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Sakiko Nishio,Takuma Fujii,Hiroshi Nishio,Kaori Kameyama,Miyuki Saito,Takashi Iwata,Kaneyuki Kubushiro,Daisuke Aoki 대한부인종양학회 2013 Journal of Gynecologic Oncology Vol.24 No.3
Objective: In cervical intraepithelial neoplasia (CIN), p16INK4a immunohistochemistry has been reported to be a useful diagnostic biomarker. However, limited information is available about the association between the p16INK4a immunohistochemistry and the outcomes of CIN. Here, we report p16INK4a immunohistochemistry as an effective biomarker to predict the outcomes of CIN. Methods: p16INK4a immunohistochemistry was performed in patients with CIN from January 2000 to August 2009. Among these patients, we have performed a retrospective analysis of the medical records to evaluate the outcome of CIN 1-2 and performed statistical analysis to determine the correlation between p16INK4a expression and the outcomes. We also performed HPV genotyping and analyzed the relation between the infecting human papillomavirus (HPV) genotype and the outcomes. Results: A total of 244 patients, including 82 with CIN 1, 60 with CIN 2, and 102 with CIN 3, were examined. The rate of p16INK4a overexpression increased with increasing CIN grade, 20.7% for CIN 1, 80.0% for CIN 2, and 89.2% for CIN 3, with significant differences between CIN 1 and CIN 2-3 group. In the 131 CIN 1-2 patients, the progression rate was significantly higher for the patients showing p16INK4a overexpression than for those not showing p16INK4a overexpression (p=0.005); the regression rate was also found to be significantly lower for the patients showing p16INK4a overexpression (p=0.003). High-risk HPV genotypes were detected in 73 patients (73.7%). Both progression and regression rates were not significantly different between the high-risk HPV-positive and HPV-negative groups (p=0.401 and p=0.381, respectively). Conclusion: p16INK4a overexpression was correlated with the outcome of CIN 1-2, and p16INK4a is considered to be a superior biomarker for predicting the outcome of CIN 1-2 compared with HPV genotyping.