背景:收集导管癌(CDC)是一种罕见的肾细胞癌组织学类型,缺乏预后预测模型。在这项研究中,我们建立了一个列线图来预测CDC患者的预后.
方法:从监测中获得2004年至2015年诊断为CDC的患者(n=247)的数据,流行病学,和最终结果(SEER)数据库,患者被随机分为训练组(n=165)和验证组(n=82).通过Kaplan-Meier方法评估生存结果。通过单变量和多变量Cox回归分析确定的重要变量用于构建列线图。C指数和校准图用于评估列线图的性能。
结果:CDC患者的中位总生存期(OS)为18.0个月(95%置信区间:13.7-22.3);1年,3年,5年OS率为58.7%,34.2%,和29.4%,分别。独立的预后因素,包括诊断时的年龄,肿瘤大小,肿瘤分级,T级,N级,M阶段,和手术信息,通过多变量分析确定。列线图是根据训练队列中的重要因素构建的。C指数为0.769(训练队列)和0.767(验证队列)。存活率的校准曲线显示预测值和观察值是一致的。
结论:本研究构建了预测CDC患者预后的列线图。列线图在预测1年方面表现良好,3年,和5年操作系统,这可以帮助医生积极监测和随访患者。
BACKGROUND: Collecting duct carcinoma (CDC) is a rare histological type of renal cell carcinoma that lacks a prognostic prediction model. In this study, we developed a nomogram to predict the prognosis of CDC patients.
METHODS: Data for patients (n = 247) diagnosed with CDC from 2004 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and the patients were randomized into training (n = 165) and validation (n = 82) cohorts. Survival outcomes were evaluated by the Kaplan-Meier method. Significant variables determined by univariate and multivariate Cox regression analyses were used to construct the nomogram. C-indexes and calibration plots were applied to evaluate the performance of the nomogram.
RESULTS: CDC patients had a median overall survival (OS) of 18.0 months (95% confidence interval: 13.7-22.3); 1-year, 3-year, and 5-year OS rates were 58.7%, 34.2%, and 29.4%, respectively. Independent prognostic factors, including age at diagnosis, tumor size, tumor grade, T stage, N stage, M stage, and surgery information, were identified by multivariate analysis. The nomogram was constructed based on significant factors in the training cohort. The C-indexes were 0.769 (training cohort) and 0.767 (validation cohort). The calibration curves for survival rates showed that the predicted and observed values were consistent.
CONCLUSIONS: This study constructed a nomogram to predict prognosis in patients with CDC. The nomogram performed well in predicting the 1-year, 3-year, and 5-year OS, which can help doctors actively monitor and follow up patients.