Abstract
BACKGROUND: Inflammation and immune status are correlated with the severity of major depressive disorder (MDD).The purpose of this study was to establish an optimization model of peripheral blood parameters to predict the severity of MDD. METHODS: MDD severity in the training and validation cohorts (n = 99 and 97) was classified using the Hamilton Depression Scale, Thirty-eight healthy individuals as controls. Significant severity-associated factors were identified using a multivariate logistic model and combined to develop a joint index through binary logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to identify the optimal model and evaluate the discriminative performance of the index. RESULTS: In the training cohort, lower CD4+/CD8+ T cell ratio, albumin level, and a higher monocyte percentage (M%) were significant as operating sociated with severe disease (P < 0.05 for all). The index was developed using these factors and calculated as CD4+/CD8+ T cell ratio, albumin level, and M%, with a sensitivity and specificity of 90 and 70%, respectively. The AUC values for the index in the training and validation cohorts were 0.85 and 0.75, respectively, indicating good discriminative performance. CONCLUSION: We identified disease severity-associated joint index that could be easily evaluated: CD4+/CD8+ T cell ratio, albumin level, and M%.