دورية أكاديمية

Value of Inflammatory Load in Predicting Prognosis of Elderly Patients with Epithelial Ovarian Cancer

التفاصيل البيبلوغرافية
العنوان: Value of Inflammatory Load in Predicting Prognosis of Elderly Patients with Epithelial Ovarian Cancer
المؤلفون: YANG Danni, ZHAO Mengna, FENG Xiaoye, TONG Jiyu, WANG Hua, CAI Hongbing
المصدر: Zhongliu Fangzhi Yanjiu, Vol 51, Iss 5, Pp 361-367 (2024)
بيانات النشر: Magazine House of Cancer Research on Prevention and Treatment, 2024.
سنة النشر: 2024
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: inflammation, ovarian cancer, aged, prognosis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: Objective To explore the value of blood inflammatory load in predicting overall survival of elderly patients with epithelial ovarian cancer (EOC). Methods Elderly patients with EOC were selected, and their clinical data and peripheral blood parameters were collected. We constructed an inflammation-related blood scoring system using univariate and multivariate Cox regression analysis. The Kaplan-Meier method was used for survival analysis. We used Cox proportional hazards analysis to identify the independent prognostic factors. A nomogram model was constructed based on independent prognostic factors, and the receiver operating characteristic curve, C-index, and calibration curve were used to evaluate the model. Results Patients with high blood inflammatory load had worse prognosis (P=0.002). Compared with the low inflammatory load group, patients with high inflammatory load had later clinical stages and larger ascites volume (P
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Chinese
تدمد: 1000-8578
العلاقة: https://doaj.org/toc/1000-8578Test
DOI: 10.3971/j.issn.1000-8578.2024.23.1174
الوصول الحر: https://doaj.org/article/d09e73b7f3b04bc9b1077403df05cf15Test
رقم الانضمام: edsdoj.09e73b7f3b04bc9b1077403df05cf15
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:10008578
DOI:10.3971/j.issn.1000-8578.2024.23.1174