开发和验证一种列线图，用于预测老年甲状腺乳头状癌患者的癌症特异性生存：一项基于人群的研究。
Development and validation of a nomogram to predict cancer-specific survival in elderly patients with papillary thyroid carcinoma: a population-based study.
机构信息
Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, National Clinical Research Center for Child Health and Disorders, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Department of Urology, Kunming Children's Hospital, Yunnan Provincial Key Research Laboratory of Pediatric Major Diseases, Kunming, 650228, China.
出版信息
BMC Geriatr. 2022 Sep 8;22(1):736. doi: 10.1186/s12877-022-03430-8.
OBJECTIVE
Thyroid carcinoma (TC) is the most common endocrine tumor in the human body. Papillary thyroid carcinoma (PTC) accounts for more than 80% of thyroid cancers. Accurate prediction of elderly PTC can help reduce the mortality of patients. We aimed to construct a nomogram predicting cancer-specific survival (CSS) in elderly patients with PTC.
METHODS
Patient information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program. Univariate and multivariate Cox regression models were used to screen the independent risk factors for patients with PTC. The nomogram of elderly patients with PTC was constructed based on the multivariate Cox regression model. We used the concordance index (C-index), the area under the receiver operating characteristic curve (AUC) and the calibration curve to test the accuracy and discrimination of the prediction model. Decision curve analysis (DCA) was used to test the clinical value of the model.
RESULTS
A total of 14,138 elderly patients with PTC were included in this study. Patients from 2004 to 2015 were randomly divided into a training set (N = 7379) and a validation set (N = 3141), and data from 2016 to 2018 were divided into an external validation set (N = 3618). Proportional sub-distribution hazard model showed that age, sex, tumor size, histological grade, TNM stage, surgery and chemotherapy were independent risk factors for prognosis. In the training set, validation set and external validation set, the C-index was 0.87(95%CI: 0.852-0.888), 0.891(95%CI: 0.866-0.916) and 0.931(95%CI:0.894-0.968), respectively, indicating that the nomogram had good discrimination. Calibration curves and AUC suggest that the prediction model has good discrimination and accuracy.
CONCLUSIONS
We constructed a new nomogram to predict CSS in elderly patients with PTC. Internal cross-validation and external validation indicate that the model has good discrimination and accuracy. The predictive model can help doctors and patients make clinical decisions.
目的
甲状腺癌（TC）是人体最常见的内分泌肿瘤。甲状腺乳头状癌（PTC）占甲状腺癌的 80%以上。准确预测老年 PTC 有助于降低患者的死亡率。我们旨在构建一个预测老年 PTC 患者癌症特异性生存（CSS）的列线图。
方法
从监测、流行病学和最终结果（SEER）计划中下载患者信息。使用单变量和多变量 Cox 回归模型筛选 PTC 患者的独立危险因素。基于多变量 Cox 回归模型构建老年 PTC 患者的列线图。我们使用一致性指数（C-index）、接受者操作特征曲线下面积（AUC）和校准曲线来测试预测模型的准确性和区分度。决策曲线分析（DCA）用于测试模型的临床价值。
结果
本研究共纳入 14138 例老年 PTC 患者。2004 年至 2015 年的患者被随机分为训练集（N=7379）和验证集（N=3141），2016 年至 2018 年的数据分为外部验证集（N=3618）。比例亚分布风险模型显示，年龄、性别、肿瘤大小、组织学分级、TNM 分期、手术和化疗是预后的独立危险因素。在训练集、验证集和外部验证集中，C-index 分别为 0.87（95%CI：0.852-0.888）、0.891（95%CI：0.866-0.916）和 0.931（95%CI：0.894-0.968），表明列线图具有良好的区分度。校准曲线和 AUC 表明该预测模型具有良好的区分度和准确性。
结论
我们构建了一个新的列线图来预测老年 PTC 患者的 CSS。内部交叉验证和外部验证表明该模型具有良好的区分度和准确性。该预测模型有助于医生和患者做出临床决策。
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