Background Misdiagnosis and ineffective treatment are common in major depressive disorder (MDD) in current clinical practice, while the combination of various proteins involved in the pathogenesis of MDD may assist the correct diagnosis. The study aimed to explore whether the combination of serum inflammatory, stress, and neurotrophic factors could be helpful for the diagnosis of MDD, and to investigate the predictors associated with early symptom improvement. Methods Baseline serum levels of C-reactive protein (CRP), interleukin (IL)-6, IL-10, IL-1beta, tumor necrosis factor (TNF)-alpha, interferon (INF)-gamma, cortisol and brain-derived neurotrophic factor (BDNF) were detected in 30 MDD patients and 30 age- and gender-matched healthy controls. 17-item Hamilton Depression Rating Scale (HAMD-17) and Hamilton Anxiety Rating Scale (HAMA) were applied to assess depressive and anxious symptoms both at baseline and 2 weeks after antidepressant treatment. Stepwise multiple linear regression was employed to identify the early efficacy predictiors; while a logistic regression model was built with above proteins and area under receiver operating characteristic (AUC) curve was calculated to evaluate the model’s diagnostic power. Results Multiple linear regression revealed that baseline socres of retardation ( β =-0.432, P =0.012) and psychological anxiety ( β =-0.423, P =0.014) factors were negatively associated with the reduction rate of HAMD-17. A simple and efficient diagnostic model was established by forward stepwise logistic regression and the model achieved an AUC of 0.884, with 86.7% sensitivity and 83.3% specificity. Couclusions The results showed that combining serum BDNF, cortisol and IFN-gamma could aid the diagnosis of MDD, while baseline retardation and psychological anxiety may negatively predict the early symptom improvement.