Using the Difference Between Estimated Glomerular Filtration Rate by Cystatin C and Creatinine to Improve Mortality Risk Prediction in Elderly Patients With CKD in the HUNT Study - PubMed (original) (raw)

Using the Difference Between Estimated Glomerular Filtration Rate by Cystatin C and Creatinine to Improve Mortality Risk Prediction in Elderly Patients With CKD in the HUNT Study

O Alison Potok et al. Kidney Med. 2025.

Abstract

Rationale & objective: The discrepancy in estimated glomerular filtration rate by cystatin C (eGFRcys) versus creatinine (eGFRcr) has been used as a surrogate for sarcopenia. We studied whether this eGFRcys - eGFRcr difference could improve prediction of kidney failure versus death, which is important in the management of patients with chronic kidney disease (CKD). We hypothesized that it improved the death prediction but not that of kidney failure.

Study design: A five-year cohort study to assess prognostic accuracy.

Setting & participants: The population included 1,146 participants with creatinine (cr) and cystatin C (cys) measurements from the population-based the Nord-Trøndelag Health Study, Norway. Those aged ≤ 65 years or with estimated glomerular filtration rate (eGFR)cr ≥ 45 mL/min/1.73m2 were excluded.

Exposures: The mortality risk equation in patients with CKD (MREK) includes age, sex, eGFRcr, albuminuria, smoking status, history of stroke, diabetes, and heart failure. The kidney failure risk equation includes age, sex, eGFRcr, and albuminuria.

Outcomes: Kidney failure or death at 5 years.

Analytical approach: The performances of MREK and kidney failure risk equation with and without eGFR_diff (= eGFRcys - eGFRcr) were compared: calibration (likelihood ratio, Akaike information criterion, Brier score), discrimination (C-statistics), reclassification (net reclassification improvement and integrated discrimination improvement).

Results: The mean ± SD age was 80 ± 7 years, 42% were men, the mean eGFRcr was 36 ± 8 and eGFR_diff was 1.04 ± 12 mL/min/1.73m2; 42 participants (4%) reached kidney failure and 444 (39%) died. C-statistics (95% CI) for MREK improved with eGFR_diff from 70.1% (66.7-73.4) to 73.0% (69.8-76.1) (P = 0.003). The proportion of participants correctly reclassified also improved (net reclassification improvement 14% [10%-17%]), and the separation between the average predicted risk for participants who died versus not (integrated discrimination improvement +0.03 [ 0.02-0.04]).

Limitations: Untested generalizability in other populations.

Conclusions: Including eGFR_diff into the kidney failure risk and mortality risk equations significantly improved mortality risk prediction, but not kidney failure, in patients with CKD. Serum creatinine level is influenced by many non-GFR determinants, including sarcopenia, and the discrepancy of creatinine versus cystatin C could be helpful in predialytic decision-making.

Keywords: Discrepancy; KFRE; cystatin C; eGFR; kidney failure; mortality; risk estimation.

Plain language summary

Patients with chronic kidney disease have a higher mortality risk than those without chronic kidney disease. They are also at risk of kidney failure, which can be treated with dialysis, but this requires preparation. Being able to discriminate between the risk of kidney failure and the risk of death is essential to best prepare patients for the future. The difference in kidney function by 2 markers (cystatin vs creatinine), cystatin C-based eGFR minus creatinine-based eGFR (eGFR_diff), has been shown to be associated with frailty and poor outcomes. In this study, we aimed to determine whether including this eGFR_diff into prediction models for kidney failure and death would help discriminate between the 2 risks. We found that adding eGFR_diff to the death prediction model improved its performance.

© 2025 The Authors.

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Figures

Figure 1

Figure 1

Kaplan Meier curves for mortality stratified by eGFR_diff group. eGFR_diff=, cystatin C-based eGFR minus creatinine-based eGFR.

Figure 2

Figure 2

Calibration curves for risk estimation equations with and without eGFR_diff. Panels A-B plot estimated versus observed risk for death using the MREK equation, and panels C-D plot estimated versus observed risk for kidney failure using the KFRE equation. eGFR_diff=, cystatin C-based eGFR minus creatinine-based eGFR; MREK, mortality risk equation in patients with kidney disease.

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