Risk factors for death in kidney transplant patients: analysis from a large protocol biopsy registry. Issue 7 (31st May 2018)

• Record Type: Journal Article
• Authors: Abeling, Tanja; Scheffner, Irina; Karch, Annika; Broecker, Verena; Koch, Armin; Haller, Hermann; Schwarz, Anke; Gwinner, Wilfried
• Is Part Of: Nephrology dialysis transplantation. Volume 34:Issue 7(2019)
• Page Start: 1171
• Page End: 1181
• Publication Date: 2018-05-31
• Subjects: kidney transplantation -- protocol biopsies -- risk factors -- survival; Nephrology -- Periodicals; Hemodialysis -- Periodicals; Kidneys -- Transplantation -- Periodicals; Hemodialysis; Kidneys -- Transplantation; Nephrology; Periodicals; 616.61
• DOI: 10.1093/ndt/gfy131
• Languages: English
• ISSNs: 0931-0509

Abstract

Abstract: Background: Identification and quantification of the relevant factors for death can improve patients' individual risk assessment and decision-making. We used a well-documented patient cohort ( n = 892) in a renal transplant programme with protocol biopsies to establish multivariable Cox models for risk assessment at 3 and 12 months post-transplantation. Methods: Patients transplanted between 2000 and 2007 were observed up to 11 years (total observation 5227 patient-years; median 5.9 years). Loss to follow-up was negligible ( n = 15). A total of 2251 protocol biopsies and 1214 biopsies for cause were performed. All rejections and clinical borderline rejections in protocol biopsies were treated. Results: Overall 10-year patient survival was 78%, with inferior survival of patients with graft loss and superior survival of patients with living-donor transplantation. Eight factors were common in the models at 3 and 12 months, including age, pre-transplant heart failure and a score of cardiovascular disease and type 2 diabetes, post-transplant urinary tract infection, treatment of rejection, new-onset heart failure, coronary events and malignancies. Additional variables of the model at 3 months included deceased donor transplantation, transplant lymphocele, BK virus nephropathy and severe infections. Graft function and graft loss were significant factors of the model at 12 months. Internal validation and validation with a separate cohort of patients ( n = 349) demonstrated good discrimination of the models. Conclusions: The identified factors indicate the important areas that need special attention in the pre- and post-transplant care of renal transplant patients. On the basis of these models, we provide nomograms as a tool to weigh individual risks that may contribute to decreased survival.