医学
列线图
队列
肿瘤科
比例危险模型
置信区间
内科学
AJCC分段系统
队列研究
一致性
人口
流行病学
作者
Xueling Qi,Luxi Xu,Juan Wang,Jinjin Yu,Yuan Wang
标识
DOI:10.1016/j.jogoh.2022.102424
摘要
To develop predictive nomograms of overall survival (OS) and cancer-specific survival (CSS) in patients with primary mucinous ovarian cancer (PMOC).Patients diagnosed with PMOC from 2010 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided into a training cohort and a validation cohort. Univariate and multivariate Cox regression analyses were conducted to identify the independent risk factors. Nomograms were constructed and then verified by calibration plots, the concordance index (C-index), and the area under the receiver operating characteristic curve (AUC).A total of 991 patients with PMOC were enrolled and randomly divided into a training cohort (n=695) and a validation cohort (n=296) at a ratio of 7:3. Multivariate Cox regression analyses demonstrated that independent risk factors for OS included age, laterality, and American Joint Committee on Cancer (AJCC) stage. Independent risk factors for CSS included age, laterality, grade, and AJCC stage. Predictive nomograms for OS and CSS were developed with respective independent risk variables. In the training cohort, the C-index of the CSS and OS nomograms were 0.88 [95% confidence interval (CI): 0.84-0.92] and 0.85 (95% CI: 0.81-0.89), respectively. In the validation cohort, the C-index of the predictive CSS and OS nomograms were 0.86 (95% CI: 0.80-0.92) and 0.80 (95% CI: 0.74-0.87), respectively. The AUCs were higher in both cohorts. Furthermore, the calibration curves in both cohorts showed good consistency between the predicted results and the actual results.The nomograms demonstrated good predictability for the survival of patients with PMOC, and could serve as an applicable tool to help clinicians improve treatment plans.
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