Ki-67 Expression for Predicting Progression of Postoperative Residual Pituitary Adenomas : Correlations With Clinical Variables
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概要
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Reliable prognostic parameters indicating progression in residual pituitary adenoma after surgery are necessary. The World Health Organization classification of tumors of endocrine organs defines atypical pituitary adenomas as tumor with Ki-67 labeling index higher than 3%, excessive p53 immunoreactivity, and increased pleomorphism. The real value of Ki-67 labeling index correlating with tumor progression is controversial. We investigated the relationship between positive labeling for MIB-1 and clinical features of 39 patients with pituitary adenomas with and without rapid re-growth after initial surgery. Ki-67 expression revealed pituitary adenomas with progression (re-growth within 5 years after initial surgery) had a mean proliferation index of 3.66 ± 3.00% (mean ± standard deviation [SD], n = 12), which was significantly higher than in tumors without progression of 1.89 ± 1.25% (mean ± SD, n = 27) (p < 0.05, Mann-Whitney test). Receiver operating characteristic analysis showed a threshold level of Ki-67 expression greater than 2.0% predicts progression with high specificity. Younger patients had higher MIB-1 index and more progression (p < 0.05). Adenomas with cavernous sinus invasion, functioning adenomas, and giant adenomas had higher MIB-1 index (p < 0.05). There was no significant correlation between tumor size or cavernous sinus invasion and progression. More completely removed tumors were less progressive. A threshold of 2% for the MIB-1 labeling index predicts higher risk of progression of residual adenomas after surgery, so shorter interval of follow-up neuroimaging, and early initiation of adjuvant therapy might be required.
- 2012-08-15
著者
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Matsuyama Junko
Department Of Neurosurgery Beppu Rehabilitation Center
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Matsuyama Junko
Department Of Neurosurgery Fujita Health University
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- Ki-67 Expression for Predicting Progression of Postoperative Residual Pituitary Adenomas : Correlations With Clinical Variables