Li Zaishang, Li Xueying, Li Yonghong, Liu Ying, Du Peng, Liu Zenqing, Xiao Kefeng
Department of Urology, Shenzhen People's Hospital, The Second Clinic Medical College of Jinan University 518060, Shenzhen, Guangdong, P. R. China.
Department of Urology, First Affiliated Hospital of Southern University of Science and Technology, 518060, Shenzhen, Guangdong, P. R. China.
J Cancer. 2021 Jan 1;12(3):790-798. doi: 10.7150/jca.50419. eCollection 2021.
Available tools for the prediction of the prognosis of patients with upper tract urothelial carcinoma (UTUC) are unified. We determined whether a novel nomogram is effective in estimating the survival of patients with invasive UTUC. From January 2004 to December 2015, 4796 invasive UTUC patients in the Surveillance, Epidemiology and End Results database underwent radical nephroureterectomy (RNU) for invasive UTUC. The medical records of the patients were randomly (7:3) divided into the training and validation cohorts. The independent factors included in the nomogram were selected by multivariate analyses. The nomogram was developed based on the training cohort. Bootstrap validation was applied to validate the nomogram, whereas external validation was performed using the validation cohort. The accuracy and discrimination of the nomogram were assessed using concordance indices (C-indices) and calibration curves. The multivariate Cox regression model identified that age, tumor stage, node stage, metastasis stage and grade were associated with survival. In the training set, the nomogram, which included the above factors, exhibited discrimination power superior to that of the 8th American Joint Committee on Cancer (AJCC) TNM classification (Harrell's C-index, 0.74 vs. 0.71; < 0.001). The nomogram showed better probability of survival agreement with the C-index than the AJCC-TNM staging system in the bootstrap validation 0.74 vs. 0.70; < 0.001 and validation set (Harrell's C-index, 0.77 vs. 0.73; < 0.001). The validation revealed that this nomogram exhibited excellent discrimination and calibration capacities. An accurate novel nomogram that is superior to the current AJCC-TNM staging system was established for the prediction of CSS after RNU for invasive UTUC.
目前用于预测上尿路尿路上皮癌(UTUC)患者预后的工具并不统一。我们确定了一种新型列线图在评估浸润性UTUC患者生存率方面是否有效。2004年1月至2015年12月,监测、流行病学和最终结果数据库中的4796例浸润性UTUC患者接受了根治性肾输尿管切除术(RNU)治疗浸润性UTUC。患者的病历被随机(7:3)分为训练队列和验证队列。通过多变量分析选择列线图中包含的独立因素。列线图基于训练队列开发。采用自助法验证来验证列线图,而使用验证队列进行外部验证。使用一致性指数(C指数)和校准曲线评估列线图的准确性和区分度。多变量Cox回归模型确定年龄、肿瘤分期、淋巴结分期、转移分期和分级与生存率相关。在训练集中,包含上述因素的列线图显示出优于美国癌症联合委员会(AJCC)第8版TNM分类的区分能力(Harrell's C指数,0.74对0.71;<0.001)。在自助法验证中,列线图显示出比AJCC-TNM分期系统更好的生存概率一致性(C指数,0.74对0.70;<0.001)和验证集(Harrell's C指数,0.77对0.73;<0.001)。验证表明该列线图具有出色的区分度和校准能力。建立了一种准确的新型列线图,其优于当前的AJCC-TNM分期系统,用于预测浸润性UTUC患者RNU术后的癌症特异性生存率(CSS)。