医学
列线图
危险系数
内科学
甲状腺乳突癌
置信区间
甲状腺癌
比例危险模型
肿瘤科
阶段(地层学)
回顾性队列研究
多元分析
单变量分析
人口
癌症
古生物学
环境卫生
生物
作者
Ya Cao,Tingting Zhang,Bao-Yuan Li,Ning Qu,Yixin Zhu
出处
期刊:Gland surgery
[AME Publishing Company]
日期:2021-07-01
卷期号:10 (7): 2170-2179
被引量:7
摘要
Prognostic evaluation model for papillary thyroid cancer is very important for guiding the personalized treatment and follow-up strategy. There are imperfections in the system existed, and there is no suitable prognostic model for Chinese population.This study was based on the clinic and follow-up data of 660 patients received surgical treatments in the Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center from 2000 to 2005. Cox univariate/multivariate analysis was used to explore the influence factors of prognosis, and nomogram model was performed to establish a prognostic prediction system.Totally, 660 patients for initial treatment were included in our analysis with a median follow-up of 113.5 months. Five-, 10- and 15-year disease-free survival rate was 95.5%, 90.2% and 89.2%. Five-, 10- and 15-year overall survival rate was 99.7%, 99.2% and 99.1%. Residual tumor was associated with overall survival [hazard ratio (HR) 20.9, 95% confidence interval (CI): 2.3-187.6, P<0.05]. Age of onset (HR 2.00, 95% CI: 1.17-3.42, P<0.05) and the dimension of lymph nodes involved (0.2-3 cm: HR 3.67, 95% CI: 1.13-11.87, P<0.05; >3 cm: HR 5.20, 95% CI: 1.31-20.65, P<0.05) were independent influence factors of disease-free survival. The nomogram model for predicting prognosis of papillary thyroid cancer was established with a moderate predictive value (c-index 0.71, 95% CI: 0.57-0.84).The prognosis of papillary thyroid cancer is very good after appropriate treatment. Age and the dimension of lymph nodes involved were independent influence factors of disease-free survival for papillary thyroid cancer. A prognostic prediction model for Chinese population was established with moderate predictive value. A study with larger samples and including more factors of prognosis is necessary to increase the predictive value of model.
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