Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study

BMI, HGS, FFMI, and bedridden status were identified as practical indicators to efficiently screen patients likely to have PG-SGA scores ≥ 4.

Authors

Hongyan Yan (ORCID: https://orcid.org/0000-0001-5899-2426)
Yang Mingxue
Qian Gui (ORCID: https://orcid.org/0000-0002-4607-5601)
Huang Jiaxin
Yinfeng Li (ORCID: https://orcid.org/0000-0001-6820-8295)
Guiyu Huang
Cong Minghua
Xiaoli Tang (ORCID: https://orcid.org/0000-0001-7378-9848)
Liu Beijia

Institutions

University of Electronic Science and Technology of China (CN)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
Sichuan Cancer Hospital (CN)

Publication Details

Journal: BMC Cancer
Published: 2025-05-20
DOI: https://doi.org/10.1186/s12885-025-14222-9
Primary Topic: Biomarkers in Disease Mechanisms
Type: article
Field-Weighted Citation Impact: 0.00

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article

Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study

Hongyan Yan, Yang Mingxue, Qian Gui, Huang Jiaxin et al.

May 20, 2025

1 links

BMC Cancer

Biomarkers in Disease Mechanisms

article

Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study

Hongyan Yan, Yang Mingxue, Qian Gui, Huang Jiaxin, Yinfeng Li, Guiyu Huang, Cong Minghua, Xiaoli Tang, Liu Beijia

May 20, 2025article en

Abstract

BMI, HGS, FFMI, and bedridden status were identified as practical indicators to efficiently screen patients likely to have PG-SGA scores ≥ 4.

BMC CancerVol. 25(1)

University of Electronic Science and Technology of China (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Sichuan Cancer Hospital (CN)

Openalex Percentile: Top 87%

Biomarkers in Disease Mechanisms

DOI Open Access PDF OpenAlex

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Rapid identification of tumor patients with PG-SGA ≥ 4 based on machine learning: a prospective study — Hongyan Yan, Yang Mingxue, et al. · BMC Cancer (2025) | TGRS Research Map | TGRS