Novel scoring system incorporating lipoproteins to predict outcomes of epithelial ovarian cancer patients.

Objective: Epithelial ovarian cancer is the most lethal gynecological malignancy worldwide. While common prognostic factors are identified, the impact of serum lipoproteins remains controversial. This retrospective cohort study aims to investigate the association between specific lipoprotein levels and prognosis.

Methods: Clinical data of 420 participants with epithelial ovarian cancer registered at Women's Hospital, School of Medicine, Zhejiang University, between January 2014 and April 2021 were included. Cox regression analyses and Kaplan-Meier methods were used to assess prognosis, estimated by hazard ratio (HR) with 95% confidence interval (CI). A novel prognostic model incorporating lipoproteins was developed for evaluating the prognosis. Meta-analysis was applied to assess the impact of low density lipoprotein cholesterol (LDL-C) on prognosis.

Results: Among 420 patients, those in advanced stages exhibited higher low density lipoprotein cholesterol (LDL-C) (p=0.008) and lower high density lipoprotein cholesterol (HDL-C) levels (p<0.001), with no significant differences in total cholesterol or triglyceride levels. Elevated LDL-C level was significantly associated with worse overall survival (HR 1.72; 95% CI 1.15 to 2.58; p=0.010) and progression free survival (HR 1.94; 95% CI 1.46 to 2.58; p<0.001), whereas higher HDL-C level was linked to better overall survival (HR 0.56; 95% CI 0.37 to 0.85; p=0.004) and progression free survival (HR 0.61; 95% CI 0.46 to 0.81; p<0.001). A novel prognostic model, low density lipoprotein cholesterol-high density lipoprotein cholesterol-fibrinogen-lactate dehydrogenase-prealbumin-Fe-stage (LH-FLPFS), was established to enhance prognostic predictive efficacy. The meta-analysis further suggested that higher LDL-C level was associated with worse overall survival (HR 1.82; 95% CI 1.39 to 2.38; p<0.001).

Conclusions: In this study, preoperative LDL-C and HDL-C levels emerged as potential prognostic factors for ovarian cancer. Establishment of a novel prognostic model, LH-FLPFS, holds promise for significantly improving prognostic predictive efficacy.