摘要
目的探讨原发性甲状腺鳞状细胞癌(PSCCT)的临床特征、生存分析及预后影响因素。方法回顾性分析12例PSCCT患者的临床表现、甲状腺超声特点、治疗方式、组织病理学特点及预后情况。采用Kaplan-Meier法及Log-rank检验、Cox比例风险回归模型进行生存分析。结果单因素分析显示,是否合并乳头状癌与甲状腺鳞癌总生存期(OS)相关;多因素分析显示,未合并乳头状癌是OS的危险因素。结论PSCCT是罕见的甲状腺恶性肿瘤,恶性程度高,病情发展迅速,预后差。临床在诊断PSCCT的同时确定其是否合并乳头状癌,选择恰当的治疗方式是提高患者生存率的关键。
Objective This study aimed to investigate the clinical characteristics,survival analysis,and factors affecting the prognosis of primary squamous cell carcinoma of the thyroid(PSCCT).Methods The preoperative clinical manifestations,thyroid ultrasound features,surgical methods and postoperative pathology of 12 patients with PSCCT admitted to the Department of Head and Neck Surgery in the hospital from January 2012 to December 2019 were retrospectively analyzed,including the immunohistochemical results,comprehensive treatment methods and prognosis.The Kaplan-Meier method,Log-rank test and Cox proportional hazard regression model were used for survival analysis.Results Univariate analysis showed that combined papillary carcinoma was associated with the overall survival(OS)in patients with PSCCT.Multivariate analysis revealed that the absence of the papillary carcinoma was a risk factor for OS.Conclusion PSCCT is a rare malignant thyroid tumor with a high degree of malignancy,rapid development and poor prognosis.If diagnosing PSCCT clinically,it is necessary to determine whether it is associated with papillary carcinoma and selecting the appropriate treatment is the key to improve the survival rate.
作者
李智林
郑洲
安韡
LI Zhilin;ZHENG Zhou;AN Wei(Department of Head and Neck Oncology,Shanxi Province Cancer Hospital,Taiyuan 030013,Shanxi,China;Shanxi Medical University,Taiyuan 030001,Shanxi,China;Department of Oral and Maxillofacial Surgery,Shanxi Provincial People's Hospital,Taiyuan 030012,Shanxi,China)
出处
《山东大学耳鼻喉眼学报》
CAS
2023年第1期59-63,共5页
Journal of Otolaryngology and Ophthalmology of Shandong University
基金
山西省重点研发计划项目(201903D321029)。
关键词
原发性甲状腺鳞状细胞癌
危险因素
单因素分析
多因素分析
生存
Primary squamous cell carcinoma of the thyroid
Risk factor
Single-factor analysis
Multivariate analysis
Survival