Abstract
To compare the predictive effect of the Masaoka-Koga staging system and the International Association for the Study of Lung Cancer (IASLC)/the International Thymic Malignancies Interest Group (ITMIG) proposal for the new TNM staging on prognosis of thymic malignancies using the Chinese Alliance for Research in Thymomas (ChART) retrospective database. From 1992 to 2012, 2,370 patients in ChART database were retrospectively reviewed. Of these, 1,198 patients with complete information on TNM stage, Masaoka-Koga stage, and survival were used for analysis. Cumulative incidence of recurrence (CIR) was assessed in R0 patients. Overall survival (OS) was evaluated both in an R0 resected cohort, as well as in all patients (any R status). CIR and OS were first analyzed according to the Masaoka-Koga staging system. Then, they were compared using the new TNM staging proposal. Based on Masaoka-Koga staging system, significant difference was detected in CIR among all stages. However, no survival difference was revealed between stage I and II, or between stage II and III. Stage IV carried the highest risk of recurrence and worst survival. According to the new TNM staging proposal, CIR in T1a was significantly lower comparing to all other T categories (P<0.05) and there is a significant difference in OS between T1a and T1b (P=0.004). T4 had the worst OS comparing to all other T categories. CIR and OS were significantly worse in N (+) than in N0 patients. Significant difference in CIR and OS was detected between M0 and M1b, but not between M0 and M1a. OS was almost always statistically different when comparison was made between stages I-IIIa and stages IIIb-IVb. However, no statistical difference could be detected among stages IIIb to IVb. Compared with Masaoka-Koga staging, the IASLC/ITMIG TNM staging proposal not only describes the extent of tumor invasion but also provides information on lymphatic involvement and tumor dissemination. Further study using prospectively recorded information on the proposed TNM categories would be helpful to better grouping thymic tumors for predicting prognosis and guiding clinical management.
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