Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China.
Department of Head and Neck Oncology, the Cancer Center of the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China.
Cancer Res Treat. 2021 Jul;53(3):657-670. doi: 10.4143/crt.2020.899. Epub 2020 Dec 7.
This study aimed to develop web-based nomograms to precisely predict survival outcomes in patients with non-metastatic nasopharyngeal carcinoma (NPC) in an endemic area.
A total of 10,126 patients who underwent radical intensity-modulated radiotherapy at Sun Yat-sen University Cancer Center (SYSUCC) from 2009 to 2015 were analyzed. We assigned patients into a training cohort (SYSUCC-A, n=6,751) and an internal validation cohort (SYSUCC-B, n=3,375) based on computer-generated random numbers. Patients collected from Wuzhou Red Cross Hospital (WZRCH) between 2012 and 2015 were used as the independent external validation cohort (WZRCH, n=450). Concordance index (C-index) was used to determine predictive accuracy and discriminative ability for the nomogram. The web-based clinicopathologic prediction models for predicting survival were based on Cox regression.
The C-indexes for SYSUCC-A, SYSUCC-B, and WZRCH cohorts for the established nomograms to predict 3-year overall survival (OS) was 0.736, 0.715, and 0.691. Additionally, C-indexes to predict 3-year distant metastasis-free survival (DMFS) was 0.717, 0.706, and 0.686, disease-free survival (DFS) was 0.713, 0.697, and 0.656, local relapse-free survival was 0.695, 0.684, and 0.652, and regional relapse-free survival was 0.672, 0.650, and 0.616. The calibration plots showed great agreement between nomogram-predicted 3-year survival outcomes and actual 3-year survival outcomes. Moreover, C-indexes of the nomograms for OS, DMFS, and DFS were significantly superior than TNM stage (p< 0.001 for all).
These user-friendly nomograms can precisely predict survival endpoints in patients with non-metastatic NPC. They may serve as a useful tool for providing patient counseling and help physicians to make individual follow-up plans.
本研究旨在开发基于网络的列线图，以准确预测地方性鼻咽癌（NPC）非转移性患者的生存结局。
对中山大学肿瘤防治中心（SYSUCC） 2009 年至 2015 年接受根治性调强放疗的 10126 例患者进行分析。根据计算机生成的随机数，我们将患者分为训练队列（SYSUCC-A，n=6751）和内部验证队列（SYSUCC-B，n=3375）。2012 年至 2015 年收集自梧州市红十字会医院（WZRCH）的患者作为独立的外部验证队列（WZRCH，n=450）。一致性指数（C-index）用于确定列线图的预测准确性和判别能力。基于 Cox 回归的网络临床病理预测模型用于预测生存。
SYSUCC-A、SYSUCC-B 和 WZRCH 队列中，用于预测 3 年总生存（OS）的建立列线图的 C 指数分别为 0.736、0.715 和 0.691。此外，用于预测 3 年无远处转移生存（DMFS）、无病生存（DFS）、局部无复发生存（LRFS）和区域无复发生存（RRFS）的 C 指数分别为 0.717、0.706、0.713、0.697、0.695、0.684 和 0.656。校准图显示，列线图预测的 3 年生存结局与实际 3 年生存结局之间具有很好的一致性。此外，OS、DMFS 和 DFS 列线图的 C 指数明显优于 TNM 分期（所有均 p<0.001）。
这些易于使用的列线图可以准确预测非转移性 NPC 患者的生存结局。它们可以作为提供患者咨询的有用工具，并帮助医生制定个体化随访计划。
