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The performance of three nutritional tools varied in colorectal cancer patients: a retrospective analysis

  • Author Footnotes
    1 The authors contributed equally to this paper.
    Xiaoli Ruan
    Footnotes
    1 The authors contributed equally to this paper.
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Author Footnotes
    1 The authors contributed equally to this paper.
    Xiaonan Wang
    Footnotes
    1 The authors contributed equally to this paper.
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Qi Zhang
    Affiliations
    Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
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  • Rena Nakyeyune
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Yi Shao
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Yi Shen
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Chen Niu
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Lingyan Zhu
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Zhaoping Zang
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Tong Wei
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Xi Zhang
    Affiliations
    Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
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  • Guotian Ruan
    Affiliations
    Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
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  • Mengmeng Song
    Affiliations
    Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
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  • Toni Miles
    Affiliations
    Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
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  • Fen Liu
    Correspondence
    Corresponding author. Capital Medical University, No.10 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing 100069, China. Tel.: +86-10-83911497.
    Affiliations
    Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
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  • Hanping Shi
    Correspondence
    Corresponding author. Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, No.10, Tie Medical Road, Yangfangdian, Haidian District, Beijing, 100038, China. Tel.: +86-10-63926985.
    Affiliations
    Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China

    Department of Oncology, Capital Medical University, Beijing, 100038, China

    Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China
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  • Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) Group
  • Author Footnotes
    1 The authors contributed equally to this paper.

      Highlights

      • Imperfect reference standard has been proved to lead to biased estimates of diagnostic accuracy.
      • This study used the Bayesian latent class model (LCM) to evaluate the sensitivity and specificity of the GLIM criteria, NRS-2002, and PG-SGA, which adjusted the imperfect gold standard bias.
      • Survival analyses showed the association between nutritional status and overall survival of colorectal cancer patients.
      • Harrell's concordance index showed all these three tools improved the TNM staging system for survival prediction.

      Abstract

      Background and Objective

      Nutritional screening tools should be sensitive, simple, and easy to use. Differing opinions among clinicians concern the simplicity of the three tools—the Global Leadership Initiative on Malnutrition (GLIM) criteria, Nutritional Risk Screening 2002 (NRS-2002), and Patient-Generated Subjective Global Assessment (PG-SGA). For each tool, we estimated prediction of overall survival (OS) in tumor staging, sensitivity, and specificity. The NRS-2002 is favored by clinicians because it is simple to use. We compared its sensitivity and specificity with the GLIM and PG-SGA.

      Study Design and Setting

      This is an analysis of data from 1,358 adult colorectal cancer patients recruited in a multicenter from July 2013 to July 2018.

      Results

      In Kaplan–Meier models, each tool was found to be significantly predictive of OS: NRS-2002 (1.28), GLIM (1.49), and PG-SGA (1.42). Use of any tool improved prediction of survival at tumor staging. NRS-2002 has superior specificity (0.90) to diagnose patients without nutritional deficits (GLIM = 0.62 and PG-SGA = 0.82).

      Conclusion

      This study provides evidence for the superiority of NRS-2002 to accurately identify colorectal cancer patients without nutritional limitations. Compared with the complexity of the other tools, NRS-2002 is the simplest tool to use in routine nutritional screening in busy clinical practice.

      Keywords

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