Clinicopathologic features and outcome of cervical cancer: implications for treatment

التفاصيل البيبلوغرافية
العنوان: Clinicopathologic features and outcome of cervical cancer: implications for treatment
المؤلفون: B-Q, Liang, S-G, Zhou, J-H, Liu, Y-M, Huang, X, Zhu
المصدر: European review for medical and pharmacological sciences. 25(2)
سنة النشر: 2021
مصطلحات موضوعية: Adult, Uterine Cervical Neoplasms, Middle Aged, Cohort Studies, Survival Rate, Nomograms, Young Adult, Treatment Outcome, Risk Factors, Humans, Regression Analysis, Female, Aged, Neoplasm Staging
الوصف: We used a regression analysis of the SEER database to establish a new Nomogram for predicting prognosis of cervical cancer patients and guiding the treatment.We divided the data into the training cohort and the verification cohort. Univariate and multivariate Cox risk regression analysis was used to identify independent prognostic factors and establish a Nomogram model. The verification cohort was used for external verification, and the accuracy was evaluated with C-index and AUC. Finally, Nomogram was used to establish 1-year, 3-year and 5-year survival curves of cervical cancer patients.In this study, 5691 patients with cervical squamous cell carcinoma were included. Data obtained from the training cohort were independent risk factors of cervical cancer AJCC stage (p = 0.039), RX Summ - Surgery Primary Site (p = 0.012), radiation (p = 0.031), chemotherapy (p = 0.013), tumor size (p = 0.009), race (p = 0.039). The 1-year, 3-year, and 5-year overall survival rates for cervical cancer patients were 77.2%, 47.8%, and 35.2%, respectively.The Nomogram model can better screen out more reasonable comprehensive treatments for patients at different stages. And it is of great help to improve the survival rate and reduce the recurrence rate of cervical cancer patients.
تدمد: 2284-0729
URL الوصول: https://explore.openaire.eu/search/publication?articleId=pmid________::c0e58485ef8abd852410e2bc1ea9b37b
https://pubmed.ncbi.nlm.nih.gov/33577024
حقوق: OPEN
رقم الأكسشن: edsair.pmid..........c0e58485ef8abd852410e2bc1ea9b37b
قاعدة البيانات: OpenAIRE