Metastatic Risk Stratification of 2526 Medullary Thyroid Carcinoma Patients: A Study Based on Surveillance, Epidemiology, and End Results Database
Metastatic Risk Stratification of 2526 Medullary Thyroid Carcinoma Patients: A Study Based on Surveillance, Epidemiology, and End Results Database
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DOI：
10.1007/s12022-022-09724-2
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发表时间：
2022-07-19
影响因子：
4.4
通讯作者：
Kondo, Tetsuo
中科院分区：
文献类型：
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作者：
Le, Minh-Khang;Kawai, Masataka;Kondo, Tetsuo
甲状腺髓样癌（MTC）远处转移的风险尚未得到很好的研究。进一步评估MTC转移风险有助于提高医疗管理质量。因此，我们进行了一项大型人群研究，以开发一种方法来对MTC患者最初出现时的转移风险进行分层。我们从监测、流行病学和最终结果（SEER）数据库中收集了3612例MTC患者，并在应用排除标准后将2526例MTC患者纳入研究。我们从2019例患者的学习队列中选择了信息量最大的变量，通过重复随机数据拼接到训练队列和正则化队列中，获得了1000个模型。我们选择了最优模型，并根据该模型建立了风险表。我们的风险表变量包括年龄、性别、肿瘤大小、甲状腺外扩张和淋巴结转移。当转移风险< 25%时，最终模型显示出良好的校准，并且在训练、正则化和测试队列中，曲线下面积（auc）分别为0.81、0.84和0.84，表现良好。我们对模型的转移估计进行k均值聚类分析，确定了三个存在显著生存差异的风险组（p < 0.001）。在三个队列中，低危患者的转移风险分别为0.88%、1.3%和0.5%，高危患者的转移风险分别为19.7%、15.8%和17.8%。将本表纳入国际MTC分级系统（IMTCGS）需要更全面的临床病理研究。
The risk of distant metastasis in medullary thyroid carcinoma (MTC) has not been well studied. Additional evaluation of MTC metastatic risk can be helpful for improving the quality of medical management. Therefore, we conducted a large population study to develop a method to stratify the risk of metastasis at the initial presentation of MTC patients. We collected 3612 MTC patients from the Surveillance, Epidemiology, and End Results (SEER) database, and included 2526 MTC patients in the study after applying exclusion criteria. We selected the most informative variables from a learning cohort of 2019 patients to obtain 1000 models by repetitive random data splicing into training and regularization cohorts. We selected the optimal model and developed a risk table from that model. Our risk table variables consist of age, gender, tumor size, extrathyroidal extension, and lymph node metastasis. The final model showed good calibration when metastatic risk was < 25% and good performance with areas under the curve (AUCs) of 0.81, 0.84, and 0.84 in the training, regularization, and test cohorts, respectively. We performed K-means clustering analysis on the model's metastatic estimation and determined three risk groups of patients with significant survival differences (p < 0.001). Low-risk patients had 0.88%, 1.3%, and 0.5% while high-risk patients had 19.7%, 15.8%, and 17.8% risk of metastasis in the three cohorts, respectively. The incorporation of our table into the International MTC Grading System (IMTCGS) requires more comprehensive clinicopathological studies.