4.0 Article

Multiplex Serum Biomarker Assays Improve Prediction of Renal and Mortality Outcomes in Chronic Kidney Disease

期刊

KIDNEY360
卷 2, 期 8, 页码 1225-1239

出版社

AMER SOC NEPHROLOGY
DOI: 10.34067/KID.0007552020

关键词

chronic kidney disease; biomarkers; C3a-desArg; end stage renal disease; machine learning; mortality; multiplex assays; neutrophil gelatinase-associated lipocalin; renal function decline; soluble tumor necrosis factor receptor

资金

  1. Enterprise Ireland Innovation Partnership grant [IP-2013-0248]
  2. Randox Teoranta Ltd.
  3. Wellcome Trust
  4. Health Research Board
  5. Health and Social Care, Research and Development Division, Northern Ireland [203930/B/16/Z]
  6. Molecular Medicine Ireland Clinical and Translational Research Scholarship - Government of Ireland Programme for Research in Third Level Institutions, Cycle5 (PRTLI5)
  7. College of Medicine, Nursing and Health Sciences, National University of Ireland Galway
  8. College of Medicine, Nursing and Health Science, National University of Ireland Galway Hardiman Scholarship
  9. Irish Endocrine Society/Royal College of Physicians of Ireland research bursary
  10. Health Research Board Emerging Investigator Award [EIA 2017-017]
  11. European Commission [634086]
  12. Science Foundation Ireland [09/SRC-B1794, 13/RC/2073]
  13. European Regional Development Fund
  14. Health Research Board (HRB) [EIA-2017-017] Funding Source: Health Research Board (HRB)

向作者/读者索取更多资源

In this study, the predictive value of 11 serum biomarkers for renal and mortality outcomes in CKD patients was investigated. Random forests trained on serum biomarkers showed better performance in predicting the composite end point compared to clinical variables. Patients with high soluble TNF receptor-1 and neutrophil gelatinase-associated lipocalin, coupled with low complement 3a des-arginine, had high adverse event rates over a 5-year follow-up period.
Background We investigated the predictive value of 11 serum biomarkers for renal and mortality end points in people with CKD. Methods Adults with CKD (n=139) were enrolled from outpatient clinics between February 2014 and November 2016. Biomarker quantification was performed using two multiplex arrays on a clinical-grade analyzer. Relationships between biomarkers and renal and mortality end points were investigated by random forests and Cox proportional hazards regression. Results The cohort was 56% male. The mean age was 63 years and median (IQR) CKD-EPI eGFR was 33 (24-51) ml/min per BSA. A total of 56 (40%) people developed a composite end point defined as >= 40% decline in eGFR, doubling of serum creatinine, RRT, or death over median (IQR) follow-up of 5.4 (4.7-5.7) years. Prediction of the composite end point was better with random forests trained on serum biomarkers compared with clinical variables (area under the curve of 0.81 versus 0.78). The predictive performance of biomarkers was further enhanced when considered alongside clinical variables (area under the curve of 0.83 versus 0.81 for biomarkers alone). Patients (n=27, 19%) with high soluble TNF receptor-1(>= 3 ng/ml) and neutrophil gelatinase-associated lipocalin (>= 156 ng/ml), coupled with low complement 3a des-arginine (< 2368 ng/ml), almost universally (96%) developed the composite renal and mortality end point. C-reactive protein (adjusted hazard ratio, 1.4; 95% CI, 1.1 to 1.8), neutrophil gelatinase-associated lipocalin (adjusted hazard ratio, 2.8; 95% CI, 1.3 to 6.1) and complement 3a des-arginine (adjusted hazard ratio, 0.6; 95% CI, 0.4 to 0.96) independently predicted time to the composite end point. Conclusions Outpatients with the triad of high soluble TNF receptor-1 and neutrophil gelatinase-associated lipocalin coupled with low complement 3a des-arginine had high adverse event rates over 5-year follow-up. Incorporation of serum biomarkers alongside clinical variables improved prediction of CKD progression and mortality. Our findings require confirmation in larger, more diverse patient cohorts.

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