作者
Ya-Nan Man,Yanan Wang,Jian Hao,Xiaohui Liu,Chang Liu,Cui-Hong Zhu,Xiong-Zhi Wu
摘要
The study aimed to evaluate the prognostic value of pretreatment plasma dimerized plasmin fragment D (D-dimer), fibrinogen, and platelet levels in epithelial ovarian cancer (EOC) after adjusting for venous thromboembolism (VTE) and to screen out the patients with the greatest risk for poor prognosis.The study comprised 190 patients with EOC. The plasma D-dimer, fibrinogen, and platelet levels were examined before treatment and analyzed with patient clinicopathological parameters, progression-free survival (PFS), and overall survival (OS). The survival analysis was performed using the Kaplan-Meier method, and prognostic factors were assessed using the Cox proportional hazards regression model.The incidences of elevated plasma D-dimer levels, hyperfibrinogenemia, and thrombocytosis were 40%, 42.11%, and 45.26%, respectively. Elevated plasma D-dimer level, hyperfibrinogenemia, and thrombocytosis were associated with advanced tumor stage (P < 0.001, P = 0.013, P < 0.001). In addition, the elevated plasma D-dimer levels were associated with macroscopic postoperative residual disease (P = 0.002) and VTE events (P = 0.006). In multivariate Cox regression model, plasma D-dimer, fibrinogen, and platelet levels were identified as independent prognostic factors for OS (P = 0.039, P = 0.002, and P = 0.049). However, plasma fibrinogen and platelet levels, but not D-dimer levels, had independent prognostic value for PFS (P = 0.012 and P = 0.022). Patients with at least any 2 abnormalities of plasma D-dimer, fibrinogen, and platelet levels showed shorter PFS and OS than did patients with at most 1 abnormality of 3 parameters (P < 0.001).Pretreatment plasma D-dimer, fibrinogen, and platelet levels, which impact prognosis independently of VTE, were demonstrated to be potential markers to predict disease progression and surgery outcome in patients with EOC. The combined use of plasma D-dimer, fibrinogen, and platelet levels may help to identify the high-risk populations for treatment decisions.