2-Step Scores with optional nephropathology for the prediction of adverse outcomes for brain-dead donor kidneys in Eurotransplant

Angela Ernst*, Heinz Regele, Christos Chatzikyrkou, Amlie Dendooven, Sándor Turkevi-Nagy, Ineke Tieken, Rainer Oberbauer, Roman Reindl-Schwaighofer, Daniel Abramowicz, Rachel Hellemans, Annick Massart, Danica Galesic Ljubanovic, Petar Senjug, Bojana Maksimovic, Volker Aßfalg, Ivan Neretljak, Christina Schleicher, Marian Clahsen-Van Groningen, Nika Kojc, Carla L. EllisChristine E. Kurschat, Leandra Lukomski, Dirk Stippel, Michael Ströhlein, Florian G. Scurt, Joris J. Roelofs, Jesper Kers, Ana Harth, Christian Jungck, Albino Eccher, Isabel Prütz, Martin Hellmich, Francesco Vasuri, Deborah Malvi, Wolfgang Arns, Jan U. Becker*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: The decision to accept or discard the increasingly rare and marginal brain-dead donor kidneys in Eurotransplant (ET) countries has to be made without solid evidence. Thus, we developed and validated flexible clinicopathological scores called 2-Step Scores for the prognosis of delayed graft function (DGF) and 1-year death-censored transplant loss (1y-tl) reflecting the current practice of six ET countries including Croatia and Belgium. Methods: The training set was n = 620 for DGF and n = 711 for 1y-tl, with validation sets n = 158 and n = 162, respectively. In Step 1, stepwise logistic regression models including only clinical predictors were used to estimate the risks. In Step 2, risk estimates were updated for statistically relevant intermediate risk percentiles with nephropathology. Results: Step 1 revealed an increased risk of DGF with increased cold ischaemia time (CIT), donor and recipient body mass index, dialysis vintage, number of HLA-DR mismatches or recipient cytomegalovirus immunoglobulin G positivity. On the training and validation set, c-statistics were 0.672 and 0.704, respectively. At a range between 18% and 36%, accuracy of DGF-prognostication improved with nephropathology including number of glomeruli and Banff cv (updated overall c-statistics of 0.696 and 0.701, respectively). Risk of 1y-tl increased in recipients with CIT, sum of HLA-A, -B, -DR mismatches, and donor age. On training and validation sets, c-statistics were 0.700 and 0.769, respectively. Accuracy of 1y-tl prediction improved (c-statistics = 0.706 and 0.765) with Banff ct. Overall, calibration was good on the training, but moderate on the validation set; discrimination was at least as good as established scores when applied to the validation set. Conclusion: Our flexible 2-Step Scores with optional inclusion of time-consuming and often unavailable nephropathology should yield good results for clinical practice in ET, and may be superior to established scores. Our scores are adaptable to donation after cardiac death and perfusion pump use.

Original languageEnglish (US)
Pages (from-to)83-108
Number of pages26
JournalNephrology Dialysis Transplantation
Volume40
Issue number1
DOIs
StatePublished - Jan 1 2025

Funding

The authors thank Els Meersman for the collation of clinical data from Antwerp and Peter Riegmann for scanning of glass slides in Rotterdam. J.U.B. and A.E. received support from the Deutsche Forschungsgemeinschaft (BE-3801).

Keywords

  • delayed graft function
  • kidney transplantation
  • prognostic modelling
  • transplant loss

ASJC Scopus subject areas

  • Nephrology
  • Transplantation

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