Development of Nomogram Models Based on Peripheral Blood Score and Clinicopathological Parameters to Predict Preoperative Advanced Stage and Prognosis for Epithelial Ovarian Cancer Patients

Gaigai Bai; Yue Zhou; Qing Rong; Sijing Qiao; Hongluan Mao; Peishu Liu

doi:10.2147/JIR.S401451

Development of Nomogram Models Based on Peripheral Blood Score and Clinicopathological Parameters to Predict Preoperative Advanced Stage and Prognosis for Epithelial Ovarian Cancer Patients

J Inflamm Res. 2023 Mar 23:16:1227-1241. doi: 10.2147/JIR.S401451. eCollection 2023.

Authors

Gaigai Bai^{1

2}, Yue Zhou^{1

2}, Qing Rong^{1

2}, Sijing Qiao^{1

2}, Hongluan Mao^#^{1

2}, Peishu Liu^#^{1

2}

Affiliations

¹ Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People's Republic of China.
² Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Nutritional and inflammatory states are crucial in cancer development. The purpose of this study is to construct a scoring system grounded on peripheral blood parameters associated with nutrition and inflammation and explore its value in stage, overall survival (OS), and progression-free survival (PFS) prediction for epithelial ovarian cancer (EOC) patients.

Patients and methods: Four hundred and fifty-three EOC patients were retrospectively identified and their clinical data and relevant peripheral blood parameters were collected. The ratio of neutrophil to lymphocyte, lymphocyte to monocyte, fibrinogen to lymphocyte, total cholesterol to lymphocyte and albumin level were calculated and dichotomized. A scoring system named peripheral blood score (PBS) was constructed. Univariate and multivariate Logistic or Cox regression analyses were used to select independent factors; these factors were then used to develop nomogram models of advanced stage and OS, PFS, respectively. The internal validation and DCA analysis were performed to evaluate models.

Results: Lower PBS indicated a better prognosis and higher PBS indicated inferior. High PBS is associated with advanced stage, high CA125, serous histological type, poor differentiation, and accompanied ascites. The logistic regression showed age, CA125, and PBS were independent factors for the FIGO III-IV stage. The nomogram models for advanced FIGO stage based on these factors showed good efficiency. FIGO stage, residual disease, and PBS were independent factors affecting OS and PFS, the nomogram models composed of these factors had good performance. DCA curves revealed the models augmented net benefits.

Conclusion: PBS can be a noninvasive biomarker for EOC patients' prognosis. The related nomogram models could be powerful, cost-effective tools to provide information of advanced stage, OS, and PFS for EOC patients.

Keywords: inflammation; nutrition; ovarian cancer; peripheral blood; predict model.

Grants and funding

This work was supported by China Postdoctoral Science Fund (21510077311145 and 21300076311047), Natural Science Foundation of Shandong Province (ZR2020MH272).