Liu Zesi, Jing Chunli, Hooblal Yashi Manisha, Yang Hongxia, Chen Ziyu, Kong Fandou
Department of Gynecology and Obstetrics, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Front Oncol. 2024 Mar 21;14:1370272. doi: 10.3389/fonc.2024.1370272. eCollection 2024.
Ovarian clear cell carcinoma (OCCC) is one of the special histologic subtypes of ovarian cancer. This study aimed to construct and validate log odds of positive lymph nodes (LODDS)-based nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with OCCC.
Patients who underwent surgical treatment between 2010 and 2016 were extracted from the Surveillance Epidemiology and End Results (SEER) database and the data of OCCC patients from the First Affiliated Hospital of Dalian Medical University were used as the external validation group to test the validity of the prognostic model. The best-fitting models were selected by stepwise Cox regression analysis. Survival probability was calculated by the Kaplan-Meier method, and the differences in survival time between subgroups were compared using the log-rank test. Each nomogram's performance was assessed by the calibration plots, decision curve analysis (DCA), and receiver operating characteristics (ROC) curves.
T stage, distant metastasis, marital status, and LODDS were identified as significant risk factors for OS. A model with four risk factors (age, T stage, stage, and LODDS value) was obtained for CSS. Nomograms were constructed by incorporating the prognostic factors to predict 1-, 3- and 5-year OS and CSS for OCCC patients, respectively. The area under the curve (AUC) range of our nomogram model for OS and CSS prediction ranged from 0.738-0.771 and 0.769-0.794, respectively, in the training cohort. The performance of this model was verified in the internal and external validation cohorts. Calibration plots illustrated nomograms have good prognostic reliability.
Predictive nomograms were constructed and validated to evaluate the OS and CSS of OCCC patients. These nomograms may provide valuable prognostic information and guide postoperative personalized care in OCCC.
卵巢透明细胞癌（OCCC）是卵巢癌的特殊组织学亚型之一。本研究旨在构建并验证基于阳性淋巴结对数优势比（LODDS）的列线图，以预测OCCC患者的总生存期（OS）和癌症特异性生存期（CSS）。
从监测、流行病学与最终结果（SEER）数据库中提取2010年至2016年间接受手术治疗的患者，并将大连医科大学附属第一医院的OCCC患者数据作为外部验证组，以检验预后模型的有效性。通过逐步Cox回归分析选择最佳拟合模型。采用Kaplan-Meier法计算生存概率，并使用对数秩检验比较亚组间生存时间的差异。通过校准图、决策曲线分析（DCA）和受试者工作特征（ROC）曲线评估每个列线图的性能。
T分期、远处转移、婚姻状况和LODDS被确定为OS的显著危险因素。获得了一个包含四个危险因素（年龄、T分期、分期和LODDS值）的CSS模型。通过纳入预后因素构建列线图，分别预测OCCC患者的1年、3年和5年OS及CSS。在训练队列中，我们的列线图模型预测OS和CSS的曲线下面积（AUC）范围分别为0.738 - 0.771和0.769 - 0.794。该模型的性能在内部和外部验证队列中得到验证。校准图表明列线图具有良好的预后可靠性。
构建并验证了预测列线图，以评估OCCC患者的OS和CSS。这些列线图可能提供有价值的预后信息，并指导OCCC患者术后的个性化护理。
