Onoja, Anthony; McDonnell, Thomas; Annessi, Isabelle; Banks, Rosamonde E; Bergin, Marianne; Cockwell, Paul; Dusaulcy, Rodolphe; ... Geifman, Nophar; + view all Onoja, Anthony; McDonnell, Thomas; Annessi, Isabelle; Banks, Rosamonde E; Bergin, Marianne; Cockwell, Paul; Dusaulcy, Rodolphe; Fraser, Simon DS; Johnson, Tim; Kalra, Philip A; Lemaître, Barbara; Saleem, Moin; Skroblin, Phillipp; Soderberg, Magnus; Taal, Maarten W; Unwin, Robert J; Vuilleumier, Nicolas; Wheeler, David C; Geifman, Nophar; - view fewer (2025) Biomarkers of Kidney Failure and All-Cause Mortality in CKD. Journal of the American Society of Nephrology 10.1681/ASN.0000000767. (In press).

Text biomarkers_of_kidney_failure_and_all_cause.683.pdf - Accepted Version Access restricted to UCL open access staff until 21 June 2026. Download (3MB)

Abstract

BACKGROUND: Chronic kidney disease (CKD) carries a variable risk for multiple adverse outcomes, highlighting the need for a personalised approach. This study evaluated several novel biomarkers linked to key disease mechanisms to predict the risk of kidney failure (first event of eGFR <15 ml/min/1.73m2 or kidney replacement therapy), all-cause mortality, and a composite of both. METHODS: We included 2,884 adults with non-dialysis CKD from 16 nephrology centres across the UK. Twenty-one biomarkers associated with kidney damage, fibrosis, inflammation, and cardiovascular disease were analysed in urine, plasma, or serum. Cox proportional hazards models were used to assess biomarker associations and develop risk prediction models. RESULTS: Participants had mean age 63 (15) years, 58% were male and 87% White. Median eGFR 35 (25, 47) ml/min/1.73m2, and median urinary albumin-to-creatinine ratio (UACR) 197 (32, 895) mg/g. During median 48 (33, 55) months follow-up, 680 kidney failure events and 414 all-cause mortality events occurred. For kidney failure, a model combining three biomarkers (sTNFR1, sCD40, UCOL1A1) showed good discrimination (c-index 0.86, 95% CI: 0.83-0.89) but was outperformed by a model using established risk factors (age, sex, ethnicity, eGFR, UACR; c-index 0.90, 95% CI: 0.88-0.92). For all-cause mortality, a model using three biomarkers (hs-cTnT, NT-proBNP, suPAR) demonstrated equivalent discrimination (c-index 0.80, 95% CI: 0.75-0.84) to an established risk factor model (c-index 0.80, 95% CI: 0.76-0.84).For the composite outcome, the biomarker model discrimination (C-index 0.78, 95% CI: 0.76, 0.81) was numerically higher than for established risk factors (C-index 0.77, 95% CI: 0.74, 0.80), and the addition of biomarkers to the established risk factors led to a small but statistically significant improvement in discrimination (C-index 0.80, 95% CI: 0.77, 0.82; p value < 0.01). CONCLUSIONS: Risk prediction models incorporating novel biomarkers showed comparable discrimination to established risk factors for kidney failure and all-cause mortality.

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