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New nomogram for predicting lymph node positivity in pancreatic head cancer

BACKGROUND: Pancreatic cancer is one of the most malignant cancers worldwide, and it mostly occurs in the head of the pancreas. Existing laparoscopic pancreaticoduodenectomy (LPD) surgical techniques have has undergone a learning curve, a wide variety of approaches for the treatment of pancreatic ca...

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Autores principales: Guo, Xingren, Song, Xiangyang, Long, Xiaoyin, Liu, Yahui, Xie, Yixin, Xie, Cheng, Ji, Bai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907461/
https://www.ncbi.nlm.nih.gov/pubmed/36761960
http://dx.doi.org/10.3389/fonc.2023.1053375
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author Guo, Xingren
Song, Xiangyang
Long, Xiaoyin
Liu, Yahui
Xie, Yixin
Xie, Cheng
Ji, Bai
author_facet Guo, Xingren
Song, Xiangyang
Long, Xiaoyin
Liu, Yahui
Xie, Yixin
Xie, Cheng
Ji, Bai
author_sort Guo, Xingren
collection PubMed
description BACKGROUND: Pancreatic cancer is one of the most malignant cancers worldwide, and it mostly occurs in the head of the pancreas. Existing laparoscopic pancreaticoduodenectomy (LPD) surgical techniques have has undergone a learning curve, a wide variety of approaches for the treatment of pancreatic cancer have been proposed, and the operation has matured. At present, pancreatic head cancer has been gradually changing from “surgeons’ evaluation of anatomical resection” to “biologically inappropriate resection”. In this study, the risk of lymph node metastasis in pancreatic head cancer was predicted using common preoperative clinical indicators. METHODS: The preoperative clinical data of 191 patients with pancreatic head cancer who received LPD in the First Affiliated Hospital of Jilin University from May 2016 to December 2021 were obtained. A univariate regression analysis study was conducted, and the indicators with a significance level of P<0.05 were included in the univariate logistic regression analysis into multivariate. Lastly, a nomogram was built based on age, tumor size, leucocyte,albumin(ALB), and lymphocytes/monocytes(LMR). The model with the highest resolution was selected by obtaining the area under a curve. The clinical net benefit of the prediction model was examined using decision curve analyses.Risk stratification was performed by combining preoperative CT scan with existing models. RESULTS: Multivariate logistic regression analysis found age, tumor size, WBC, ALB, and LMR as five independent factors. A nomogram model was constructed based on the above indicators. The model was calibrated by validating the calibration curve within 1000 bootstrap resamples. The ROC curve achieved an AUC of 0.745(confidence interval of 95%: 0.673-0.816), thus indicating that the model had excellent discriminative skills. DCA suggested that the predictive model achieved a high net benefit in the nearly entire threshold probability range. CONCLUSIONS: This study has been the first to investigate a nomogram for preoperative prediction of lymphatic metastasis in pancreatic head cancer. The result suggests that age, ALB, tumor size, WBC, and LMR are independent risk factors for lymph node metastasis in pancreatic head cancer. This study may provide a novel perspective for the selection of appropriate continuous treatment regimens, the increase of the survival rate of patients with pancreatic head cancer, and the selection of appropriate neoadjuvant therapy patients.
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spelling pubmed-99074612023-02-08 New nomogram for predicting lymph node positivity in pancreatic head cancer Guo, Xingren Song, Xiangyang Long, Xiaoyin Liu, Yahui Xie, Yixin Xie, Cheng Ji, Bai Front Oncol Oncology BACKGROUND: Pancreatic cancer is one of the most malignant cancers worldwide, and it mostly occurs in the head of the pancreas. Existing laparoscopic pancreaticoduodenectomy (LPD) surgical techniques have has undergone a learning curve, a wide variety of approaches for the treatment of pancreatic cancer have been proposed, and the operation has matured. At present, pancreatic head cancer has been gradually changing from “surgeons’ evaluation of anatomical resection” to “biologically inappropriate resection”. In this study, the risk of lymph node metastasis in pancreatic head cancer was predicted using common preoperative clinical indicators. METHODS: The preoperative clinical data of 191 patients with pancreatic head cancer who received LPD in the First Affiliated Hospital of Jilin University from May 2016 to December 2021 were obtained. A univariate regression analysis study was conducted, and the indicators with a significance level of P<0.05 were included in the univariate logistic regression analysis into multivariate. Lastly, a nomogram was built based on age, tumor size, leucocyte,albumin(ALB), and lymphocytes/monocytes(LMR). The model with the highest resolution was selected by obtaining the area under a curve. The clinical net benefit of the prediction model was examined using decision curve analyses.Risk stratification was performed by combining preoperative CT scan with existing models. RESULTS: Multivariate logistic regression analysis found age, tumor size, WBC, ALB, and LMR as five independent factors. A nomogram model was constructed based on the above indicators. The model was calibrated by validating the calibration curve within 1000 bootstrap resamples. The ROC curve achieved an AUC of 0.745(confidence interval of 95%: 0.673-0.816), thus indicating that the model had excellent discriminative skills. DCA suggested that the predictive model achieved a high net benefit in the nearly entire threshold probability range. CONCLUSIONS: This study has been the first to investigate a nomogram for preoperative prediction of lymphatic metastasis in pancreatic head cancer. The result suggests that age, ALB, tumor size, WBC, and LMR are independent risk factors for lymph node metastasis in pancreatic head cancer. This study may provide a novel perspective for the selection of appropriate continuous treatment regimens, the increase of the survival rate of patients with pancreatic head cancer, and the selection of appropriate neoadjuvant therapy patients. Frontiers Media S.A. 2023-01-25 /pmc/articles/PMC9907461/ /pubmed/36761960 http://dx.doi.org/10.3389/fonc.2023.1053375 Text en Copyright © 2023 Guo, Song, Long, Liu, Xie, Xie and Ji https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Guo, Xingren
Song, Xiangyang
Long, Xiaoyin
Liu, Yahui
Xie, Yixin
Xie, Cheng
Ji, Bai
New nomogram for predicting lymph node positivity in pancreatic head cancer
title New nomogram for predicting lymph node positivity in pancreatic head cancer
title_full New nomogram for predicting lymph node positivity in pancreatic head cancer
title_fullStr New nomogram for predicting lymph node positivity in pancreatic head cancer
title_full_unstemmed New nomogram for predicting lymph node positivity in pancreatic head cancer
title_short New nomogram for predicting lymph node positivity in pancreatic head cancer
title_sort new nomogram for predicting lymph node positivity in pancreatic head cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907461/
https://www.ncbi.nlm.nih.gov/pubmed/36761960
http://dx.doi.org/10.3389/fonc.2023.1053375
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