Considering their similarity, we combined event-free (EFS), progression-free (PFS), and disease-free (DFS) survival as DFS. Hazard ratios and 95% CI were applied to estimate the correlation of blood inflammatory markers and survival. The heterogeneity among studies was assessed by means of Q-test and I2 of the chi-square test. If significant heterogeneity (P < 0.05 and I2 > 50%) was observed, the random effect model was used; otherwise, the fixed effect model was employed. To identify the sources of heterogeneity, we performed subgroup analysis by tumor stage, analysis method, histological type, and ethnicity. Publication bias was conducted by means of the Begg test (funnel plots). The Stata software (Stata corporation, version 12.0, College Station, TX, USA) was used for the analysis of data, and statistical significance was considered for P values <0.05.

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