Kidney Failure Prediction Models: A Comprehensive External Validation Study in Patients with Advanced CKD.

Rotmans J

Collaborators: Cupisti A, Sagliocca A, Ferraro A, Musiała A, Mele A, Naticchia A, Còsaro A, Woodman A, Ranghino A, Stucchi A, Jonsson A, Schneider A, Pignataro A, Schrander A, Torp A, McKeever A, Szymczak A, Blom AL, De Blasio A, Pani A, Tsalouichos A, Ullah A, McLaren B, van Dam B, Iwig B, Antonio B, Di Iorio BR, Rogland B, Perras B, Alessandra B, Harron C, Wallquist C, Siegert C, Barrett C, Gaillard C, Garofalo C, Abaterusso C, Beerenhout C, O'Toole C, Somma C, Marx C, Summersgill C, Blaser C, D'alessandro C, Emde C, Zullo C, Pozzi C, Geddes C, Verburgh C, Bergamo D, Ciurlino D, Motta D, Glowski D, McGlynn D, Vargas D, Krieter D, Russo D, Fuchs D, Sands D, Hoogeveen E, Irmler E, Dimény E, Favaro E, Platen E, Olczyk E, Hoorn E, Vigotti F, Ansali F, Conte F, Cianciotta F, Giacchino F, Cappellaio F, Pizzarelli F, Sundelin F, Uhlin F, Greco G, Roy G, Porto G, Bigatti G, Marinangeli G, Cabiddu G, Hirst G, Fumagalli G, Caloro G, Piccoli G, Capasso G, Gambaro G, Tognarelli G, Bonforte G, Conte G, Toscano G, Del Rosso G, Welander G, Augustyniak-Bartosik H, Boots H, Schmidt-Gürtler H, King H, McNally H, Schlee H, Boom H, Naujoks H, Masri-Senghor H, Murtagh H, Rayner H, Miśkowiec-Wiśniewska I, Schlee I, Capizzi I, Bascaran Hernandez I, Baragetti I, Manitius J, Turner J, Eijgenraam JW, Kooman J, Beige J, Pondel J, Wilcox J, Berdeprado J, Röthele J, Wong J, Rotmans J, Banda J, Mazur J, Hahn K, Jędrzejak K, Nowańska K, Blouin K, Neumeier K, Jones K, Anding-Rost K, Gröntoft KC, Oldrizzi L, Haydock L, Vogt L, Wilkinson L, Gesualdo L, Schramm L, Biancone L, Nowak Ł, Raasveld M, Durlik M, Magnano M, Vervloet M, Ricardi M, Carmody M, Di Bari M, Laudato M, Luisa Sirico M, Stendahl M, Svensson M, Weetman M, van Buren M, Joinson M, Ferraresi M, Dutton M, van Diepen M, Matthews M, Provenzano M, Hopf M, Malaguti M, Wuttke N, Morgan N, Palmieri N, Frischmuth N, Bleakley N, Murrone P, Cockwell P, Leurs P, Roderick P, Voskamp P, Kashioulis P, Ichtiaris P, Blankestijn P, Kirste P, Schulz P, Mason P, Kalra P, Cirillo P, Dattolo P, Acampora P, Sajith R, Nigro R, Boero R, Scarpioni R, Sicoli R, Malandra R, Aign S, Cäsar S, van Esch S, Chapman S, Biribauer S, Navjee S, Crosbie S, Brown S, Tickle S, Manan S, Röser S, Savoldi S, Bertoli S, Borrelli S, Boorsma S, Heidenreich S, Melander S, Maxia S, Maffei S, Mangano S, Palm S, Konings S, Mathavakkannan S, Schwedler S, Delrieux S, Renker S, Schättel S, Dorota S, Cicchetti T, Nieszporek T, Stephan T, Schmiedeke T, Weinreich T, Leimbach T, Rappa T, Almquist T, Stövesand T, Bahner U, Jensen U, Palazzo V, De Simone W, Seeger W, Kuan Y, Heleniak Z, Aydin Z.
Author information:
(1)Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands [Email]
(2)Division of Renal Medicine, Department of Clinical Science, Intervention and Technology, Karolinska Institute and Karolinska University Hospital, Stockholm, Sweden.
(3)Division of Nephrology, University Hospital of Wurzburg, Wurzburg, Germany.
(4)Division of Nephrology, Department of Internal Medicine 1, University Hospital Wurzburg, Wurzburg, Germany.
(5)Department of Medical Informatics, European Renal Association-European Dialysis and Transplant Association Registry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Public Health Institute, Amsterdam, The Netherlands.
(6)Department of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland.
(7)Department of Clinical Epidemiology of Renal Diseases and Hypertension, Consiglio Nazionale della Ricerche - Istituto di fisiologia clinica, Reggio Calabria, Italy.
(8)Department of Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
(9)United Kingdom Renal Registry, Bristol, United Kingdom.
(10)Departmen of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
(11)Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

https://dx.doi.org/10.1681/ASN.2020071077

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).