Department of Radiation Oncology, Sichuan Provincial People's Hospital Qionglai Medical Center Hospital, Chengdu, Sichuan, China.
Department of Radiation Oncology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Biomed Res Int. 2023 Jan 17;2023:7126881. doi: 10.1155/2023/7126881. eCollection 2023.
To establish and validate a nomogram to predict the overall survival (OS) and cancer-specific survival (CSS) in patients with nasopharyngeal carcinoma (NPC) receiving radiotherapy by integrating multiple independent prognostic factors.
Data from 5663 patients with NPC who received definite radiotherapy between 2004 and 2018 were included and divided into training and validation cohorts. Univariate and multivariate Cox regression analyses were performed to determine the independent prognostic factors of patients with NPC after radiotherapy. Thereafter, the predictive accuracy of the nomogram model was evaluated.
Age, race, marital status, pathological type, tumor size, T stage, N stage, M stage, American Joint Committee on Cancer stage, and chemotherapy were independent factors affecting the prognosis of patients with NPC receiving radiotherapy. Nomograms with a concordance index of 0.726 (95% confidence interval (CI): 0.675-0.777) and 0.732 (95% CI: 0.680-0.785) were able to predict OS and CSS, respectively. The area under the curve showed excellent predictive performance. Additionally, the calibration curve indicated that the predicted survival rate was consistent with the actual survival rate, and the decision curve indicated its clinical value. The established risk stratification system was able to accurately stratify patients receiving radiotherapy for NPC into three risk subgroups with significant differences in prognosis ( < 0.05).
The constructed nomogram had good prognostic performance and could be used as an effective tool to evaluate the prognosis of patients with NPC after radiotherapy. This nomogram could be further used to guide clinical decisions and personalized treatment plans.
通过整合多个独立的预后因素，建立并验证一个列线图模型，以预测接受放疗的鼻咽癌患者的总生存（OS）和癌症特异性生存（CSS）。
纳入 2004 年至 2018 年间接受明确放疗的 5663 例鼻咽癌患者的数据，并将其分为训练队列和验证队列。采用单因素和多因素 Cox 回归分析确定接受放疗的鼻咽癌患者的独立预后因素。然后，评估列线图模型的预测准确性。
年龄、种族、婚姻状况、病理类型、肿瘤大小、T 分期、N 分期、M 分期、美国癌症联合委员会分期和化疗是影响接受放疗的鼻咽癌患者预后的独立因素。一致性指数为 0.726（95%置信区间：0.675-0.777）和 0.732（95%置信区间：0.680-0.785）的列线图能够分别预测 OS 和 CSS。曲线下面积显示出良好的预测性能。此外，校准曲线表明预测的生存率与实际生存率一致，决策曲线表明其具有临床价值。所建立的风险分层系统能够准确地将接受放疗的鼻咽癌患者分为预后差异显著的三个风险亚组（<0.05）。
所构建的列线图具有良好的预后预测性能，可作为评估接受放疗的鼻咽癌患者预后的有效工具。该列线图可进一步用于指导临床决策和制定个性化治疗方案。
