基于外周血评分和临床病理参数的列线图模型用于预测上皮性卵巢癌患者术前晚期阶段及预后的研究
Development of Nomogram Models Based on Peripheral Blood Score and Clinicopathological Parameters to Predict Preoperative Advanced Stage and Prognosis for Epithelial Ovarian Cancer Patients.
作者信息
Bai Gaigai, Zhou Yue, Rong Qing, Qiao Sijing, Mao Hongluan, Liu Peishu
机构信息
Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, People's Republic of China.
Shandong Engineering Laboratory for Urogynecology, Qilu Hospital of Shandong University, Jinan, People's Republic of China.
出版信息
J Inflamm Res. 2023 Mar 23;16:1227-1241. doi: 10.2147/JIR.S401451. eCollection 2023.
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.
目的
营养和炎症状态在癌症发展中至关重要。本研究的目的是构建一个基于与营养和炎症相关的外周血参数的评分系统,并探讨其在上皮性卵巢癌(EOC)患者的分期、总生存期(OS)和无进展生存期(PFS)预测中的价值。
患者与方法
回顾性纳入453例EOC患者,收集其临床资料及相关外周血参数。计算中性粒细胞与淋巴细胞比值、淋巴细胞与单核细胞比值、纤维蛋白原与淋巴细胞比值、总胆固醇与淋巴细胞比值及白蛋白水平,并进行二分法处理。构建了一个名为外周血评分(PBS)的评分系统。采用单因素和多因素Logistic或Cox回归分析筛选独立因素;然后将这些因素分别用于建立晚期、OS和PFS的列线图模型。进行内部验证和决策曲线分析(DCA)以评估模型。
结果
较低的PBS提示较好的预后,较高的PBS提示较差的预后。高PBS与晚期、高CA125、浆液性组织学类型、低分化及伴有腹水相关。Logistic回归显示年龄、CA125和PBS是FIGO III-IV期的独立因素。基于这些因素构建的FIGO晚期列线图模型显示出良好的效能。FIGO分期、残留病灶和PBS是影响OS和PFS的独立因素,由这些因素组成的列线图模型具有良好的性能。DCA曲线显示模型增加了净效益。
结论
PBS可作为EOC患者预后的非侵入性生物标志物。相关列线图模型可能是为EOC患者提供晚期、OS和PFS信息的强大且具有成本效益的工具。