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Meta-Analysis
. 2024 Dec 20;19(12):e0316070.
doi: 10.1371/journal.pone.0316070. eCollection 2024.

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

Menghao Yang  1 , Na Xiao  1 , Le Tang  1 , Yang Zhang  1 , Yuexiu Wen  2 , Xiuqin Yang  1   2
Affiliations
Meta-Analysis

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

Menghao Yang et al. PLoS One. .

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

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Conflict of interest statement

The authors assert that there are no conflicts of interest in the conduct of this study.

Figures

Fig 1
Fig 1. Flow chart of study selection for inclusion in the meta-analysis.
Fig 2
Fig 2. Risk assessment of included studies using QUADAS.
(a) Risk of bias and applicability concerns summary: review authors’ judgments about each domain for each included study. (b) Risk of bias and applicability concerns graph: review authors’ judgments about each domain presented as percentages across included studies.
Fig 3
Fig 3. Hierarchical summary receiver operating characteristic (HSROC) curves.
(a) MUST. (b) MST. (c) NRS-2002. (d) MNA-SF. (e) NRI. (f) PG-SGA. MUST, Malnutrition Universal Screening Tool; MST, Malnutrition Screening Tool; NRS-2002, Nutritional Risk Screening 2002; MNA-SF, Mini Nutritional Assessment-Short Form; NRI, Nutritional Risk Index; PG-SGA, Patient-Generated Subjective Global Assessment.
Fig 4
Fig 4. Forest plot for sensitivity and specificity.
(a) MUST. (b) MST. (c) MNA-SF. (d) NRI. (e) NRS-2002. (f) PG-SGA. MUST, Malnutrition Universal Screening Tool; MST, Malnutrition Screening Tool; NRS-2002, Nutritional Risk Screening 2002; MNA-SF, Mini Nutritional Assessment-Short Form; NRI, Nutritional Risk Index; PG-SGA, Patient-Generated Subjective Global Assessment.
Fig 5
Fig 5. Fagan plot analysis.
(a) MUST. (b) MUT. (c) NRS-2002. (d) MNA-SF. (e) NRI. (f) PG-SGA. MUST, Malnutrition Universal Screening Tool; MST, Malnutrition Screening Tool; NRS-2002, Nutritional Risk Screening 2002; MNA-SF, Mini Nutritional Assessment-Short Form; NRI, Nutritional Risk Index; PG-SGA, Patient-Generated Subjective Global Assessment.
Fig 6
Fig 6. Deeks’ funnel plot.
(a) MUST. (b) MST. (c) NRS-2002. (d) MNA-SF. (e) NRI. (f) PG-SGA. MUST, Malnutrition Universal Screening Tool; MST, Malnutrition Screening Tool; NRS-2002, Nutritional Risk Screening 2002; MNA-SF, Mini Nutritional Assessment-Short Form; NRI, Nutritional Risk Index; PG-SGA, Patient-Generated Subjective Global Assessment.
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