Prognostic relevance of low-grade versus high-grade FIGO IB1 squamous cell uterine cervical carcinomas

FIGO IB1期低级别与高级别宫颈鳞状细胞癌的预后意义

阅读:2

Abstract

PURPOSE: Tumor grade is one of the more controversial factors with limited prognostic information in squamous cell carcinomas (SCC) of the uterine cervix. METHODS: Histologic slides of 233 surgically treated cervical SCC (FIGO IB1) were re-examined regarding the prognostic impact of the WHO-based grading system, using the different degree of keratinization, categorizing the tumors in G1, G2 and G3 (conventional tumor grade). RESULTS: 45.1% presented with well-differentiated tumors (G1), 29.2% with moderate (G2) and 25.8% with poor differentiation (G3). Tumor grade significantly correlated with decreased recurrence-free and overall survival. However, detailed analyses between G1- and G2-tumors failed to show any correlation with either recurrence-free or overall survival. G1- and G2-tumors were therefore merged into low-grade tumors and were compared to the high-grade group (G3-tumors). This binary conventional grading system showed an improved 5-years recurrence-free (low-grade: 90.2% vs. high-grade: 71.6%; p = 0.001) and overall survival rates (low-grade: 89.9% vs. high-grade: 71.1%; p = 0.001) for low-grade tumors. On multivariate analysis adjusted for lymph node metastasis, high-grade tumors represented a hazard ratio of 2.4 (95% CI 1.3-4.7) for reduced recurrence-free and 2.4 (95% CI 1.2-4.6) for overall survival. High-grade tumors showed a significantly higher risk for pelvic lymph node involvement [OR 2.7 (95% CI 1.4-5.5); p = 0.003]. The traditional three-tiered grading system failed to predict pelvic lymph node metastases. CONCLUSION: A binary grading model for the conventional tumor grade (based on the degree of keratinization) in SCC of the uterine cervix may allow a better prognostic discrimination than the traditionally used three-tiered system.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。