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Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients

PURPOSE: We aim to investigate the clinical significance of dynamic changes in the lymphocyte-to-monocyte ratio (LMR) and neutrophil-lymphocyte ratio (NLR) in peripheral blood at different time points combined with CEA in the prediction of postoperative-recurrence-in-patients with colorectal cancer...

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Autores principales: Chen, Shan, Zhang, Jie, Qian, Chengjia, Qi, Xiaowei, Mao, Yong, Lu, Tingxun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522459/
https://www.ncbi.nlm.nih.gov/pubmed/37772275
http://dx.doi.org/10.2147/JIR.S422500
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author Chen, Shan
Zhang, Jie
Qian, Chengjia
Qi, Xiaowei
Mao, Yong
Lu, Tingxun
author_facet Chen, Shan
Zhang, Jie
Qian, Chengjia
Qi, Xiaowei
Mao, Yong
Lu, Tingxun
author_sort Chen, Shan
collection PubMed
description PURPOSE: We aim to investigate the clinical significance of dynamic changes in the lymphocyte-to-monocyte ratio (LMR) and neutrophil-lymphocyte ratio (NLR) in peripheral blood at different time points combined with CEA in the prediction of postoperative-recurrence-in-patients with colorectal cancer (CRC). PATIENTS AND METHODS: This study collected 357 patients with stage I–III CRC between 2016 and April 2018. The dynamic changes from preoperative to postoperative LMR (p-LMR-p) and NLR (p-NLR-p) were analyzed using COX regression for multivariate analysis. Logistic regression was used to investigate whether the dynamic changes from post-treatment to pre-end of follow-up LMR (p-LMR-f) and NLR (p-NLR-f) were independent risk factors for CRC recurrence and to construct a predictive model. Internal validation using bootstrapping was performed to validate the discrimination ability of the model. The models’ discriminative effect, calibration degree, and clinical utility were assessed. RESULTS: In both the total cohort and the adjuvant therapy group, the dynamic changes of p-LMR-p (High-High vs Low-Low: p=0.006; HR:2.210, 95% CI: 1.256–3.890) were found to be independent prognostic factors for recurrence-free survival (RFS) in CRC patients. Additionally, logistic regression analysis revealed that N stage, CEA, LMR of pre-end of follow-up (f-LMR), and p-LMR-f were independent risk factors for CRC recurrence. In the total cohort, the p-LMR-f had an area under the curve (AUC) of 0.704, with a sensitivity of 64% and a specificity of 75.3%. By combining p-LMR-f with CEA, a predictive model was constructed, which showed an AUC of 0.913 (0.986–0.913) in the total cohort and an AUC of 0.924 (0.902–0.924) in the adjuvant therapy group during internal validation using bootstrapping. CONCLUSION: Dynamic changes in LMR can be used to predict the prognosis of CRC and serve as a biomarker for predicting CRC recurrence. Combined with CEA, it can improve the predictive performance for detecting CRC recurrence.
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spelling pubmed-105224592023-09-28 Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients Chen, Shan Zhang, Jie Qian, Chengjia Qi, Xiaowei Mao, Yong Lu, Tingxun J Inflamm Res Original Research PURPOSE: We aim to investigate the clinical significance of dynamic changes in the lymphocyte-to-monocyte ratio (LMR) and neutrophil-lymphocyte ratio (NLR) in peripheral blood at different time points combined with CEA in the prediction of postoperative-recurrence-in-patients with colorectal cancer (CRC). PATIENTS AND METHODS: This study collected 357 patients with stage I–III CRC between 2016 and April 2018. The dynamic changes from preoperative to postoperative LMR (p-LMR-p) and NLR (p-NLR-p) were analyzed using COX regression for multivariate analysis. Logistic regression was used to investigate whether the dynamic changes from post-treatment to pre-end of follow-up LMR (p-LMR-f) and NLR (p-NLR-f) were independent risk factors for CRC recurrence and to construct a predictive model. Internal validation using bootstrapping was performed to validate the discrimination ability of the model. The models’ discriminative effect, calibration degree, and clinical utility were assessed. RESULTS: In both the total cohort and the adjuvant therapy group, the dynamic changes of p-LMR-p (High-High vs Low-Low: p=0.006; HR:2.210, 95% CI: 1.256–3.890) were found to be independent prognostic factors for recurrence-free survival (RFS) in CRC patients. Additionally, logistic regression analysis revealed that N stage, CEA, LMR of pre-end of follow-up (f-LMR), and p-LMR-f were independent risk factors for CRC recurrence. In the total cohort, the p-LMR-f had an area under the curve (AUC) of 0.704, with a sensitivity of 64% and a specificity of 75.3%. By combining p-LMR-f with CEA, a predictive model was constructed, which showed an AUC of 0.913 (0.986–0.913) in the total cohort and an AUC of 0.924 (0.902–0.924) in the adjuvant therapy group during internal validation using bootstrapping. CONCLUSION: Dynamic changes in LMR can be used to predict the prognosis of CRC and serve as a biomarker for predicting CRC recurrence. Combined with CEA, it can improve the predictive performance for detecting CRC recurrence. Dove 2023-09-22 /pmc/articles/PMC10522459/ /pubmed/37772275 http://dx.doi.org/10.2147/JIR.S422500 Text en © 2023 Chen 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
Chen, Shan
Zhang, Jie
Qian, Chengjia
Qi, Xiaowei
Mao, Yong
Lu, Tingxun
Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients
title Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients
title_full Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients
title_fullStr Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients
title_full_unstemmed Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients
title_short Prognostic Value of Combined LMR and CEA Dynamic Monitoring in Postoperative Colorectal Cancer Patients
title_sort prognostic value of combined lmr and cea dynamic monitoring in postoperative colorectal cancer patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10522459/
https://www.ncbi.nlm.nih.gov/pubmed/37772275
http://dx.doi.org/10.2147/JIR.S422500
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