Wang Ce, Yang Chunyan, Wang Wenjie, Xia Bairong, Li Kang, Sun Fengyu, Hou Yan
Department of Epidemiology and Biostatistics, School of Public Health, Harbin Medical University, Harbin, 150086, China.
Department of Gynecology Oncology, the Tumor Hospital, Harbin Medical University, Harbin 150086, China.
J Cancer. 2018 Oct 10;9(21):3923-3928. doi: 10.7150/jca.26220. eCollection 2018.
: To develop and validate a nomogram based on the conventional measurements and log of odds between the number of positive lymph node and the number of negative lymph node (LODDS) in predicting prognosis for cervical cancer patients after surgery. A total of 8202 cervical cancer patients with pathologically confirmed between 2004 and 2014 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All the patients were divided into training (n=3603) and validation (n=4599) cohorts based on consecutive age of diagnosis. Demographic and clinical pathological factors were evaluated the association with overall survival (OS). Parameters significantly correlating with OS were used to create a nomogram. An independent external validation cohort was subsequently used to assess the predictive performance of the model. In the training set, age at diagnosis, race, marital status, tumor grade, FIGO stage, histology, size and LODDS were correlated significantly with outcome and used to develop a nomogram. The calibration curve for probability of survival showed excellent agreement between prediction by nomogram and actual observation in the training cohort, with a bootstrap-corrected concordance index of 0.749(95% CI, 0.731-0.767). Importantly, our nomogram performed favorably compared to the currently utilized FIGO model, with concordance indices of 0.786 (95% CI, 0.764 to 0.808) vs 0.685 (95%CI, 0.660 to 0.710) for OS in the validation cohort, respectively. By incorporating LODDS, our nomogram may be superior to the currently utilized FIGO staging system in predicting OS in cervical cancer patients after surgery.
基于传统测量指标以及阳性淋巴结数量与阴性淋巴结数量的比值对数(LODDS),开发并验证一种列线图,用于预测宫颈癌患者术后的预后。从监测、流行病学和最终结果(SEER)数据库中获取了2004年至2014年间共8202例经病理确诊的宫颈癌患者。根据连续诊断年龄将所有患者分为训练队列(n = 3603)和验证队列(n = 4599)。评估人口统计学和临床病理因素与总生存期(OS)的相关性。将与OS显著相关的参数用于创建列线图。随后使用独立的外部验证队列评估该模型的预测性能。在训练集中,诊断年龄、种族、婚姻状况、肿瘤分级、国际妇产科联盟(FIGO)分期、组织学类型、肿瘤大小和LODDS与预后显著相关,并用于开发列线图。生存概率的校准曲线显示,训练队列中列线图预测与实际观察结果之间具有良好的一致性,自展校正一致性指数为0.749(95%CI,0.731 - 0.767)。重要的是,与目前使用的FIGO模型相比,我们的列线图表现良好,验证队列中OS的一致性指数分别为0.786(95%CI,0.764至0.808)和0.685(95%CI,0.660至0.710)。通过纳入LODDS,我们的列线图在预测宫颈癌患者术后OS方面可能优于目前使用的FIGO分期系统。