Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
Authors: Schwab Simon , Sidler Daniel , Haidar Fadi , Kuhn Christian , Schaub Stefan , Koller Michael , Mellac Katell , Stürzinger Ueli , Tischhauser Bruno , Binet Isabelle , Golshayan Déla , Müller Thomas , Elmer Andreas , Franscini Nicola , Krügel Nathalie , Fehr Thomas , Immer Franz ,   the Swisstransplant Kidney Working Group (STAN), Amico Patrizia , Folie Patrick , Gannagé Monique , Matter Maurice , Nilsson Jakob , Peloso Andrea , de Rougemont Olivier , Schnyder Aurelia , Spartà Giuseppina , Storni Federico , Villard Jean , Wirth-müller Urs , Wolff Thomas ,   the Swiss Transplant Cohort Study, Aubert John-David , Banz Vanessa , Beckmann Sonja , Beldi Guido , Berger Christoph , Berishvili Ekaterine , Berzigotti Annalisa , Bochud Pierre-Yves , Branca Sanda , Bucher Heiner , Catana Emmanuelle , Cairoli Anne , Chalandon Yves , De Geest Sabina , De Seigneux Sophie , Dickenmann Michael , Dreifuss Joëlle Lynn , Duchosal Michel , Ferrari-Lacraz Sylvie , Garzoni Christian , Goossens Nicolas , Halter Jörg , Heim Dominik , Hess Christoph , Hillinger Sven , Hirsch Hans H , Hirt Patricia , Hoessly Linard , Hofbauer Günther , Huynh-Do Uyen , Laesser Bettina , Lamoth Frédéric , Lehmann Roger , Leichtle Alexander , Manuel Oriol , Marti Hans-Peter , Martinelli Michele , McLin Valérie , Merçay Aurélia , Mettler Karin , Mueller Nicolas J , Müller-Arndt Ulrike , Müllhaupt Beat , Nägeli Mirjam , Oldani Graziano , Pascual Manuel , Passweg Jakob , Pazeller Rosemarie , Posfay-Barbe Klara , Rick Juliane , Rosselet Anne , Rossi Simona , Rothlin Silvia , Ruschitzka Frank , Schachtner Thomas , Scherrer Alexandra , Schuurmans Macé , Sengstag Thierry , Simonetta Federico , Stampf Susanne , Steiger Jürg , Stirnimann Guido , Van Delden Christian , Venetz Jean-Pierre , Vionnet Julien , Wick Madeleine , Wilhelm Markus , Yerly Patrick 
Published: March 2023

Abstract
Background
Many potential prognostic factors for predicting kidney transplantation outcomes have been identified. However, in Switzerland, no widely accepted prognostic model or risk score for transplantation outcomes is being routinely used in clinical practice yet. We aim to develop three prediction models for the prognosis of graft survival, quality of life, and graft function following transplantation in Switzerland.

Methods
The clinical kidney prediction models (KIDMO) are developed with data from a national multi-center cohort study (Swiss Transplant Cohort Study; STCS) and the Swiss Organ Allocation System (SOAS). The primary outcome is the kidney graft survival (with death of recipient as competing risk); the secondary outcomes are the quality of life (patient-reported health status) at 12 months and estimated glomerular filtration rate (eGFR) slope. Organ donor, transplantation, and recipient-related clinical information will be used as predictors at the time of organ allocation. We will use a Fine & Gray subdistribution model and linear mixed-effects models for the primary and the two secondary outcomes, respectively. Model optimism, calibration, discrimination, and heterogeneity between transplant centres will be assessed using bootstrapping, internal-external cross-validation, and methods from meta-analysis.

Discussion
Thorough evaluation of the existing risk scores for the kidney graft survival or patient-reported outcomes has been lacking in the Swiss transplant setting. In order to be useful in clinical practice, a prognostic score needs to be valid, reliable, clinically relevant, and preferably integrated into the decision-making process to improve long-term patient outcomes and support informed decisions for clinicians and their patients. The state-of-the-art methodology by taking into account competing risks and variable selection using expert knowledge is applied to data from a nationwide prospective multi-center cohort study. Ideally, healthcare providers together with patients can predetermine the risk they are willing to accept from a deceased-donor kidney, with graft survival, quality of life, and graft function estimates available for their consideration.

Study registration
Open Science Framework ID: z6mvj