Department of Breast and Thyroid Surgery, Suining Central Hospital, Suining, Sichuan Province, China.
Medicine (Baltimore). 2024 Nov 1;103(44):e40381. doi: 10.1097/MD.0000000000040381.
This study aimed to develop and validate a prognostic model for elderly patients with differentiated thyroid carcinoma (DTC) based on various demographic and clinical parameters in order to accurately predict patient outcomes. Patients who were diagnosed with DTC and were over 55 years old between 2010 and 2019 were identified from the Surveillance, Epidemiology, and End Results database. The patients were then randomly divided into a training set and a validation set in a 7:3 ratio, and patients from our center were included as an external validation group. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic factors, which were then utilized to develop nomograms for predicting the prognosis. The discriminative ability of the nomograms was evaluated using the concordance index, and the calibration was assessed using calibration plots. The clinical usefulness and benefits of the predictive models were determined through decision curve analysis. The findings of the stepwise Cox regression analysis revealed that several variables, including age, marital status, sex, multifocality, T stage, N stage, and M stage, were significantly associated with overall survival in elderly patients with DTC. Additionally, age, tumor size, multifocality, T stage, N stage, and M stage were identified as the primary determinants of cancer specific survival in elderly patients with DTC. Using these predictors, nomograms were constructed to estimate the probability of overall survival and cancer specific survival. The nomograms demonstrated a high level of predictive accuracy, as evidenced by the concordance index, and the calibration plots indicated that the predicted outcomes were consistent with the actual outcomes. Furthermore, the decision curve analysis demonstrated that the nomograms provided substantial clinical net benefit, indicating their utility in clinical practice.
本研究旨在基于各种人口统计学和临床参数为老年分化型甲状腺癌 (DTC) 患者开发和验证一种预后模型，以准确预测患者的结局。从监测、流行病学和最终结果数据库中确定了 2010 年至 2019 年间诊断为 DTC 且年龄超过 55 岁的患者。然后，患者被随机分为 7:3 的训练集和验证集，我们中心的患者被纳入外部验证组。进行单变量和多变量 Cox 比例风险回归分析以确定独立的预后因素，然后利用这些因素开发用于预测预后的列线图。通过一致性指数评估列线图的判别能力，并通过校准图评估校准。通过决策曲线分析确定预测模型的临床实用性和获益。逐步 Cox 回归分析的结果表明，几个变量，包括年龄、婚姻状况、性别、多灶性、T 分期、N 分期和 M 分期，与老年 DTC 患者的总生存率显著相关。此外，年龄、肿瘤大小、多灶性、T 分期、N 分期和 M 分期被确定为老年 DTC 患者癌症特异性生存率的主要决定因素。使用这些预测因子，构建了列线图以估计总生存率和癌症特异性生存率的概率。列线图表现出高度的预测准确性，一致性指数证明了这一点，校准图表明预测结果与实际结果一致。此外，决策曲线分析表明，列线图提供了实质性的临床净获益，表明它们在临床实践中的实用性。
