Authors' Reply: Novel Biomarkers in CKD

We thank Liang and colleagues for their thoughtful and supportive comments1 regarding our JASN study “Biomarkers of Kidney Failure and All-Cause Mortality in CKD.”2 Although we acknowledge their points regarding the lack of incremental benefit over established risk factors, including the absence of reclassification indices, we believe that a focus solely on incremental gains in risk prediction has often shaped a negative perception of CKD biomarker studies. We and others have shown that the kidney failure risk equation (KFRE) performs superbly as a predictor of progression to kidney failure (c-index approximately 0.9).3,4 Attempting to improve further on KFRE in this context is arguably unnecessary, and if used as the sole benchmark for assessing the clinical value of novel biomarkers, they will inevitably fail. Hence, we sought to investigate the clinically relevant question: What additional insights can these biomarkers provide beyond risk prediction alone? KFRE is a validated risk prediction tool, but of the predictors included, age and sex are unmodifiable, and eGFR primarily reflects past damage and proximity to the outcome. Thus, only albuminuria is potentially modifiable but is nonspecific, reflecting kidney damage from multiple mechanisms. With our parsimonious novel biomarker model, we have demonstrated comparably good risk prediction but based on potentially modifiable predictors that provide insight into disease mechanisms. While attempting to improve on KFRE in an advanced, undifferentiated CKD cohort may not be helpful, novel biomarkers may offer improved risk prediction in subgroups where KFRE performance is lower, such as earlier CKD3 and specific primary kidney diagnoses,5 an area we plan to explore in future work. We agree with the suggestions regarding the need for further studies. Although we mitigated the risk of false discovery by creating training and testing datasets, we will seek to validate our findings in other cohorts and also assess generalizability in populations with different ethnic composition and risk profiles. Liang et al.1 also raise important points about whether these biomarkers change with novel CKD therapies and their potential for guiding targeted treatment. Planned future analyses in the National Unified Renal Translational Research Enterprise (NURTuRE)-CKD cohort will examine follow-up biomarker measurements, the effects of treatments on biomarker changes, and their relationship to outcomes. In addition, we advocate for incorporating these biomarkers into interventional trials aimed at slowing CKD progression to assess biomarker response. Finally, we were asked to consider cost-effectiveness; this was partially addressed using the number needed to screen metric (Supplemental Table 24), but we agree that further studies are needed.

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Publication Details

Journal
Journal of the American Society of Nephrology
Published
2025-09-05
DOI
https://doi.org/10.1681/asn.0000000847
Primary Topic
Diabetes Treatment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Authors' Reply: Novel Biomarkers in CKD

Maarten W. Taal, Thomas McDonnell, Nicolas Vuilleumier, Philip A. Kalra
Journal of the American Society of Nephrology
Diabetes Treatment and Management
article

Authors' Reply: Novel Biomarkers in CKD

Maarten W. Taal, Thomas McDonnell, Nicolas Vuilleumier, Philip A. Kalra
article en

Abstract

We thank Liang and colleagues for their thoughtful and supportive comments1 regarding our JASN study “Biomarkers of Kidney Failure and All-Cause Mortality in CKD.”2 Although we acknowledge their points regarding the lack of incremental benefit over established risk factors, including the absence of reclassification indices, we believe that a focus solely on incremental gains in risk prediction has often shaped a negative perception of CKD biomarker studies. We and others have shown that the kidney failure risk equation (KFRE) performs superbly as a predictor of progression to kidney failure (c-index approximately 0.9).3,4 Attempting to improve further on KFRE in this context is arguably unnecessary, and if used as the sole benchmark for assessing the clinical value of novel biomarkers, they will inevitably fail. Hence, we sought to investigate the clinically relevant question: What additional insights can these biomarkers provide beyond risk prediction alone? KFRE is a validated risk prediction tool, but of the predictors included, age and sex are unmodifiable, and eGFR primarily reflects past damage and proximity to the outcome. Thus, only albuminuria is potentially modifiable but is nonspecific, reflecting kidney damage from multiple mechanisms. With our parsimonious novel biomarker model, we have demonstrated comparably good risk prediction but based on potentially modifiable predictors that provide insight into disease mechanisms. While attempting to improve on KFRE in an advanced, undifferentiated CKD cohort may not be helpful, novel biomarkers may offer improved risk prediction in subgroups where KFRE performance is lower, such as earlier CKD3 and specific primary kidney diagnoses,5 an area we plan to explore in future work. We agree with the suggestions regarding the need for further studies. Although we mitigated the risk of false discovery by creating training and testing datasets, we will seek to validate our findings in other cohorts and also assess generalizability in populations with different ethnic composition and risk profiles. Liang et al.1 also raise important points about whether these biomarkers change with novel CKD therapies and their potential for guiding targeted treatment. Planned future analyses in the National Unified Renal Translational Research Enterprise (NURTuRE)-CKD cohort will examine follow-up biomarker measurements, the effects of treatments on biomarker changes, and their relationship to outcomes. In addition, we advocate for incorporating these biomarkers into interventional trials aimed at slowing CKD progression to assess biomarker response. Finally, we were asked to consider cost-effectiveness; this was partially addressed using the number needed to screen metric (Supplemental Table 24), but we agree that further studies are needed.

Journal of the American Society of NephrologyVol. 37(1)
University of Nottingham (GB), University of Manchester (GB), University Hospital of Geneva (CH), Salford Royal Hospital (GB), University Hospitals of Derby and Burton NHS Foundation Trust (GB)
Openalex Percentile: Top 68%
Diabetes Treatment and Management
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