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A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study

BACKGROUND & AIMS: Lymphocyte-C-reactive Protein Ratio (LCR) has been demonstrated as a promising new marker for predicting surgical and oncological outcomes in colorectal carcinoma (CRC). However, anastomotic leakage (AL) is also likely related to this inflammatory marker. Herein, we aimed to i...

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Autores principales: Zhong, Bin, Lin, Zhen-Yu, Ma, Dan-Dan, Shang, Zuo-Hong, Shen, Yan-Bin, Zhang, Tao, Zhang, Jian-Xin, Jin, Wei-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308913/
https://www.ncbi.nlm.nih.gov/pubmed/35870933
http://dx.doi.org/10.1186/s12893-022-01734-5
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author Zhong, Bin
Lin, Zhen-Yu
Ma, Dan-Dan
Shang, Zuo-Hong
Shen, Yan-Bin
Zhang, Tao
Zhang, Jian-Xin
Jin, Wei-Dong
author_facet Zhong, Bin
Lin, Zhen-Yu
Ma, Dan-Dan
Shang, Zuo-Hong
Shen, Yan-Bin
Zhang, Tao
Zhang, Jian-Xin
Jin, Wei-Dong
author_sort Zhong, Bin
collection PubMed
description BACKGROUND & AIMS: Lymphocyte-C-reactive Protein Ratio (LCR) has been demonstrated as a promising new marker for predicting surgical and oncological outcomes in colorectal carcinoma (CRC). However, anastomotic leakage (AL) is also likely related to this inflammatory marker. Herein, we aimed to identify preoperative predictors of AL and build and develop a novel model able to identify patients at risk of developing AL. METHODS: We collected 858 patients with CRC undergoing elective radical operation between 2007 and 2018 at a single center were retrospectively reviewed. We performed univariable and multivariable analyses and built a multivariable model that predicts AL based on preoperative factors. Propensity adjustment was used to correct the bias introduced by non-random matching of the LCR. The model's performance was evaluated by using the area under the receiver operator characteristic curves (AUROCs), decision curve analysis (DCA), Brier scores, D statistics, and R2 values. RESULTS: Age, nutrition risk screening 2002 (NRS2002) score, tumor location and LCR, together with hemoglobin < 90 g/l, were independent predictors of AL. The models built on these variables showed good performance (internal validation: c-statistic = 0.851 (95%CI 0.803–0.965), Brier score = 0.049; temporal validation: c-statistic = 0.777 (95%CI 0.823–0.979), Brier score = 0.096). A regression equation to predict the AL was also established by multiple linear regression analysis: [Age(≥ 60 year) × 1.281] + [NRS2002(≥ 3) × 1.341] + [Tumor location(pt.) × 1.348]-[LCR(≤ 6000) × 1.593]-[Hemoglobin(< 90 g/L) × 1.589]-6.12. CONCLUSION: Preoperative LCR is an independent predictive factor for AL. A novel model combining LCR values, age, tumor location, and NRS2002 provided an excellent preoperative prediction of AL in patients with CRC. The nomogram can help clinical decision-making and support future research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12893-022-01734-5.
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spelling pubmed-93089132022-07-25 A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study Zhong, Bin Lin, Zhen-Yu Ma, Dan-Dan Shang, Zuo-Hong Shen, Yan-Bin Zhang, Tao Zhang, Jian-Xin Jin, Wei-Dong BMC Surg Research BACKGROUND & AIMS: Lymphocyte-C-reactive Protein Ratio (LCR) has been demonstrated as a promising new marker for predicting surgical and oncological outcomes in colorectal carcinoma (CRC). However, anastomotic leakage (AL) is also likely related to this inflammatory marker. Herein, we aimed to identify preoperative predictors of AL and build and develop a novel model able to identify patients at risk of developing AL. METHODS: We collected 858 patients with CRC undergoing elective radical operation between 2007 and 2018 at a single center were retrospectively reviewed. We performed univariable and multivariable analyses and built a multivariable model that predicts AL based on preoperative factors. Propensity adjustment was used to correct the bias introduced by non-random matching of the LCR. The model's performance was evaluated by using the area under the receiver operator characteristic curves (AUROCs), decision curve analysis (DCA), Brier scores, D statistics, and R2 values. RESULTS: Age, nutrition risk screening 2002 (NRS2002) score, tumor location and LCR, together with hemoglobin < 90 g/l, were independent predictors of AL. The models built on these variables showed good performance (internal validation: c-statistic = 0.851 (95%CI 0.803–0.965), Brier score = 0.049; temporal validation: c-statistic = 0.777 (95%CI 0.823–0.979), Brier score = 0.096). A regression equation to predict the AL was also established by multiple linear regression analysis: [Age(≥ 60 year) × 1.281] + [NRS2002(≥ 3) × 1.341] + [Tumor location(pt.) × 1.348]-[LCR(≤ 6000) × 1.593]-[Hemoglobin(< 90 g/L) × 1.589]-6.12. CONCLUSION: Preoperative LCR is an independent predictive factor for AL. A novel model combining LCR values, age, tumor location, and NRS2002 provided an excellent preoperative prediction of AL in patients with CRC. The nomogram can help clinical decision-making and support future research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12893-022-01734-5. BioMed Central 2022-07-23 /pmc/articles/PMC9308913/ /pubmed/35870933 http://dx.doi.org/10.1186/s12893-022-01734-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhong, Bin
Lin, Zhen-Yu
Ma, Dan-Dan
Shang, Zuo-Hong
Shen, Yan-Bin
Zhang, Tao
Zhang, Jian-Xin
Jin, Wei-Dong
A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
title A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
title_full A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
title_fullStr A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
title_full_unstemmed A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
title_short A preoperative prediction model based on Lymphocyte-C-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
title_sort preoperative prediction model based on lymphocyte-c-reactive protein ratio predicts postoperative anastomotic leakage in patients with colorectal carcinoma: a retrospective study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308913/
https://www.ncbi.nlm.nih.gov/pubmed/35870933
http://dx.doi.org/10.1186/s12893-022-01734-5
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