Abstract
Background Various prediction models have been developed to predict the risk of kidney failure in patients with CKD. However, guideline-recommended models have yet to be compared head to head, their validation in patients with advanced CKD is lacking, and most do not account for competing risks.
Methods To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration.
Results The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%–18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts.
Conclusions Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years).
Methods To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration.
Results The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%–18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts.
Conclusions Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years).
| Original language | English |
|---|---|
| Pages (from-to) | 1174-1186 |
| Number of pages | 13 |
| Journal | Journal of the American Society of Nephrology |
| Volume | 32 |
| Issue number | 5 |
| Early online date | 1 May 2021 |
| DOIs | |
| Publication status | Published - 3 May 2021 |
Bibliographical note
Funding Information:or member as Nephrology Dialysis Transplantation editorial board; and other interests/relationships via collaboration with Dutch Kidney Patients Association and collaborationwith Dutch Quality Institute for Renal Care (Nefrovisie). C. Drechsler reports research funding from Genzyme. M. Evans reports honoraria from payment for lectures by Astellas, AstraZeneca, and Vifor Pharma; being a scientific advisor or member with Astellas, AstraZeneca, and Vifor Pharma advisory board; other interests/relationships as a member of the steering committee of SRR and the European Renal Association–European Dialysis and Transplant Association (ERA-EDTA) Registry Committee. M. Evans was funded by a grant from the Centre of Innovative Medicine, Karolinska Institutet and Stockholm City Council. K.J. Jager reports honoraria from Fresenius and being a scientific advisor or member on the editorial board of Nephrology Dialysis Transplantation, the editorial board of Kidney International Reports, and the editorial board of Journal of Renal Nutrition. M. Krajewska reports other interests/relationships as ERA-EDTA member and with the Polish Society of Nephrology and the Polish Society of Transplantology. C. Wanner reports consultancy agreements with Akebia, Bayer, Boehringer-Ingelheim, Gilead, GSK, MSD, Sanofi-Genzyme, Triceda, and Vifor; research funding from an Idorsia grant to the institution and Sanofi-Genyzme from a grant to the institution; honoraria from Astellas, AstraZeneca, Bayer, Boehringer-Ingelheim, Eli-Lilly, FMC, Sanofi-Genzyme, and Shire-Takeda; and other interests/relationships with ERA-EDTA. Funding for EQUAL was received from the Dutch Kidney Foundation (grant: SB142), ERA-EDTA, the Italian Society of Nephrology (Reni), the National Institute for Health Research in the United Kingdom, Njurfonden, the Stockholm County Council ALF, the Swedish Medical Association, and the Young Investigators grant in Germany. All remaining authors have nothing to disclose.
Funding Information:
F. Caskey reports research funding from Kidney Research UK and National Institute for Health Research and honoraria from Baxter. F.W. Dekker reports research funding from Astellas and Chiesi; being a scientific advisor
Publisher Copyright:
© 2021 American Society of Nephrology. All rights reserved.
Keywords
- comprehensive external validation
- chronic kidney disease
- kidney failure
- prediction model
- prognostic