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Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol

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 predict...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990297/
https://www.ncbi.nlm.nih.gov/pubmed/36879332
http://dx.doi.org/10.1186/s41512-022-00139-5
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author 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
author_facet 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
author_sort Schwab, Simon
collection PubMed
description 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
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spelling pubmed-99902972023-03-08 Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol 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 Diagn Progn Res Protocol 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 BioMed Central 2023-03-07 /pmc/articles/PMC9990297/ /pubmed/36879332 http://dx.doi.org/10.1186/s41512-022-00139-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Protocol
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
Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
title Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
title_full Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
title_fullStr Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
title_full_unstemmed Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
title_short Clinical prediction model for prognosis in kidney transplant recipients (KIDMO): study protocol
title_sort clinical prediction model for prognosis in kidney transplant recipients (kidmo): study protocol
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9990297/
https://www.ncbi.nlm.nih.gov/pubmed/36879332
http://dx.doi.org/10.1186/s41512-022-00139-5
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