文章摘要
伍俊锋,林李嵩,陈法,刘凤琼,鄢灵君,包晓丹,汪靖,王瑞,林亮坤,邱宇,郑晓燕,胡志坚,蔡琳,何保昌.福建省口腔鳞状细胞癌预后指数构建[J].中华流行病学杂志,2018,39(6):841-846
福建省口腔鳞状细胞癌预后指数构建
A novel prognostic index for oral cancer in Fujian province
投稿时间:2017-09-15  
DOI:10.3760/cma.j.issn.0254-6450.2018.06.028
中文关键词: 口腔肿瘤;预后指数;Cox回归
英文关键词: Oral carcinoma;Prognostic index;Cox regression
基金项目:福建省科技厅科研项目(2015J01304);福建省科技创新联合资金(2016Y9033);福建省卫生计生科研人才培养项目(2017-ZQN-57)
作者单位E-mail
伍俊锋 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
林李嵩 350004 福州, 福建医科大学附属第一医院口腔颌面外科  
陈法 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
刘凤琼 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
鄢灵君 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
包晓丹 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
汪靖 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
王瑞 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
林亮坤 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
邱宇 350004 福州, 福建医科大学附属第一医院口腔颌面外科  
郑晓燕 350004 福州, 福建医科大学附属第一医院口腔颌面外科  
胡志坚 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
蔡琳 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系  
何保昌 350108 福州, 福建医科大学公共卫生学院流行病与卫生统计学系 hbc517@163.com 
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中文摘要:
      目的 探讨福建省口腔鳞状细胞癌(OSCC)患者预后影响因素并构建预后指数(PI)。方法 收集福建医科大学附属第一医院口腔颌面外科2004年1月至2016年6月经病理确诊634例OSCC患者的临床资料,并进行随访,将患者随机分为建立模型组(建模组,318例)和验证模型组(验证组,316例)。在建模组,运用Kaplan-Meier法计算生存率,log-rank检验比较生存率差别,采用Cox比例风险回归模型探讨OSCC患者预后影响因素并计算死亡风险比值(HR)及其95%CI,以模型组中有意义的预测变量的β值计算PI。运用三分位法将患者分为高危组、中危组和低危组,并在验证组中采用赤池信息准则(AIC)和Harrell一致性指数(Harrell's c-index,C)检验模型的预测效能。结果 Cox比例风险回归模型分析发现,OSCC患者中年龄≥ 55岁的HR值(95%CI)为2.22(1.45~3.39);口腔卫生较差的HR值(95%CI)为2.12(1.27~3.54);首诊淋巴结转移的HR值(95%CI)为5.78(3.60~9.27);TNM分期为Ⅲ~Ⅳ期(Ⅰ期为参照)的HR值(95%CI)为2.43(1.10~5.37);组织分化程度为低分化(高分化为参照)的HR值(95%CI)为2.53(1.60~4.01)。建模组和验证组中预后模型的预测效能良好(AIC和C值分别为1 205.80、0.700 2和1 150.47、0.737 3)。结论 年龄、口腔卫生、首诊断淋巴结转移、TNM分期和组织病理学分级是OSCC预后影响因素,构建PI模型可有效指导临床治疗。
英文摘要:
      Objective To explore the survival factors and construct a prognostic index (PI) for oral squamous cell carcinoma (OSCC).Methods From January 2004 to June 2016, a total of 634 patients with pathologically confirmed OSCC were recruited in a hospital of Fujian. The clinical and follow-up data of all the patients with pathologically confirmed OSCC were collected to identify the factors influencing the prognosis of OSCC. All the patients were randomly divided into two groups:modeling group (modeling dataset, n=318) and validation group (validation dataset, n=316). Randomization was carried out by using computer-generated random numbers. In the modeling dataset, survival rates were calculated using Kaplan-Meier method and compared using the log-rank test. Cox regression model was used to estimate the hazard ratio (HRs) and 95% confidence intervals (CIs) of prognosis factors. An PI for OSCC patients prognostic prediction model was developed based on β value of each significant variable obtained from the multivariate Cox regression model. Using the tertile analysis, patients were divided into high-risk group, moderate-risk group, and low-risk group according to the PI, the Akaike information criterion (AIC) and Harrell's c-statistic (C index) were used to evaluated the model's predictability.Results Results from the multivariate Cox regression model indicated that aged ≥ 55 years (HR=2.22, 95% CI:1.45-3.39), poor oral hygiene (HR=2.12, 95% CI:1.27-3.54), first diagnosis of lymph node metastasis (HR=5.78, 95% CI:3.60-9.27), TNM stage Ⅲ-Ⅳ (stage Ⅰ as reference) (HR=2.43, 95% CI:1.10-5.37) and poor differentiation (well differentiation as reference) (HR=2.53, 95% CI:1.60-4.01) were the risk factors influencing the prognosis of OSCC. The PI model had a high predictability in modeling group and validation group (AIC and C index were 1 205.80, 0.700 2 and 1 150.47, 0.737 3).Conclusion Age, poor oral hygiene, first diagnosis of lymph node metastasis, TNM stage and histological grade were factors associated with the prognosis of OSCC, and the PI model has a certain significance in the clinical treatment of OSCC.
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