Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, 1 ShuaiFuYuan, Wangfujing, DongCheng District, Beijing, 100730, P.R. China.
J Ovarian Res. 2020 Oct 17;13(1):123. doi: 10.1186/s13048-020-00727-3.
Ovarian clear cell carcinoma (OCCC) is a rare histologic type of ovarian cancer. There is a lack of an efficient prognostic predictive tool for OCCC in clinical work. This study aimed to construct and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with OCCC.
Data of patients with primary diagnosed OCCC in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016 was extracted. Prognostic factors were evaluated with LASSO Cox regression and multivariate Cox regression analysis, which were applied to construct nomograms. The performance of the nomogram models was assessed by the concordance index (C-index), calibration plots, decision curve analysis (DCA) and risk subgroup classification. The Kaplan-Meier curves were plotted to compare survival outcomes between subgroups.
A total of 1541 patients from SEER registries were randomly divided into a training cohort (n = 1079) and a validation cohort (n = 462). Age, laterality, stage, lymph node (LN) dissected, organ metastasis and chemotherapy were independently and significantly associated with OS, while laterality, stage, LN dissected, organ metastasis and chemotherapy were independent risk factors for CSS. Nomograms were developed for the prediction of 3- and 5-year OS and CSS. The C-indexes for OS and CSS were 0.802[95% confidence interval (CI) 0.773-0.831] and 0.802 (0.769-0.835), respectively, in the training cohort, while 0.746 (0.691-0.801) and 0.770 (0.721-0.819), respectively, in the validation cohort. Calibration plots illustrated favorable consistency between the nomogram predicted and actual survival. C-index and DCA curves also indicated better performance of nomogram than the AJCC staging system. Significant differences were observed in the survival curves of different risk subgroups.
We have constructed predictive nomograms and a risk classification system to evaluate the OS and CSS of OCCC patients. They were validated to be of satisfactory predictive value, and could aid in future clinical practice.
卵巢透明细胞癌（OCCC）是一种罕见的卵巢癌组织学类型。在临床工作中，OCCC 缺乏有效的预后预测工具。本研究旨在构建和验证用于预测 OCCC 患者总生存（OS）和癌症特异性生存（CSS）的列线图。
从 2010 年至 2016 年的监测、流行病学和最终结果（SEER）数据库中提取原发性 OCCC 患者的数据。使用 LASSO Cox 回归和多变量 Cox 回归分析评估预后因素，并应用这些因素构建列线图。通过一致性指数（C 指数）、校准图、决策曲线分析（DCA）和风险亚组分类来评估列线图模型的性能。绘制 Kaplan-Meier 曲线比较亚组之间的生存结果。
SEER 登记处的 1541 名患者被随机分为训练队列（n=1079）和验证队列（n=462）。年龄、侧别、分期、淋巴结（LN）清扫、器官转移和化疗与 OS 独立且显著相关，而侧别、分期、LN 清扫、器官转移和化疗是 CSS 的独立危险因素。建立了预测 3 年和 5 年 OS 和 CSS 的列线图。训练队列中 OS 和 CSS 的 C 指数分别为 0.802[95%置信区间（CI）0.773-0.831]和 0.802（0.769-0.835），验证队列中分别为 0.746（0.691-0.801）和 0.770（0.721-0.819）。校准图表明列线图预测的生存与实际生存具有良好的一致性。C 指数和 DCA 曲线也表明列线图的性能优于 AJCC 分期系统。不同风险亚组的生存曲线存在显著差异。
我们构建了预测列线图和风险分类系统，以评估 OCCC 患者的 OS 和 CSS。验证表明它们具有令人满意的预测价值，并有助于未来的临床实践。
