International Journal of General Medicine (Jun 2024)

Diagnostic Value of Nutritional Risk Index and Other Indices for Predicting Sarcopenia in the Middle-Aged and Elderly Population of China Without Cancer: A ROC Curve Analysis

  • Zou JF,
  • Li ST,
  • Wang LP,
  • Zhou NL,
  • Ran JJ,
  • Yang X,
  • Tian CH,
  • Liu YT,
  • Liu Y,
  • Peng W

Journal volume & issue
Vol. Volume 17
pp. 2527 – 2538

Abstract

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Jing-Feng Zou,* Shao-Tian Li,* Li-Ping Wang,* Nian-Li Zhou, Jia-Jia Ran, Xin Yang, Chun-Hui Tian, Yi-Ting Liu, Yun Liu, Wen Peng Department of General Practice, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, WuHan, Hubei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yun Liu; Wen Peng, Department of General Practice, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jie Fang Avenue, WuHan, Hubei, 1227, People’s Republic of China, Email [email protected]; [email protected]: Emerging evidence suggests that systemic inflammatory and nutritional biomarkers, along with derived indices, could serve as predictors for sarcopenia in cancer population. This study aimed to compare these predictors, focusing on the nutritional risk index (NRI) and evaluate its diagnostic value, for sarcopenic patients without cancer.Methods: This cross-sectional retrospective study included 1674 participants. Sarcopenia is defined by skeletal muscle mass index (SMI). Laboratory data reflected the values of systemic inflammatory and nutritional biomarkers, from which the derived indices were calculated. Multiple logistic regression analysis, ROC curve analysis, and the Youden index were utilized to assess the association between these markers and sarcopenia and determine the cutoff value for predicting sarcopenia.Results: Among all participants (1110 men and 564 women, mean age 61.97 ± 9.83 years), 398 individuals were diagnosed with sarcopenia, indicating a prevalence of 23.78% in China’s middle-aged and elderly population without cancer. Logistic regression analysis revealed significant associations between all biomarkers and derived indices with sarcopenia. Following adjustment for potential confounders, lower NRI values were significantly associated with a higher incidence of sarcopenia. For sarcopenia diagnosis, the area under the curve (AUC) for NRI was 0.769 ([95% CI, 0.742, 0.796], P < 0.001), with a cutoff value of 106.016, sensitivity of 75.6% and specificity of 66.1%. NRI demonstrated greater predictive advantage for sarcopenia incidence in men compared to women.Conclusion: A lower NRI value was associated with a higher prevalence of sarcopenia. NRI shows promise for early, rapid, and effective sarcopenia screening, particularly in China’s middle-aged and elderly male population without cancer.Keywords: sarcopenia, systemic inflammation, nutritional risk index, NRI

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