value of baseline serum high-sensitivity C-reactive protein (hsCRP) levels for predicting 12-week antidepressant treatment responses in patients with depressive disorders.
Methods: Serum levels of hsCRP, IL-1β, and IL-6 were measured at baseline in 1086 outpatient participants diagnosed with depressive disorders. Participants initially received monotherapy with antidepressants for the first three weeks, followed by a naturalistic, stepwise pharmacotherapy regimen administered every three weeks up to 12 weeks. Remission was defined as achieving a score of ≤7 on the Hamilton Depression Rating Scale. Logistic regression models were employed to analyze the data, adjusting for demographic and clinical covariates.
Results: Higher baseline levels of hsCRP, IL-1β, and IL-6 were significantly associated with lower rates of remission at 12 weeks. Notably, the inclusion of IL-1β and IL-6 levels alongside hsCRP significantly enhanced the model's predictive accuracy, revealing robust interaction effects among these biomarkers.
Limitation: Serum biomarkers were solely measured at baseline and various antidepressants in stepwise psychopharmacotherapy should be considered.
Conclusion: The addition of IL-1β and IL-6 measurements to hsCRP testing could significantly refine the prediction of antidepressant treatment outcomes. These findings support the integration of multiple inflammatory markers into clinical practice, advancing personalized medicine approaches in the treatment of depressive disorders. Further replication studies and randomized controlled trials are encouraged to validate and extend these preliminary findings.
Keywords: Antidepressant; Depression; Inflammation; Prediction; Remission.
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