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Establishment and application of a nomogram model for prognostic risk prediction in patients with epithelial ovarian cancer

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Author:
No author available
Journal Title:
Chinese Journal of Obstetrics and Gynecology
Issue:
3
DOI:
10.3760/cma.j.cn112141-20220110-00017
Key Word:
卵巢肿瘤;卵巢上皮癌;列线图;预后;预测;比例危险度模型;回顾性研究;Ovarian neoplasms;Carcinoma, ovarian epithelial;Nomograms;Prognosis;Forecasting;Proportional hazards models;Retrospective studies

Abstract: Objective:To explore the prognostic factors of epithelial ovarian carcinoma (EOC), construct a nomogram model, and evaluate the prognosis of EOC patients.Methods:A retrospective analysis was performed on clinicopathological data of 208 cases of EOC patients who received initial treatment in the First Affiliated Hospital of Army Medical University from August 11, 2016 to July 11, 2018, including age, preoperative ascites, preoperative neoadjuvant chemotherapy, surgical method, pathological type, pathological differentiation degree, surgical pathology stage, preoperative and post-chemotherapy serum cancer antigen 125 (CA 125) level, human epididymal protein 4 (HE4) level, platelet count and platelet/lymphocyte number ratio (PLR). The univariate and multivariate Cox risk ratio models were used to analyze the related factors affecting progression free survival (PFS) in EOC patients, and the prediction nomogram of PFS in EOC patients was established to evaluate its efficacy in predicting PFS. Results:Univariate analysis showed that preoperative neoadjuvant chemotherapy, pathological type, pathological differentiation degree, surgical pathology stage, serum CA 125 and HE4 level before operation and after chemotherapy, platelet count and PLR before operation and after chemotherapy were significantly correlated with PFS in EOC patients (all P<0.05). Multivariate analysis showed that surgical pathology stage, preoperative PLR, serum CA 125 and HE4 level after chemotherapy were independent prognostic factors affecting PFS of EOC patients (all P<0.01). The index coefficient of the prediction model for the prognosis of EOC patients established by this method was 0.749 (95% CI: 0.699-0.798), which had good prediction ability, and could help clinicians to more accurately evaluate the prognosis of EOC patients. Conclusion:The nomogram model constructed based on surgical pathology stage, preoperative PLR, serum CA 125 and HE4 level after chemotherapy could effectively predict the PFS of EOC patients after initial treatment, could help clinicians to screen high-risk patients, provide individualized treatment, and improve the prognosis of EOC patients.

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