title: A clinical scoring system highly predictive of long-term kidney graft survival.
abstract: Determining early surrogate markers of long-term graft outcome is important for optimal medical management. In order to identify such markers, we used clinical information from a cross-validated French database (Données Informatisées et VAlidées en Transplantation) of 2169 kidney transplant recipients to construct a composite score 1 year after transplantation. This Kidney Transplant Failure Score took into account a series of eight accepted pre- and post-transplant risk factors of graft loss, and was subsequently evaluated for its ability to predict graft failure at 8 years. This algorithm outperformed the traditional surrogates of serum creatinine and the estimated graft filtration rate, with an area under the receiver-operator characteristic curve of 0.78. Validation on an independent database of 317 graft recipients had the same predictive capacity. Our algorithm was also able to stratify patients into two groups according to their risk: a high-risk group of 81 patients with 25% graft failure and a low-risk group of 236 patients with an 8% failure rate. Thus, although this clinical composite score predicts long-term graft survival, it needs validation in different patient groups throughout the world.
authors.affiliation: Institut de Transplantation et de Recherche en Transplantation-Urologie-Néphrologie, CHU Nantes, IUN and INSERM U643, Nantes, France.
authors.forename: Yohann
authors.initials: Y
authors.lastname: Foucher
authors.forename: Pascal
authors.initials: P
authors.lastname: Daguin
authors.forename: Ahmed
authors.initials: A
authors.lastname: Akl
authors.forename: Michèle
authors.initials: M
authors.lastname: Kessler
authors.forename: Marc
authors.initials: M
authors.lastname: Ladrière
authors.forename: Christophe
authors.initials: C
authors.lastname: Legendre
authors.forename: Henri
authors.initials: H
authors.lastname: Kreis
authors.forename: Lionel
authors.initials: L
authors.lastname: Rostaing
authors.forename: Nassim
authors.initials: N
authors.lastname: Kamar
authors.forename: Georges
authors.initials: G
authors.lastname: Mourad
authors.forename: Valérie
authors.initials: V
authors.lastname: Garrigue
authors.forename: François
authors.initials: F
authors.lastname: Bayle
authors.forename: Bruno
authors.initials: B
authors.lastname: H de Ligny
authors.forename: Mathias
authors.initials: M
authors.lastname: Büchler
authors.forename: Carole
authors.initials: C
authors.lastname: Meier
authors.forename: Jean P
authors.initials: JP
authors.lastname: Daurès
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Soulillou
authors.forename: Magali
authors.initials: M
authors.lastname: Giral
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D005260:Female; D005500:Follow-Up Studies; D006084:Graft Rejection / Q000453:epidemiology / Q000503:physiopathology; D006085:Graft Survival / Q000502:physiology*; D006801:Humans; D007223:Infant; D016030:Kidney Transplantation / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D055815:Young Adult