Frontiers in Immunology (Mar 2023)

Lymphocyte-to-C reactive protein ratio as novel inflammatory marker for predicting outcomes in hemodialysis patients: A multicenter observational study

  • Xinpan Chen,
  • Wang Guo,
  • Zongli Diao,
  • Hongdong Huang,
  • Wenhu Liu

DOI
https://doi.org/10.3389/fimmu.2023.1101222
Journal volume & issue
Vol. 14

Abstract

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BackgroundPatients undergoing hemodialysis experience inflammation, which is associated with a higher risk of mortality. The lymphocyte-to-C reactive protein ratio (LCR) is a novel marker of inflammation that has been shown to predict mortality in patients with malignant cancer. However, the utility of LCR has not been evaluated in patients undergoing hemodialysis.MethodsWe performed a multi-center cohort study of 3,856 patients who underwent hemodialysis as part of the Beijing Hemodialysis Quality Control and Improvement Project between 1 January 2012 and December 2019. The relationship between LCR and all-cause mortality was assessed using a restricted cubic spline model and a multivariate Cox regression model. An outcome-oriented method was used to determine the most appropriate cut-off value of LCR. Subgroup analysis was also performed to evaluate the relationships of LCR with key parameters.ResultsOf the 3,856 enrolled patients, 1,581 (41%) were female, and their median age was 62 (53, 73) years. Over a median follow-up period of 75.1 months, 1,129 deaths occurred. The mortality rate for the patients after 60 months was 38.1% (95% confidence interval (CI) 36%–40.1%), resulting in a rate of 93.41 events per 1,000 patient-years. LCR showed an L-shaped dose-response relationship with all-cause mortality. The optimal cut-off point for LCR as a predictor of mortality in hemodialysis patients was 1513.1. An LCR of ≥1513.1 could independently predict mortality (hazard ratio 0.75, 95% CI 0.66–0.85, P<0.001).ConclusionsBaseline LCR was found to be an independent prognostic biomarker in patients undergoing hemodialysis. Implying that it should be a useful means of improving patient prognosis and judging the timing of appropriate interventions in routine clinical practice.

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