一项基于监测、流行病学和最终结果（SEER）数据库预测黏液性卵巢癌患者预后的列线图：一项真实世界研究
A Nomogram Based on SEER Database for Predicting Prognosis in Patients with Mucinous Ovarian Cancer: A Real-World Study.
作者信息
Zhang Ke, Feng Songwei, Ge Yu, Ding Bo, Shen Yang
机构信息
Department of Obstetrics and Gynaecology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, People's Republic of China.
出版信息
Int J Womens Health. 2022 Jul 26;14:931-943. doi: 10.2147/IJWH.S372328. eCollection 2022.
PURPOSE
Mucinous ovarian cancer (MOC) is a rare histological type of EOC. In order to guide the clinical diagnosis and management of MOC patients, we constructed and verified a nomogram for the estimation of overall survival in patients with MOC.
PATIENTS AND METHODS
We collected 494 patients with MOC diagnosed from 2010 to 2015 in SEER database, and the following main inclusion criteria were used: (1) patients whose MOC was confirmed by pathology; (2) patients without a history of primary other cancer. Subsequently, we performed randomized grouping (6:4) and Cox hazard regression analysis in the training group. Subsequently, the nomogram was established. A variety of indicators were used to validate the prognosis value of nomogram, including the C-index, area under the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA). Moreover, Kaplan-Meier analysis was used to compare the survival results among different risk subgroups.
RESULTS
Cox hazard regression analysis revealed that age, grade, FIGO stage and log odds of positive lymph nodes stage were independent risk factors for patients with MOC. In the training group, the C-index of the nomogram was 0.827 (95% CI: 0.791-0.863) and the areas under the curve (AUC) predicting the 1-, 3- and 5-year survival rate were 0.853 (95% CI: 0.791-0.915), 0.886 (95% CI: 0.852-0.920) and 0.815 (95% CI: 0.766-0.864), respectively. The calibration curve revealed that the nomogram of the 1-, 3- and 5-year survival rate was consistent with the actual fact. Patients with high risk had a poorer prognosis than those with low risk (P < 0.001). DCA revealed that the nomogram had the best clinical value than other classical prognostic markers. Similarly, nomogram had excellent prognostic ability in the testing group.
CONCLUSION
The nomogram was constructed to predict overall survival in patients with MOC, which had the significance for clinical evaluation.
目的
黏液性卵巢癌（MOC）是上皮性卵巢癌（EOC）中一种罕见的组织学类型。为指导MOC患者的临床诊断和管理，我们构建并验证了一种用于评估MOC患者总生存期的列线图。
患者与方法
我们收集了2010年至2015年在监测、流行病学与最终结果（SEER）数据库中诊断出的494例MOC患者，并采用以下主要纳入标准：（1）经病理确诊为MOC的患者；（2）无原发性其他癌症病史的患者。随后，我们在训练组中进行随机分组（6:4）和Cox风险回归分析。随后，建立列线图。使用多种指标验证列线图的预后价值，包括C指数、受试者操作特征曲线下面积、校准曲线和决策曲线分析（DCA）。此外，采用Kaplan-Meier分析比较不同风险亚组之间的生存结果。
结果
Cox风险回归分析显示，年龄、分级、国际妇产科联盟（FIGO）分期和淋巴结阳性分期的对数比值是MOC患者的独立危险因素。在训练组中，列线图的C指数为0.827（95%可信区间：0.791 - 0.863），预测1年、3年和5年生存率的曲线下面积（AUC）分别为0.853（95%可信区间：0.791 - 0.915）、0.886（95%可信区间：0.852 - 0.920）和0.815（95%可信区间：0.766 - 0.864）。校准曲线显示，1年、3年和5年生存率的列线图与实际情况一致。高风险患者的预后比低风险患者差（P < 0.001）。DCA显示，列线图比其他经典预后标志物具有更好的临床价值。同样，列线图在测试组中具有出色的预后能力。
结论
构建列线图用于预测MOC患者的总生存期，对临床评估具有重要意义。
Zotero 插件