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Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model

OBJECTIVE: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model. METHODS: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to...

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Autores principales: Wang, Keli, Li, Meijiao, Liu, Rui, Ji, Yang, Yan, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343466/
https://www.ncbi.nlm.nih.gov/pubmed/35928989
http://dx.doi.org/10.2147/CMAR.S364875
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author Wang, Keli
Li, Meijiao
Liu, Rui
Ji, Yang
Yan, Jin
author_facet Wang, Keli
Li, Meijiao
Liu, Rui
Ji, Yang
Yan, Jin
author_sort Wang, Keli
collection PubMed
description OBJECTIVE: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model. METHODS: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AL after AR. A nomogram risk prediction model was established based on the selected independent risk factors and the predictive performance of nomogram was evaluated. RESULTS: A 1013 patients undergoing laparoscopic AR were included, of which 67 had AL, with an incidence of 6.6%. Univariate and multivariate logistic regression analyses showed that male gender, tumors distance from the anus verge of ≤ 5cm, tumors distance from the anus verge of 5–10cm, circumferential tumor growth, operation time ≥ 240min, and no diverting stoma were independent risk factors for AL after AR. A nomogram prediction model was established based on these results. The calibration curve showed that the predicted occurrence probability of the nomogram model was in good agreement with the actual occurrence probability. The area under the receiver operating characteristic (ROC) curve was 0.749. CONCLUSION: The nomogram prediction model based on the independent risk factors of patients undergoing AL after AR can effectively predict the probability of AL.
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spelling pubmed-93434662022-08-03 Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model Wang, Keli Li, Meijiao Liu, Rui Ji, Yang Yan, Jin Cancer Manag Res Original Research OBJECTIVE: To explore the risk factors of anastomotic leakage (AL) after laparoscopic anterior resection (AR) of rectal cancer and establish a nomogram prediction model. METHODS: Clinical and surgical data of patients who underwent AR of rectal cancer at Sichuan Cancer Hospital from January 2017 to December 2020 were retrospectively collected. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AL after AR. A nomogram risk prediction model was established based on the selected independent risk factors and the predictive performance of nomogram was evaluated. RESULTS: A 1013 patients undergoing laparoscopic AR were included, of which 67 had AL, with an incidence of 6.6%. Univariate and multivariate logistic regression analyses showed that male gender, tumors distance from the anus verge of ≤ 5cm, tumors distance from the anus verge of 5–10cm, circumferential tumor growth, operation time ≥ 240min, and no diverting stoma were independent risk factors for AL after AR. A nomogram prediction model was established based on these results. The calibration curve showed that the predicted occurrence probability of the nomogram model was in good agreement with the actual occurrence probability. The area under the receiver operating characteristic (ROC) curve was 0.749. CONCLUSION: The nomogram prediction model based on the independent risk factors of patients undergoing AL after AR can effectively predict the probability of AL. Dove 2022-07-28 /pmc/articles/PMC9343466/ /pubmed/35928989 http://dx.doi.org/10.2147/CMAR.S364875 Text en © 2022 Wang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wang, Keli
Li, Meijiao
Liu, Rui
Ji, Yang
Yan, Jin
Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model
title Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model
title_full Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model
title_fullStr Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model
title_full_unstemmed Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model
title_short Analysis of Risk Factors for Anastomotic Leakage After Laparoscopic Anterior Resection of Rectal Cancer and Construction of a Nomogram Prediction Model
title_sort analysis of risk factors for anastomotic leakage after laparoscopic anterior resection of rectal cancer and construction of a nomogram prediction model
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343466/
https://www.ncbi.nlm.nih.gov/pubmed/35928989
http://dx.doi.org/10.2147/CMAR.S364875
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