Preoperative magnetic resonance imaging criteria for predicting lymph node metastasis in patients with stage IB1-IIA2 cervical cancer

术前磁共振成像预测IB1-IIA2期宫颈癌患者淋巴结转移的标准

阅读:1

Abstract

OBJECTIVE: This study aimed to identify patients with stage IB1-IIA2 cervical cancer at low risk for lymph node metastasis (LNM) using preoperative magnetic resonance imaging (MRI) parameters. METHODS: Clinical and MRI data of patients with stage IB1-IIA2 cervical cancer who underwent radical surgery between 2010 and 2015 were retrospectively reviewed. Clinical stage IB1-IIA2 cervical cancer was diagnosed according to the 2009 International Federation of Gynecology and Obstetrics staging system. The low-risk criteria for LNM were identified using logistic regression analysis. The performance of the logistic regression analysis was estimated through receiver operating characteristic curve analysis. RESULTS: Of 453 patients, 105 (23.2%) exhibited pathological LNM (p-LNM). The maximal tumor diameter (adjusted odds ratio [aOR], 1.586; 95% confidence interval [CI], 1.312-1.916; p < 0.001) and LNM (aOR, 2.384; 95% CI, 1.418-4.007; p = 0.001) on preoperative MRI (m-LNM) were identified as independent risk factors for p-LNM using a multivariate logistic analysis. The p-LNM rate was 4.0% for low-risk patients (n = 124) identified using the current criteria (maximal tumor diameter <3.0 cm and no sign of m-LNM). The 5-year disease-free survival rate of low-risk patients was significantly greater than the rate of patients with a maximal tumor diameter ˃3.0 cm and/or signs of m-LNM (90.4% vs. 82.1%; p = 0.033). CONCLUSIONS: The low-risk criteria for p-LNM were a maximal tumor diameter <3.0 cm and no sign of m-LNM. Patients with stage IB1-IIA2 cervical cancer at low risk for m-LNM could be candidates for radical surgery; hence, they have a lesser need for adjuvant chemoradiotherapy, thus avoiding the severe comorbidities it causes.

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。