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A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study

BACKGROUND: This study aimed to develop an innovative inflammation-nutrition biomarker score (INS) system to stratify the prognoses of patients with cancer. METHODS: A total of 5,221 patients with cancer from multiple centers in China between June 2010 and December 2017 were enrolled in this prospec...

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Autores principales: Xie, Hailun, Ruan, Guotian, Wei, Lishuang, Zhang, Heyang, Zhang, Qi, Ge, Yizhong, Lin, Shiqi, Song, Mengmeng, Zhang, Xi, Liu, Xiaoyue, Zhang, Xiaowei, Li, Xiangrui, Zhang, Kangping, Yang, Ming, Tang, Meng, Deng, Li, Shi, Hanping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749281/
https://www.ncbi.nlm.nih.gov/pubmed/36517779
http://dx.doi.org/10.1186/s12885-022-10399-5
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author Xie, Hailun
Ruan, Guotian
Wei, Lishuang
Zhang, Heyang
Zhang, Qi
Ge, Yizhong
Lin, Shiqi
Song, Mengmeng
Zhang, Xi
Liu, Xiaoyue
Zhang, Xiaowei
Li, Xiangrui
Zhang, Kangping
Yang, Ming
Tang, Meng
Deng, Li
Shi, Hanping
author_facet Xie, Hailun
Ruan, Guotian
Wei, Lishuang
Zhang, Heyang
Zhang, Qi
Ge, Yizhong
Lin, Shiqi
Song, Mengmeng
Zhang, Xi
Liu, Xiaoyue
Zhang, Xiaowei
Li, Xiangrui
Zhang, Kangping
Yang, Ming
Tang, Meng
Deng, Li
Shi, Hanping
author_sort Xie, Hailun
collection PubMed
description BACKGROUND: This study aimed to develop an innovative inflammation-nutrition biomarker score (INS) system to stratify the prognoses of patients with cancer. METHODS: A total of 5,221 patients with cancer from multiple centers in China between June 2010 and December 2017 were enrolled in this prospective cohort study. We compared the commonly used inflammation and nutrition biomarkers and selected the most valuable to develop the novel INS system. Survival curves were assessed using the Kaplan–Meier method and the log-rank test to evaluate the difference in survival rates between groups. The Cox proportional hazards model was used to investigate the association between biomarkers and all-cause mortality. RESULTS: As the risk stratification of INS increased (1 to 5), the rate of death for cancer patients gradually increased (25.43% vs. 37.09% vs. 44.59% vs. 56.21% vs. 61.65%, p < 0.001). The INS system was associated with all-cause mortality in patients with cancer. Patients with both high inflammation and nutrition risk (INS = 5) were estimated to have much worse prognosis than those with neither (HR, 2.606; 95%CI, 2.261–3.003, p < 0.001). Subsequently, the results of randomized internal validation also confirmed that INS system had an ideal effect in identifying adverse outcomes. In addition, the INS system could be used as a supplement to pathological stages in prognosis assessment, and had a higher predictive value in comparison with the constitute biomarkers. Patients with a high INS had less functional ability, reduced quality of life, and were at high risk of malnutrition, cachexia, and poor short-term outcomes. CONCLUSION: The INS system based on inflammation and nutrition biomarkers is a simple and effective prognostic stratification tool for patients with cancer, which can provide a valuable reference for clinical prognosis assessment and treatment strategy formulation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10399-5.
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spelling pubmed-97492812022-12-15 A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study Xie, Hailun Ruan, Guotian Wei, Lishuang Zhang, Heyang Zhang, Qi Ge, Yizhong Lin, Shiqi Song, Mengmeng Zhang, Xi Liu, Xiaoyue Zhang, Xiaowei Li, Xiangrui Zhang, Kangping Yang, Ming Tang, Meng Deng, Li Shi, Hanping BMC Cancer Research BACKGROUND: This study aimed to develop an innovative inflammation-nutrition biomarker score (INS) system to stratify the prognoses of patients with cancer. METHODS: A total of 5,221 patients with cancer from multiple centers in China between June 2010 and December 2017 were enrolled in this prospective cohort study. We compared the commonly used inflammation and nutrition biomarkers and selected the most valuable to develop the novel INS system. Survival curves were assessed using the Kaplan–Meier method and the log-rank test to evaluate the difference in survival rates between groups. The Cox proportional hazards model was used to investigate the association between biomarkers and all-cause mortality. RESULTS: As the risk stratification of INS increased (1 to 5), the rate of death for cancer patients gradually increased (25.43% vs. 37.09% vs. 44.59% vs. 56.21% vs. 61.65%, p < 0.001). The INS system was associated with all-cause mortality in patients with cancer. Patients with both high inflammation and nutrition risk (INS = 5) were estimated to have much worse prognosis than those with neither (HR, 2.606; 95%CI, 2.261–3.003, p < 0.001). Subsequently, the results of randomized internal validation also confirmed that INS system had an ideal effect in identifying adverse outcomes. In addition, the INS system could be used as a supplement to pathological stages in prognosis assessment, and had a higher predictive value in comparison with the constitute biomarkers. Patients with a high INS had less functional ability, reduced quality of life, and were at high risk of malnutrition, cachexia, and poor short-term outcomes. CONCLUSION: The INS system based on inflammation and nutrition biomarkers is a simple and effective prognostic stratification tool for patients with cancer, which can provide a valuable reference for clinical prognosis assessment and treatment strategy formulation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-10399-5. BioMed Central 2022-12-14 /pmc/articles/PMC9749281/ /pubmed/36517779 http://dx.doi.org/10.1186/s12885-022-10399-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Xie, Hailun
Ruan, Guotian
Wei, Lishuang
Zhang, Heyang
Zhang, Qi
Ge, Yizhong
Lin, Shiqi
Song, Mengmeng
Zhang, Xi
Liu, Xiaoyue
Zhang, Xiaowei
Li, Xiangrui
Zhang, Kangping
Yang, Ming
Tang, Meng
Deng, Li
Shi, Hanping
A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
title A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
title_full A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
title_fullStr A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
title_full_unstemmed A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
title_short A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
title_sort novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749281/
https://www.ncbi.nlm.nih.gov/pubmed/36517779
http://dx.doi.org/10.1186/s12885-022-10399-5
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