Department of Obstetrics and Gynecology, The People's Hospital of Yingshang, Anhui, China.
Bosn J Basic Med Sci. 2021 Oct 1;21(5):620-631. doi: 10.17305/bjbms.2020.5271.
In this study, we established a nomogram for the prognostic prediction of patients with early-onset cervical cancer (EOCC) for both overall survival (OS) and cancer-specific survival (CSS). The Surveillance, Epidemiology, and End Results (SEER) database was used to identify 10,079 patients diagnosed with EOCC between 2004 and 2015; these cases were then randomly divided into training and validation sets. The independent prognostic factors were identified in a retrospective study of 7,055 patients from the training set. A prognostic nomogram was developed using R software according to the results of multivariable Cox regression analysis. Furthermore, the model was externally validated using the data from the remaining 3,024 patients diagnosed at different times and enrolled in the SEER database. For the training set, the C-indexes for OS and CSS prediction were determined to be 0.831 (95 % confidence interval [CI]: 0.815-0.847) and 0.855 (95 % CI: 0.839-0.871), respectively. Receiver operating characteristic (ROC) analysis has revealed that the nomograms were a superior predictor compared with TNM stage and SEER stage. The areas under the curve (AUC) of the nomogram for OS and CSS prediction in the ROC analysis were 0.855 (95 % CI: 0.847-0.864) and 0.782 (95 % CI: 0.760-0.804), respectively. In addition, calibration curves indicated a perfect agreement between the nomogram-predicted and the actual 1-, 3-, and 5-year OS and CSS rates in the validation cohort. Thus, in this study, we established and validated a prognostic nomogram that provides an accurate prediction for 3-, 5-, and 10-year OS and CSS of EOCC patients. This will be useful for clinicians in guiding counseling and clinical trial design for cervical cancer patients.
在这项研究中,我们建立了一个列线图,用于预测早期宫颈癌(EOCC)患者的总生存(OS)和癌症特异性生存(CSS)的预后。我们使用监测、流行病学和最终结果(SEER)数据库,确定了 2004 年至 2015 年间诊断为 EOCC 的 10079 例患者;然后将这些病例随机分为训练集和验证集。我们通过对来自训练集的 7055 例患者的回顾性研究,确定了独立的预后因素。根据多变量 Cox 回归分析的结果,我们使用 R 软件建立了一个预后列线图。此外,我们使用来自 SEER 数据库中不同时间诊断的剩余 3024 例患者的数据,对该模型进行了外部验证。对于训练集,OS 和 CSS 预测的 C 指数分别为 0.831(95%置信区间[CI]:0.815-0.847)和 0.855(95%CI:0.839-0.871)。受试者工作特征(ROC)分析表明,该列线图比 TNM 分期和 SEER 分期更能预测预后。ROC 分析中 OS 和 CSS 预测的列线图曲线下面积(AUC)分别为 0.855(95%CI:0.847-0.864)和 0.782(95%CI:0.760-0.804)。此外,校准曲线表明,验证队列中列线图预测的与实际的 1、3 和 5 年 OS 和 CSS 率之间存在极好的一致性。因此,在这项研究中,我们建立并验证了一个列线图,可对 EOCC 患者的 3、5 和 10 年 OS 和 CSS 进行准确预测。这将有助于临床医生为宫颈癌患者提供咨询和指导,并为临床试验设计提供参考。