Predictors of para-aortic lymph node metastasis based on pathological diagnosis via surgical staging in patients with locally advanced cervical cancer: A multicenter study

Para-aortic lymph node (PALN) metastasis of patients with locally advanced cervical cancer (LACC) is associated with multiple risk factors. This study aimed to identify risk factors and develop a predictive model for PALN metastasis based on the pathological diagnosis via surgical staging to determine the patient-population suitable for extended-field irradiation (EFRT) and clarify the prognosis of patients with LACC. Five parameters were identified as predictors by logistic regression analysis. The predictive model was displayed as a nomogram and then modified into a simple scoring system. The concordance indices for the prediction nomogram were 0.939 in the training cohort, and 0.954 in the validation cohort, respectively. The scoring system consisted of tumor size, histological type, number of pelvic lymph nodes (PLNs), common iliac lymph node, and shorter diameter of the largest PLN. With a cutoff value of 8 points, the sensitivity and specificity of the predictive model were 91.04 % and 85.37 %, respectively, in the training cohort, and 89.47 % and 84.68 %, respectively, in the validation cohort. Using this system, patients were divided into high- and low-risk groups. Patients in the high-risk group showed a greater likelihood of PALN metastasis and worse PFS and OS than those in the low-risk group. The predictive model displays promise for the pathological diagnosis of PALN via surgical staging, offering good accuracy. It provides a non-invasive, practical tool to guide precise radiation strategy and stratify prognosis of patients with LACC.

Authors

Institutions

Publication Details

Journal
Cancer Letters
Published
2025-02-15
DOI
https://doi.org/10.1016/j.canlet.2025.217545
Citations
4
Primary Topic
Endometrial and Cervical Cancer Treatments
Type
article
Field-Weighted Citation Impact
8.23

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictors of para-aortic lymph node metastasis based on pathological diagnosis via surgical staging in patients with locally advanced cervical cancer: A multicenter study

Yue Huang, Mingfang Guo, Ying Tang, Dongling Zou et al.
4 citations
Cancer Letters
Endometrial and Cervical Cancer Treatments
8.23
article

Predictors of para-aortic lymph node metastasis based on pathological diagnosis via surgical staging in patients with locally advanced cervical cancer: A multicenter study

Yue Huang, Mingfang Guo, Ying Tang, Dongling Zou, Misi He, Haike Lei, Xiang Zhang, Jing Wang, Lei Li, Qi Zhou, Liang Du, Xiuying Li, Qiaoling Li, Hao He, Qian Zheng, Yun Dang
article en
4 citations

Abstract

Para-aortic lymph node (PALN) metastasis of patients with locally advanced cervical cancer (LACC) is associated with multiple risk factors. This study aimed to identify risk factors and develop a predictive model for PALN metastasis based on the pathological diagnosis via surgical staging to determine the patient-population suitable for extended-field irradiation (EFRT) and clarify the prognosis of patients with LACC. Five parameters were identified as predictors by logistic regression analysis. The predictive model was displayed as a nomogram and then modified into a simple scoring system. The concordance indices for the prediction nomogram were 0.939 in the training cohort, and 0.954 in the validation cohort, respectively. The scoring system consisted of tumor size, histological type, number of pelvic lymph nodes (PLNs), common iliac lymph node, and shorter diameter of the largest PLN. With a cutoff value of 8 points, the sensitivity and specificity of the predictive model were 91.04 % and 85.37 %, respectively, in the training cohort, and 89.47 % and 84.68 %, respectively, in the validation cohort. Using this system, patients were divided into high- and low-risk groups. Patients in the high-risk group showed a greater likelihood of PALN metastasis and worse PFS and OS than those in the low-risk group. The predictive model displays promise for the pathological diagnosis of PALN via surgical staging, offering good accuracy. It provides a non-invasive, practical tool to guide precise radiation strategy and stratify prognosis of patients with LACC.

Cancer LettersVol. 616
Chongqing University (CN), Zhejiang Cancer Hospital (CN), Gansu Provincial Maternal and Child Health Hospital (CN), Cancer Hospital of Chinese Academy of Medical Sciences (CN), Chongqing Cancer Hospital (CN), Hangzhou Cancer Hospital (CN)
Chongqing Science and Technology Commission
Good health and well-being
Openalex Percentile: Top 3%
Endometrial and Cervical Cancer Treatments
8.23
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.