Chen Fa, Cao Yujie, Huang Jiangfeng, Yan Lingjun, Lin Lisong, Liu Fengqiong, Liu Fangping, Wu Junfeng, Qiu Yu, Cai Lin, He Baochang
Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian, China.
Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fujian, China.
Oncotarget. 2017 Jan 26;8(33):55525-55533. doi: 10.18632/oncotarget.14821. eCollection 2017 Aug 15.
This study aims to develop an applicable prognostic index with conventional factors for predicting outcome of patients with oral squamous cell carcinoma (OSCC). We performed a prospective study in a large cohort of 892 OSCC patients in Fujian, China. All patients were randomly divided into a discovery group and validation group. A prognostic index was developed based on β value of each significant variable obtained from the multivariate Cox regression model. The results from discovery and validation set demonstrated thatthe model-4(included clinical stage, tumor differentiation, ill-fitting denture, oral hygiene and cigarette smoking) was the optimal model. The optimal cutoff points of prognostic index (1.88 and 2.80) were determined by X-tile program which categorized all subjects into low, middle and high risk subsets. Patients in high risk group were at the greatest risk of death compared with those in low risk group (HR: 6.02; 95%CI: 4.33-8.38). Moreover, there was a significant tendency of the worse overall survival with the higher prognostic index (trend <0.001). The discriminatory capacity of prognostic index was 0.661(95%CI: 0.621-0.701). This study developed and validated a prognostic index that is an economical and useful tool for predicting the clinical outcomes of OSCC patients in Southeast China. Future randomized trials with larger cohort are required to confirm our results.
本研究旨在利用传统因素开发一种适用的预后指数,以预测口腔鳞状细胞癌(OSCC)患者的预后。我们在中国福建对892例OSCC患者的大型队列进行了一项前瞻性研究。所有患者被随机分为发现组和验证组。基于从多变量Cox回归模型获得的每个显著变量的β值开发了一种预后指数。发现集和验证集的结果表明,模型4(包括临床分期、肿瘤分化、义齿不合适、口腔卫生和吸烟)是最佳模型。通过X-tile程序确定预后指数的最佳截断点(1.88和2.80),该程序将所有受试者分为低、中、高风险亚组。与低风险组相比,高风险组患者的死亡风险最高(HR:6.02;95%CI:4.33-8.38)。此外,预后指数越高,总生存期越差的趋势越明显(趋势<0.001)。预后指数的鉴别能力为0.661(95%CI:0.621-0.701)。本研究开发并验证了一种预后指数,该指数是预测中国东南部OSCC患者临床结局的一种经济且有用的工具。未来需要更大队列的随机试验来证实我们的结果。