C-reactive protein could predict the efficacy of SSRIs in clinical practice: A cohort study of large samples in the real world

Abstract

BackgroundC-reactive protein (CRP) has been shown to predict antidepressant treatment outcomes in several trials, but they were limited to small-sample and strictly-restricted conditions. This study plans to verify if CRP can predict antidepressant efficacy in large samples in the real world. Methods918 depressed patients who had tested CRP were included, then were followed up through their outpatient visits or by telephone to obtain information about their medication therapy (SSRIs, SNRIs, MT, NaSSA) and assess efficacy using the Clinical Global Impressions–Improvement scale (CGII). Efficacy was classified as effective and ineffective and CRP was separated into the low CRP group (CRP <1 mg/L, n = 709) and the high CRP group (CRP ≥1 mg/L, n = 209).The efficacy was compared in different groups. ResultsUsing Kaplan-Meier survival analysis and Cox proportional regression model to analyze, it was discovered that SNRIs were more effective than SSRIs in treating patients with high CRP(HR = 1.652, p = 0.037,95 % CI:1.031–2.654), and SSRIs were more effective in treating patients with low CRP than those with high CRP (HR = 1.257, p = 0.047,95 % CI:1.003–1.574), while no difference in efficacy between the two groups was found in patients using SNRIs, MT, NaSSA. LimitationsSmall amounts of MT and NaSSA were included, and some factors that may affect CRP value have not been controlled. ConclusionCRP could predict the efficacy of SSRIs in the real world, depressed patients with high CRP may be more likely to respond poorly to SSRIs.