K-Y Kim1, X Zhang2, S-M Kim3, B-D Lee3, I-H Cha3. 1. BK21 PLUS Project, College of Dentistry, Yonsei University, Seoul, Korea. 2. Department of pathology, Yanbian University medical college, Yanji city, China. 3. Department of Oral and Maxillofacial Surgery, College of Dentistry, Yonsei University, Seoul, Korea.
Abstract
PURPOSE: We aimed to identify a combined prognostic factor for predicting better performance in risk stratification. MATERIALS AND METHODS: We reviewed the clinical and pathological variables of 316 patients with oral squamous cell carcinoma (OSCC) who underwent surgery. To identify a combined predictor, principal component analysis (PCA) was performed. RESULTS: Univariate analysis showed that the independent prognostic variables for overall survival (OS) were pathologic T stage (T1 vs T4, HR = 1.99, 95% CI: = 1.083-3.675, P = 0.026) and pathologic N stage (N0 vs N2, HR=1.90, 95% CI: = 1.17-3.08, P = 0.008). In the multivariate analysis, only pathologic T stage was significant (P = 0.006 and P = 0.007); however, the multivariate model was not significant (P = 0.191). The multivariate model became significant by including lymph node ratio (LNR) instead of pathologic N stage (P = 0.0025 in numeric LNR, P = 0.0007 in categorized LNR). Also, the performance of prediction model was improved by a combined prognostic factor (P = 0.0002). CONCLUSIONS: The newly identified combined prognostic factor included resection margin, differentiation, and LNR, and they were insignificant factors independently except for LNR. This combined prognostic factor showed a good performance although it did not include molecular markers; therefore, it may be used conveniently for risk stratification of patients with OSCC by combining only clinical information.
PURPOSE: We aimed to identify a combined prognostic factor for predicting better performance in risk stratification. MATERIALS AND METHODS: We reviewed the clinical and pathological variables of 316 patients with oral squamous cell carcinoma (OSCC) who underwent surgery. To identify a combined predictor, principal component analysis (PCA) was performed. RESULTS: Univariate analysis showed that the independent prognostic variables for overall survival (OS) were pathologic T stage (T1 vs T4, HR = 1.99, 95% CI: = 1.083-3.675, P = 0.026) and pathologic N stage (N0 vs N2, HR=1.90, 95% CI: = 1.17-3.08, P = 0.008). In the multivariate analysis, only pathologic T stage was significant (P = 0.006 and P = 0.007); however, the multivariate model was not significant (P = 0.191). The multivariate model became significant by including lymph node ratio (LNR) instead of pathologic N stage (P = 0.0025 in numeric LNR, P = 0.0007 in categorized LNR). Also, the performance of prediction model was improved by a combined prognostic factor (P = 0.0002). CONCLUSIONS: The newly identified combined prognostic factor included resection margin, differentiation, and LNR, and they were insignificant factors independently except for LNR. This combined prognostic factor showed a good performance although it did not include molecular markers; therefore, it may be used conveniently for risk stratification of patients with OSCC by combining only clinical information.