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A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy

OBJECTIVE: To investigate the predictive merit of combined preoperative nutritional condition and systemic inflammation on the prognosis of patients receiving esophagectomy, with the assessment of model construction to extract a multidisciplinary phantom having clinical relevance and suitability. ME...

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Autores principales: Chen, LiangLiang, Yu, GuoCan, Zhao, WuChen, Ye, Bo, Shu, YuSheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10201727/
https://www.ncbi.nlm.nih.gov/pubmed/37211596
http://dx.doi.org/10.1186/s12957-023-03020-x
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author Chen, LiangLiang
Yu, GuoCan
Zhao, WuChen
Ye, Bo
Shu, YuSheng
author_facet Chen, LiangLiang
Yu, GuoCan
Zhao, WuChen
Ye, Bo
Shu, YuSheng
author_sort Chen, LiangLiang
collection PubMed
description OBJECTIVE: To investigate the predictive merit of combined preoperative nutritional condition and systemic inflammation on the prognosis of patients receiving esophagectomy, with the assessment of model construction to extract a multidisciplinary phantom having clinical relevance and suitability. METHODS: The software of R 4.1.2 was utilized to acquire the survival optimal truncation value and the confusion matrix of survival for the continuity variables. SPSS Statistics 26 was employed to analyze the correlation of parameters, where including t-test, ANOVA and the nonparametric rank sum test shall. Pearson chi-square test was used for categorical variables. The survival curve was retrieved by Kaplan–Meier method. Univariate analysis of overall survival (OS) was performed through log-rank test. Cox analysis was for survival analyze. The performance of the prediction phantom through the area under curve (AUC) of receiver operating characteristic curve (ROC), decision curve analysis (DCA), nomogram and clinical impact curve (CIC) was plotted by R. RESULTS: The AUC value of albumin-globulin score and skeletal muscle index (CAS) is markedly superior. Patients with diminished AGS and greater SMI were associated with improved overall survival (OS) and recurrence-free survival (RFS) (P < 0.01). The CAS composite evaluation model was calibrated with better accuracy and predictive performance. The DCA and CIC indicated a relatively higher net revenue for the prediction model. CONCLUSIONS: The prediction model including the CAS score has excellent accuracy, a high net revenue, and favorable prediction function. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-023-03020-x.
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spelling pubmed-102017272023-05-23 A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy Chen, LiangLiang Yu, GuoCan Zhao, WuChen Ye, Bo Shu, YuSheng World J Surg Oncol Research OBJECTIVE: To investigate the predictive merit of combined preoperative nutritional condition and systemic inflammation on the prognosis of patients receiving esophagectomy, with the assessment of model construction to extract a multidisciplinary phantom having clinical relevance and suitability. METHODS: The software of R 4.1.2 was utilized to acquire the survival optimal truncation value and the confusion matrix of survival for the continuity variables. SPSS Statistics 26 was employed to analyze the correlation of parameters, where including t-test, ANOVA and the nonparametric rank sum test shall. Pearson chi-square test was used for categorical variables. The survival curve was retrieved by Kaplan–Meier method. Univariate analysis of overall survival (OS) was performed through log-rank test. Cox analysis was for survival analyze. The performance of the prediction phantom through the area under curve (AUC) of receiver operating characteristic curve (ROC), decision curve analysis (DCA), nomogram and clinical impact curve (CIC) was plotted by R. RESULTS: The AUC value of albumin-globulin score and skeletal muscle index (CAS) is markedly superior. Patients with diminished AGS and greater SMI were associated with improved overall survival (OS) and recurrence-free survival (RFS) (P < 0.01). The CAS composite evaluation model was calibrated with better accuracy and predictive performance. The DCA and CIC indicated a relatively higher net revenue for the prediction model. CONCLUSIONS: The prediction model including the CAS score has excellent accuracy, a high net revenue, and favorable prediction function. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-023-03020-x. BioMed Central 2023-05-22 /pmc/articles/PMC10201727/ /pubmed/37211596 http://dx.doi.org/10.1186/s12957-023-03020-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Chen, LiangLiang
Yu, GuoCan
Zhao, WuChen
Ye, Bo
Shu, YuSheng
A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
title A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
title_full A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
title_fullStr A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
title_full_unstemmed A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
title_short A possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
title_sort possible combined appraisal pattern: predicting the prognosis of patients after esophagectomy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10201727/
https://www.ncbi.nlm.nih.gov/pubmed/37211596
http://dx.doi.org/10.1186/s12957-023-03020-x
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