| Title |
Risk model in stage IB1-IIB cervical cancer with positive node after radical hysterectomy
|
|---|---|
| Published in |
OncoTargets and therapy, May 2016
|
| DOI | 10.2147/ott.s94151 |
| Pubmed ID | |
| Authors |
Zhilan Chen, Kecheng Huang, Zhiyong Lu, Song Deng, Jiaqiang Xiong, Jia Huang, Xiong Li, Fangxu Tang, Zhihao Wang, Haiying Sun, Lin Wang, Shasha Zhou, Xiaoli Wang, Yao Jia, Ting Hu, Juan Gui, Dongyi Wan, Ding Ma, Shuang Li, Shixuan Wang |
| Abstract |
The purpose of this study was to identify risk factors in patients with surgically treated node-positive IB1-IIB cervical cancer and to establish a risk model for disease-free survival (DFS) and overall survival (OS). A total of 170 patients who underwent radical hysterectomy and bilateral pelvic lymphadenectomy as primary treatment for node-positive International Federation of Gynaecology and Obstetrics (FIGO) stage IB1-IIB cervical cancer from January 2002 to December 2008 were retrospectively analyzed. Five published risk models were evaluated in this population. The variables, including common iliac lymph node metastasis and parametrial invasion, were independent predictors of outcome in a multivariate analysis using a Cox regression model. Three distinct prognostic groups (low, intermediate, and high risk) were defined using these variables. Five-year DFS rates for the low-, intermediate-, and high-risk groups were 73.7%, 60.0%, and 25.0%, respectively (P<0.001), and 5-year OS rates were 81.9%, 42.8%, and 25.0%, respectively (P<0.001). The risk model derived in this study provides a novel means for assessing prognosis of patients with node-positive stage IB1-IIB cervical cancer. Future study will focus on external validation of the model and refinement of the risk scoring systems by adding new biologic markers. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 2 | 15% |
| Researcher | 2 | 15% |
| Student > Bachelor | 2 | 15% |
| Other | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 2 | 15% |
| Biochemistry, Genetics and Molecular Biology | 2 | 15% |
| Nursing and Health Professions | 1 | 8% |
| Materials Science | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 6 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 May 2016.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from OncoTargets and therapy
#1,146
of 3,016 outputs
Outputs of similar age
#191,104
of 311,864 outputs
Outputs of similar age from OncoTargets and therapy
#44
of 123 outputs
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