4.6 Article

How do serum lipid levels change and influence progression-free survival in epithelial ovarian cancer patients receiving bevacizumab treatment?

Journal

FRONTIERS IN ONCOLOGY
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2023.1168996

Keywords

epithelial ovarian cancer; serum lipid level; change; influence; progression free survival; bevacizumab treatment

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This study investigated the impact of serum lipid levels on the treatment of epithelial ovarian cancer (EOC) patients receiving bevacizumab and developed a predictive model for prognosis. The study found that serum levels of total cholesterol, triglycerides, apolipoprotein A1, and free fatty acids significantly increased, while apolipoprotein B levels significantly decreased. Using machine learning, independent risk factors were identified and a predictive model for progression-free survival in EOC patients was constructed.
BackgroundThis study aimed to investigate how serum lipid levels affect epithelial ovarian cancer (EOC) patients receiving bevacizumab treatment and to develop a model for predicting the patients' prognosis. MethodsA total of 139 EOC patients receiving bevacizumab treatment were involved in this study. Statistical analysis was used to compare the median and average values of serum lipid level variables between the baseline and final follow-up. Additionally, a method based on machine learning was proposed to identify independent risk factors for estimating progression-free survival (PFS) in EOC patients receiving bevacizumab treatment. A PFS nomogram dividing the patients into low- and high-risk categories was created based on these independent prognostic variables. Finally, Kaplan-Meier curves and log-rank tests were utilized to perform survival analysis. ResultsAmong EOC patients involved in this study, statistical analysis of serum lipid level variables revealed a substantial increase in total cholesterol, triglycerides, apolipoprotein A1, and free fatty acids, and a significant decrease in apolipoprotein B from baseline to final follow-up. Our method identified FIGO stage, combined chemotherapy regimen, activated partial thromboplastin time, globulin, direct bilirubin, free fatty acids, blood urea nitrogen, high-density lipoprotein cholesterol, and triglycerides as risk factors. These risk factors were then included in our nomogram as independent predictors for EOC patients. PFS was substantially different between the low-risk group (total score < 298) and the high-risk group (total score >= 298) according to Kaplan-Meier curves (P < 0.05). ConclusionSerum lipid levels changed variously in EOC patients receiving bevacizumab treatment. A prediction model for PFS of EOC patients receiving bevacizumab treatment was constructed, and it can be beneficial in determining the prognosis, selecting a treatment plan, and monitoring these patients' long-term care.

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