Prognostic implications of the BRAF-V600 mutation in papillary thyroid carcinoma based on a new cut-off age stratification.

The BRAF-V600 mutation is the most common and specific oncogenic event known in papillary thyroid carcinoma (PTC). However, it remains controversial whether there is an association between the BRAF-V600 mutation and clinicopathologically aggressive characteristics of PTC. The purpose of the present retrospective study was to investigate the significance of the BRAF-V600 mutation in predicting prognostic and aggressive clinicopathological characteristics according to a new age-based stratification. Clinical data and the BRAF-V600 mutation status of 475 patients with PTC were downloaded from The Cancer Genome Atlas database. The association between BRAF-V600 status and clinicopathological characteristics was analyzed by χ test or Fisher's exact test. Recurrence-free survival rate (RFS) was analyzed using the Kaplan-Meier method. Aggressive clinicopathological factors associated with recurrence were analyzed by Cox multivariate regression. This study was conducted on 219 cases of patients with PTC with a known BRAF-V600 mutational status. In the ≥55 years age group, BRAF-V600 was found to be significantly associated with aggressive PTC characteristics, including tumor size, PTC subtype, radioactive iodine (RAI) dose, follow-up time, recurrence, recurrence risk stage, advanced T stage, advanced N stage and American Joint Committee on Cancer (III/IV) stage (all P<0.05). RFS was analyzed by the log-rank test and exhibited statistically significant differences in the ≥55 years group (P=0.041), but there was no significant difference in the <55 group (P=0.757), according to the BRAF-V600 mutation status. The BRAF-V600 gene was excluded from the recurrence Cox multivariate regression model. The BRAF-V600 mutation was found to better predict aggressive and recurrent PTC based on age stratification with the cut-off age of 55 years. The synergistic interaction between BRAF-V600 mutation and the new age stratification may help clinicians reach the optimal decision in terms of surgical approach and the extent of surgery.