Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China (mainland).
Physical Examination Center, The Ninth Hospital of Xi'an Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China (mainland).
Med Sci Monit. 2019 Jul 27;25:5561-5571. doi: 10.12659/MSM.915620.
BACKGROUND The AJCC staging system is inadequate for use in patients with thyroid carcinomas. Here, we aimed to establish a nomogram for thyroid cancer, and we compare its prognostic value with the AJCC staging system in adults diagnosed with thyroid carcinoma. MATERIAL AND METHODS Patient records were obtained from the Surveillance, Epidemiology, and End Result database. The 8491 included patients were divided into a modeling cohort (n=5943) and a validation cohort (n=2548). The variables included in the modeling cohort were selected using a backward stepwise selection method with Cox regression, and the prognosis nomogram was constructed. In the validation cohort, we compared our survival model with the AJCC prognosis model using the concordance index, the area under the time-dependent receiver operating characteristic curve, the net reclassification improvement, the integrated discrimination improvement, calibration plotting, and decision curve analysis. RESULTS Twelve independent prognostic factors were identified and used to establish the nomogram. In particular, marital status was included in a survival prediction model of thyroid cancer for the first time. The concordance index, area under the time-dependent receiver operating characteristic curve, net reclassification improvement, integrated discrimination improvement, calibration plotting, and decision curve analysis for the nomogram showed better performance compared to the AJCC staging system. CONCLUSIONS We have developed and validated a highly accurate thyroid cancer prognosis nomogram. The prognostic value of the nomogram is better than that of the AJCC staging system alone.
AJCC 分期系统在甲状腺癌患者中应用不足。本研究旨在建立甲状腺癌的列线图，并比较其在诊断为甲状腺癌的成人中的预后价值与 AJCC 分期系统的差异。
从监测、流行病学和最终结果数据库中获取患者记录。纳入的 8491 例患者被分为建模队列（n=5943）和验证队列（n=2548）。使用 Cox 回归的向后逐步选择方法选择建模队列中的变量，并构建预后列线图。在验证队列中，我们使用一致性指数、时间依赖性接受者操作特征曲线下面积、净重新分类改善、综合判别改善、校准图和决策曲线分析来比较我们的生存模型与 AJCC 预后模型。
确定了 12 个独立的预后因素，并用于建立列线图。特别是，婚姻状况首次被纳入甲状腺癌生存预测模型中。列线图的一致性指数、时间依赖性接受者操作特征曲线下面积、净重新分类改善、综合判别改善、校准图和决策曲线分析的表现均优于 AJCC 分期系统。
我们已经开发并验证了一个高度准确的甲状腺癌预后列线图。该列线图的预后价值优于 AJCC 分期系统。
