Evaluation of outcome and prognostic factors in 739 patients with uterine cervix carcinoma: a single institution experience

单中心经验:对739例子宫颈癌患者的结局和预后因素进行评估

阅读:2

Abstract

AIM OF THE STUDY: The aim of this retrospective chart review was to determine the long-term outcomes and identify prognostic factors that impact the survival of patients with cervical cancer. MATERIAL AND METHODS: A retrospective chart review of 739 patients with International Federation of Gynaecology and Obstetrics (FIGO) stage I-IV cervical cancer treated with surgery, radiation or chemoradiation was performed. Patient charts were evaluated in terms of demographics, clinical outcomes, and survival. Disease-free survival (DFS) and overall survival (OS) were calculated with the Kaplan-Meier method, and differences in survival were compared with the log-rank test. Multivariate analysis was performed with a Cox proportional hazards model to determine the estimated hazard ratios (HR) with 95% confidence intervals (CI) for each prognostic factor. RESULTS: The Cox proportional hazards model demonstrated that pelvic nodal metastasis (p = 0.018), parametrial invasion (p = 0.015), and presence of disease in the surgical margin (p = 0.011) were all independent prognostic factors for OS. The 5-year OS rate of patients with negative pelvic lymph nodes was 67.1%, which was higher than the rate for those with positive nodes at 49.0% (p < 0.05). The 5-year OS rate was 54.3% for patients with metastasis to the parametrium, 79.2% with a cancer-free parametrium, 60.9% with a cancer-positive surgical margin, 85.4% with a cancer-negative surgical margin, and 64.3% with a 1-3 mm close surgical margin (p < 0.05). CONCLUSIONS: Assessing pelvic lymph nodes, the parametrium, and surgical margins is important for survival and may aid in better identifying patients who would derive greater benefits from receiving adjuvant therapies and more aggressive treatments.

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。