Suppr超能文献

预测膀胱原发性小细胞癌患者个体预后的列线图

Nomograms to Predict Individual Prognosis of Patients with Primary Small Cell Carcinoma of the Bladder.

作者信息

Dong Fan, Shen Yifan, Gao Fengbin, Shi Xiao, Xu Tianyuan, Wang Xianjin, Zhang Xiaohua, Zhong Shan, Zhang Minguang, Chen Shanwen, Shen Zhoujun

机构信息

Department of Urology, Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China.

Department of Urology, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.

出版信息

J Cancer. 2018 Mar 8;9(7):1152-1164. doi: 10.7150/jca.23344. eCollection 2018.

Abstract

To develop reliable nomograms to estimate individualized overall survival (OS) and cancer specific survival (CSS) for patients with primary small cell carcinoma of the bladder (SCCB) and compare the predictive value with the AJCC stages. 582 eligible SCCB patients identified in the Surveillance, Epidemiology, and End Results (SEER) dataset were randomly divided into training (n=482) and validation (n=100) cohorts. Akaike information criterion was used to select the clinically important variables in multivariate Cox models when establishing nomograms. The performance of nomograms was bootstrapped validated internally and externally using the concordance index (C-index) with 95% confidence interval (95% CI) and calibration curves and was compared with that of the AJCC stages using C-index, Kaplan-Meier curves and decision curve analysis (DCA). Two nomograms shared common indicators including age, tumor size, T stage, lymph node ratio, metastases, chemotherapy, radiation and radical cystectomy, while marriage and gender were only incorporated in the OS nomogram. The C-indices of nomograms for OS and CSS were 0.736 (95%CI 0.711-0.761) and 0.731(95%CI 0.704-0.758), respectively, indicating considerable predictive accuracy. Calibration curves showed consistency between the nomograms and the actual observation. The results remained reproducible when nomograms were applied to the validation cohort. Additionally, comparisons between C-indices, Kaplan-Meier curves and DCA proved that the nomograms obtained obvious superiority over the AJCC stages with wide practical threshold probabilities. We proposed the first two nomograms for individualized prediction of OS and CSS in SCCB patients with satisfactory predictive accuracy, good robustness and wide applicability.

摘要

为了开发可靠的列线图,以估计原发性膀胱小细胞癌(SCCB)患者的个体总生存期(OS)和癌症特异性生存期(CSS),并将预测价值与美国癌症联合委员会(AJCC)分期进行比较。在监测、流行病学和最终结果(SEER)数据集中确定的582例符合条件的SCCB患者被随机分为训练队列(n = 482)和验证队列(n = 100)。在建立列线图时,使用赤池信息准则在多变量Cox模型中选择临床重要变量。列线图的性能通过一致性指数(C-index)及95%置信区间(95%CI)和校准曲线在内部和外部进行自举验证,并使用C-index、Kaplan-Meier曲线和决策曲线分析(DCA)与AJCC分期进行比较。两个列线图共享包括年龄、肿瘤大小、T分期、淋巴结比例、转移、化疗、放疗和根治性膀胱切除术等共同指标,而婚姻状况和性别仅纳入OS列线图。OS和CSS列线图的C指数分别为0.736(95%CI 0.711 - 0.761)和0.731(95%CI 0.704 - 0.758),表明具有相当高的预测准确性。校准曲线显示列线图与实际观察结果一致。当将列线图应用于验证队列时,结果仍然具有可重复性。此外,C指数、Kaplan-Meier曲线和DCA之间的比较证明,在广泛的实际阈值概率下,列线图比AJCC分期具有明显优势。我们提出了前两个用于SCCB患者OS和CSS个体化预测的列线图,具有令人满意的预测准确性、良好的稳健性和广泛的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b382/5907663/221470375e7f/jcav09p1152g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验