Inflammatory Burden Index: A Superior Prognostic Biomarker of Systemic Inflammation in Patients on Peritoneal Dialysis

J Inflamm Res. 2024 Dec 11:17:10913-10927. doi: 10.2147/JIR.S393291. eCollection 2024.

Abstract

Purpose: Systemic inflammation biomarkers, derived from routine blood tests, have been demonstrated to be associated with prognosis of patients undergoing peritoneal dialysis (PD). However, studies focusing on the comparisons of their role on predictive efficacy for prognosis of PD patient are limited and results are inconsistent. The purpose of this study was to evaluate the prognostic value of various systemic inflammation biomarkers and to identify the optimal one in PD patients.

Patients and methods: This longitudinal study involved 3,225 patients undergoing PD across China. The prognostic accuracy of systemic inflammatory biomarkers was evaluated using C-statistics. Independent prognostic biomarkers of outcomes were determined using multivariate Cox proportional hazards regression analysis.

Results: During a 46-month follow-up, 829 (25.7%) patients died, with 458 (55.3%) deaths attributed to cardiovascular disease (CVD). The highest C-statistics were observed for the IBI, with 0.619 and 0.621 for all-cause and CVD mortality, respectively. The optimal threshold of the IBI for predicting prognosis in patients undergoing PD was 50.0. An elevated IBI was a significant independent predictor of all-cause mortality, with a 1-SD increase associated with higher risks of all-cause and CVD mortality. Participants in the upper two quartiles of IBI exhibited increased risks of all-cause mortality by 41.2% and 67.6%, respectively, compared to those in the lowest quartile. Similar results were observed for CVD mortality.

Conclusion: The IBI is a superior prognostic indicator of survival and could be broadly applied for prognosis of patients undergoing PD. Elevated IBI is an independent risk factor for all-cause and CVD mortality.

Keywords: biomarker; peritoneal dialysis; prognosis; systemic inflammation.

Grants and funding

This work was supported by the Project of Jiangmen Science and Technology Bureau, China. (2024YL01002, 2024YL01004) and the Key Project of Jiangmen Basic and Applied Basic Research (No.2320002000884).