Proliferative status is a risk index for recurrence in primary superficial (pTa/T1) low-grade urothelial XXXX .

@entity1 @entity2558 @entity22149 @entity5 @entity876 @entity150 @entity1722
The current clinicopathologic study for evaluation of superficial @entity150 still has limitations in predicting the true behavior of recurrence. To determine the high-risk recurrence factors, we studied the influence of Ki-67, @entity1722 , @entity876 and @entity22149 ( @entity22149 ) expression. Samples were obtained from 33 pTa and 46pT1 diagnosed @entity150 @entity1 with a mean follow-up of 48.7 +/- 30.6 months. The contingency table method, Kaplan-Meier curve and multivariate analysis were used to evaluate the association among the immunohistochemical factors expression, clinicopathologic parameters with @entity5 recurrence. Stage @entity2558 @entity5 , @entity5 and large @entity5 (> 3 cm) showed a significantly high recurrence rate (p = 0.0158, p = 0.0162, p = 0.0001 respectively). Tumors with overexpression of Ki-67, @entity1722 and @entity876 were more likely to recur (p = 0.0035, p = 0.0027, p = 0.0076 respectively), @entity22149 expression was not associated with recurrence. Multivariate analysis showed that large @entity5 and high Ki-67 expression were independent indicators of recurrence. On the other hand, in @entity5 less than 1 cm, recurrence was significantly correlated with overexpression of Ki-67 and @entity876 . High Ki-67 expression could discriminate higher recurrence cases in grade 2, @entity2558 and single @entity5 . The @entity1722 overexpression was more frequently associated with recurrence in @entity5 , large @entity5 , multiple and grade 1 @entity5 . The @entity876 overexpression also predicted a higher risk of recurrence in pTa @entity5 . These data demonstrated that the use of proliferative related proteins yields significant prognostic information in addition to clinicopathological factors, high Ki-67 expression is a reliable indicator of recurrence. A combination rather than any factor alone could more accurately predict @entity5 recurrence.
