Abstract

Ankit Patel*, Jagdish Varma and Barna Ganguly

ABSTRACT

Context: Depression is one of the most debilitating illnesses worldwide. As response to available antidepressant treatment takes 4-6 weeks to produce significant clinical response, trying various treatments consume long time before concluding one effective treatment in many patients. Treatment predicting biomarkers to classify groups of patients, can play significantly in monitoring the outcome of their treatment who were given specific class of antidepressant. Aims: To find out relationship between baseline level of inflammatory biomarkers (IL-6, TNF-α and CRP) and response of selective serotonin reuptake inhibitors (SSRIs). Settings and design: Systematic review Methods and material: Literature search on treatment of depression and inflammatory markers was performed in PubMed. Through critical appraisal and screening, 17 out of 387 articles were selected. Statistical analysis was carried out by RevMan 5. Results: Efficacy of SSRI was analyzed in 14 studies. Statistically highly significant reduction in HAM-D score was found after treatment with escitalopram [SMD = 9.06 (95% CI: 5.28, 12.83), Z = 4.70, P < 0.00001], sertraline [SMD = 11.70 (95% CI: 8.48, 14.91), Z = 7.13, P < 0.00001] and all SSRIs together [SMD = 10.32 (95% CI: 8.54, 12.09), Z = 11.38, P < 0.00001]. At initiation of SSRI treatment, low baseline level of IL-6 (10 pg/ml), TNF-α (11 pg/ml) and CRP (5 mg/L) were found associated with better clinical outcome in the patients of depression. Conclusions: It is evident that SSRIs are effective in treating depression. Low baseline level of IL-6, TNF-α and CRP can predict better response by SSRIs, so baseline level of these biomarkers can be potentially utilized as treatment deciding biomarkers in depressive patients.