Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.

<h4>Background</h4>Cancer, particularly tumors of the digestive system, presents a major global health challenge. The incidence and mortality rates of these cancers are increasing, and many patients face significant nutritional risks, which are often overlooked in clinical practice. This...

Full description

Saved in:
Bibliographic Details
Main Authors: Menghao Yang, Na Xiao, Le Tang, Yang Zhang, Yuexiu Wen, Xiuqin Yang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0316070
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1841555499631247360
author Menghao Yang
Na Xiao
Le Tang
Yang Zhang
Yuexiu Wen
Xiuqin Yang
author_facet Menghao Yang
Na Xiao
Le Tang
Yang Zhang
Yuexiu Wen
Xiuqin Yang
author_sort Menghao Yang
collection DOAJ
description <h4>Background</h4>Cancer, particularly tumors of the digestive system, presents a major global health challenge. The incidence and mortality rates of these cancers are increasing, and many patients face significant nutritional risks, which are often overlooked in clinical practice. This oversight can lead to serious health consequences, underscoring the need for effective nutritional assessment tools to improve clinical outcomes. Although several nutritional risk screening tools exist, their specific utility for patients with gastrointestinal tumors remains unclear. This study aimed to address this gap by systematically evaluating the performance of various nutritional screening tools in this patient population.<h4>Methods</h4>A systematic search of six databases was conducted to identify studies that met predefined inclusion and exclusion criteria. Diagnostic test metrics such as sensitivity, specificity, and likelihood ratios (positive and negative) were estimated using a hierarchical summary receiver operating characteristic model. This approach was used to compare the accuracy of different nutritional screening scales.<h4>Results</h4>A total of 33 eligible studies were included in this meta-analysis, assessing six nutritional screening tools: the Malnutrition Universal Screening Tool, Malnutrition Screening Tool, Nutritional Risk Screening 2002, Mini Nutritional Assessment-Short Form, Nutritional Risk Index, and Patient-Generated Subjective Global Assessment. Among these, the Patient-Generated Subjective Global Assessment demonstrated the highest performance, with a sensitivity of 0.911 (95% confidence interval: 0.866-0.942) and a specificity of 0.805 (95% confidence interval: 0.674-0.891), outperforming the other screening tools.<h4>Conclusions</h4>This study confirms the effectiveness of the Patient-Generated Subjective Global Assessment in identifying malnutrition risk among patients with digestive system tumors. However, as this research focused on a Chinese population, future studies should encompass a broader geographic scope and work toward standardized assessment criteria to enhance the global validation and refinement of nutritional screening tools.
format Article
id doaj-art-f9817e7a1f804901ba42e9a08bf4ae9e
institution Kabale University
issn 1932-6203
language English
publishDate 2024-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS ONE
spelling doaj-art-f9817e7a1f804901ba42e9a08bf4ae9e2025-01-08T05:32:44ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031607010.1371/journal.pone.0316070Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.Menghao YangNa XiaoLe TangYang ZhangYuexiu WenXiuqin Yang<h4>Background</h4>Cancer, particularly tumors of the digestive system, presents a major global health challenge. The incidence and mortality rates of these cancers are increasing, and many patients face significant nutritional risks, which are often overlooked in clinical practice. This oversight can lead to serious health consequences, underscoring the need for effective nutritional assessment tools to improve clinical outcomes. Although several nutritional risk screening tools exist, their specific utility for patients with gastrointestinal tumors remains unclear. This study aimed to address this gap by systematically evaluating the performance of various nutritional screening tools in this patient population.<h4>Methods</h4>A systematic search of six databases was conducted to identify studies that met predefined inclusion and exclusion criteria. Diagnostic test metrics such as sensitivity, specificity, and likelihood ratios (positive and negative) were estimated using a hierarchical summary receiver operating characteristic model. This approach was used to compare the accuracy of different nutritional screening scales.<h4>Results</h4>A total of 33 eligible studies were included in this meta-analysis, assessing six nutritional screening tools: the Malnutrition Universal Screening Tool, Malnutrition Screening Tool, Nutritional Risk Screening 2002, Mini Nutritional Assessment-Short Form, Nutritional Risk Index, and Patient-Generated Subjective Global Assessment. Among these, the Patient-Generated Subjective Global Assessment demonstrated the highest performance, with a sensitivity of 0.911 (95% confidence interval: 0.866-0.942) and a specificity of 0.805 (95% confidence interval: 0.674-0.891), outperforming the other screening tools.<h4>Conclusions</h4>This study confirms the effectiveness of the Patient-Generated Subjective Global Assessment in identifying malnutrition risk among patients with digestive system tumors. However, as this research focused on a Chinese population, future studies should encompass a broader geographic scope and work toward standardized assessment criteria to enhance the global validation and refinement of nutritional screening tools.https://doi.org/10.1371/journal.pone.0316070
spellingShingle Menghao Yang
Na Xiao
Le Tang
Yang Zhang
Yuexiu Wen
Xiuqin Yang
Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.
PLoS ONE
title Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.
title_full Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.
title_fullStr Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.
title_full_unstemmed Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.
title_short Evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors: A hierarchical Bayesian latent class meta-analysis.
title_sort evaluating the accuracy of a nutritional screening tool for patients with digestive system tumors a hierarchical bayesian latent class meta analysis
url https://doi.org/10.1371/journal.pone.0316070
work_keys_str_mv AT menghaoyang evaluatingtheaccuracyofanutritionalscreeningtoolforpatientswithdigestivesystemtumorsahierarchicalbayesianlatentclassmetaanalysis
AT naxiao evaluatingtheaccuracyofanutritionalscreeningtoolforpatientswithdigestivesystemtumorsahierarchicalbayesianlatentclassmetaanalysis
AT letang evaluatingtheaccuracyofanutritionalscreeningtoolforpatientswithdigestivesystemtumorsahierarchicalbayesianlatentclassmetaanalysis
AT yangzhang evaluatingtheaccuracyofanutritionalscreeningtoolforpatientswithdigestivesystemtumorsahierarchicalbayesianlatentclassmetaanalysis
AT yuexiuwen evaluatingtheaccuracyofanutritionalscreeningtoolforpatientswithdigestivesystemtumorsahierarchicalbayesianlatentclassmetaanalysis
AT xiuqinyang evaluatingtheaccuracyofanutritionalscreeningtoolforpatientswithdigestivesystemtumorsahierarchicalbayesianlatentclassmetaanalysis