Multiplex Serum Biomarker Assays Improve Prediction of Renal and Mortality Outcomes in Chronic Kidney Disease
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Published on: July 14, 2023
William P Martin1, Chloe Conroy2, Serika D Naicker3
1Diabetes Complications Research Centre, School of Medicine, Conway Institute, University College Dublin, Dublin, Ireland.
Insights
Serum biomarkers can predict kidney disease progression and mortality in CKD patients. Combining biomarkers with clinical data improves prediction accuracy for adverse events.
Area of Science:
- Nephrology
- Biomarker Discovery
- Predictive Analytics
Background:
- Chronic kidney disease (CKD) poses significant risks for renal decline and mortality.
- Identifying reliable predictors of adverse outcomes in CKD is crucial for patient management.
Purpose of the Study:
- To evaluate the predictive capability of 11 serum biomarkers for renal and mortality endpoints in individuals with CKD.
- To assess the added value of serum biomarkers when combined with clinical variables for predicting CKD progression.
Main Methods:
- A cohort of 139 CKD outpatients was analyzed.
- Serum biomarkers were quantified using multiplex arrays.
- Random forests and Cox regression models were employed to investigate associations with renal and mortality endpoints.
Main Results:
- Random forests using serum biomarkers outperformed clinical variables in predicting a composite endpoint (AUC 0.81 vs. 0.78).
- Combining biomarkers and clinical variables further improved prediction (AUC 0.83).
- A specific triad of high soluble TNF receptor-1, high neutrophil gelatinase-associated lipocalin, and low complement 3a des-arginine was associated with a 96% adverse event rate.
Conclusions:
- The combination of specific serum biomarkers can significantly enhance the prediction of CKD progression and mortality.
- Incorporating these biomarkers alongside clinical data offers a more robust predictive model.
- Further validation in larger, diverse populations is warranted.
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 desarginine (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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