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A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma

Introduction: Renal cell carcinoma (RCC) is one of the most common urinary tumors. The risk of metastasis for patients with RCC is about 1/3, among which 30–40% have lymph node metastasis, and the existence of lymph node metastasis will greatly reduce the survival rate of patients. However, the nece...

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Autores principales: Sun, Jian-Xuan, Liu, Chen-Qian, Zhang, Zong-Biao, Xia, Qi-Dong, Xu, Jin-Zhou, An, Ye, Xu, Meng-Yao, Zhong, Xing-Yu, Zeng, Na, Ma, Si-Yang, He, Hao-Dong, Guan, Wei, Wang, Shao-Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866659/
https://www.ncbi.nlm.nih.gov/pubmed/36675368
http://dx.doi.org/10.3390/jcm12020441
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author Sun, Jian-Xuan
Liu, Chen-Qian
Zhang, Zong-Biao
Xia, Qi-Dong
Xu, Jin-Zhou
An, Ye
Xu, Meng-Yao
Zhong, Xing-Yu
Zeng, Na
Ma, Si-Yang
He, Hao-Dong
Guan, Wei
Wang, Shao-Gang
author_facet Sun, Jian-Xuan
Liu, Chen-Qian
Zhang, Zong-Biao
Xia, Qi-Dong
Xu, Jin-Zhou
An, Ye
Xu, Meng-Yao
Zhong, Xing-Yu
Zeng, Na
Ma, Si-Yang
He, Hao-Dong
Guan, Wei
Wang, Shao-Gang
author_sort Sun, Jian-Xuan
collection PubMed
description Introduction: Renal cell carcinoma (RCC) is one of the most common urinary tumors. The risk of metastasis for patients with RCC is about 1/3, among which 30–40% have lymph node metastasis, and the existence of lymph node metastasis will greatly reduce the survival rate of patients. However, the necessity of lymph node dissection is still controversial at present. Therefore, a new predictive model is urgently needed to judge the risk of lymph node metastasis and guide clinical decision making before operation. Method: We retrospectively collected the data of 189 patients who underwent retroperitoneal lymph node dissection or enlarged lymph node resection due to suspected lymph node metastasis or enlarged lymph nodes found during an operation in Tongji Hospital from January 2016 to October 2021. Univariate and multivariate logistic regression and least absolute shrinkage and selection operator (lasso) regression analyses were used to identify preoperative predictors of pathological lymph node positivity. A nomogram was established to predict the probability of lymph node metastasis in patients with RCC before surgery according to the above independent predictors, and its efficacy was evaluated with a calibration curve and a DCA analysis. Result: Among the 189 patients, 54 (28.60%) were pN1 patients, and 135 (71.40%) were pN0 patients. Three independent impact factors were, finally, identified, which were the following: age (OR = 0.3769, 95% CI = 0.1864–0.7622, p < 0.01), lymph node size according to pre-operative imaging (10–20 mm: OR = 15.0040, 95% CI = 1.5666–143.7000, p < 0.05; >20 mm: OR = 4.4013, 95% CI = 1.4892–7.3134, p < 0.01) and clinical T stage (cT1–2 vs. cT3–4) (OR = 3.1641, 95% CI = 1.0336–9.6860, p < 0.05). The calibration curve and DCA (Decision Curve Analysis) showed the nomogram of this predictive model had good fitting. Conclusions: Low age, large lymph node size in pre-operative imaging and high clinical T stage can be used as independent predictive factors of pathological lymph node metastasis in patients with RCC. Our predictive nomogram using these factors exhibited excellent discrimination and calibration.
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spelling pubmed-98666592023-01-22 A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma Sun, Jian-Xuan Liu, Chen-Qian Zhang, Zong-Biao Xia, Qi-Dong Xu, Jin-Zhou An, Ye Xu, Meng-Yao Zhong, Xing-Yu Zeng, Na Ma, Si-Yang He, Hao-Dong Guan, Wei Wang, Shao-Gang J Clin Med Article Introduction: Renal cell carcinoma (RCC) is one of the most common urinary tumors. The risk of metastasis for patients with RCC is about 1/3, among which 30–40% have lymph node metastasis, and the existence of lymph node metastasis will greatly reduce the survival rate of patients. However, the necessity of lymph node dissection is still controversial at present. Therefore, a new predictive model is urgently needed to judge the risk of lymph node metastasis and guide clinical decision making before operation. Method: We retrospectively collected the data of 189 patients who underwent retroperitoneal lymph node dissection or enlarged lymph node resection due to suspected lymph node metastasis or enlarged lymph nodes found during an operation in Tongji Hospital from January 2016 to October 2021. Univariate and multivariate logistic regression and least absolute shrinkage and selection operator (lasso) regression analyses were used to identify preoperative predictors of pathological lymph node positivity. A nomogram was established to predict the probability of lymph node metastasis in patients with RCC before surgery according to the above independent predictors, and its efficacy was evaluated with a calibration curve and a DCA analysis. Result: Among the 189 patients, 54 (28.60%) were pN1 patients, and 135 (71.40%) were pN0 patients. Three independent impact factors were, finally, identified, which were the following: age (OR = 0.3769, 95% CI = 0.1864–0.7622, p < 0.01), lymph node size according to pre-operative imaging (10–20 mm: OR = 15.0040, 95% CI = 1.5666–143.7000, p < 0.05; >20 mm: OR = 4.4013, 95% CI = 1.4892–7.3134, p < 0.01) and clinical T stage (cT1–2 vs. cT3–4) (OR = 3.1641, 95% CI = 1.0336–9.6860, p < 0.05). The calibration curve and DCA (Decision Curve Analysis) showed the nomogram of this predictive model had good fitting. Conclusions: Low age, large lymph node size in pre-operative imaging and high clinical T stage can be used as independent predictive factors of pathological lymph node metastasis in patients with RCC. Our predictive nomogram using these factors exhibited excellent discrimination and calibration. MDPI 2023-01-05 /pmc/articles/PMC9866659/ /pubmed/36675368 http://dx.doi.org/10.3390/jcm12020441 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sun, Jian-Xuan
Liu, Chen-Qian
Zhang, Zong-Biao
Xia, Qi-Dong
Xu, Jin-Zhou
An, Ye
Xu, Meng-Yao
Zhong, Xing-Yu
Zeng, Na
Ma, Si-Yang
He, Hao-Dong
Guan, Wei
Wang, Shao-Gang
A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma
title A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma
title_full A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma
title_fullStr A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma
title_full_unstemmed A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma
title_short A Novel Predictive Model of Pathological Lymph Node Metastasis Constructed with Preoperative Independent Predictors in Patients with Renal Cell Carcinoma
title_sort novel predictive model of pathological lymph node metastasis constructed with preoperative independent predictors in patients with renal cell carcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866659/
https://www.ncbi.nlm.nih.gov/pubmed/36675368
http://dx.doi.org/10.3390/jcm12020441
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