[A novel prognostic index for oral cancer in Fujian province].

To explore the survival factors and construct a prognostic index (PI) for oral squamous cell carcinoma (OSCC). 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, =318) and validation group (validation dataset, =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 (s) and 95 confidence intervals (s) of prognosis factors. An PI for OSCC patients prognostic prediction model was developed based on 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 from the multivariate Cox regression model indicated that aged ≥55 years (=2.22, 95: 1.45-3.39), poor oral hygiene (=2.12, 95: 1.27-3.54), first diagnosis of lymph node metastasis (=5.78, 95: 3.60-9.27), TNM stage Ⅲ-Ⅳ (stage Ⅰ as reference) (=2.43, 95: 1.10-5.37) and poor differentiation (well differentiation as reference) (=2.53, 95: 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). 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.