Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients
Repeated vaccination against SARS-CoV-2 increases serological response in kidney transplant recipients (KTR) with high interindividual variability. No decision support tool exists to predict SARS-CoV-2 vaccination response to third or fourth vaccination in KTR. We developed, internally and externall...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.997343/full |
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| author | Bilgin Osmanodja Johannes Stegbauer Marta Kantauskaite Lars Christian Rump Andreas Heinzel Roman Reindl-Schwaighofer Rainer Oberbauer Ilies Benotmane Sophie Caillard Christophe Masset Clarisse Kerleau Gilles Blancho Klemens Budde Fritz Grunow Michael Mikhailov Eva Schrezenmeier Eva Schrezenmeier Simon Ronicke |
| author_facet | Bilgin Osmanodja Johannes Stegbauer Marta Kantauskaite Lars Christian Rump Andreas Heinzel Roman Reindl-Schwaighofer Rainer Oberbauer Ilies Benotmane Sophie Caillard Christophe Masset Clarisse Kerleau Gilles Blancho Klemens Budde Fritz Grunow Michael Mikhailov Eva Schrezenmeier Eva Schrezenmeier Simon Ronicke |
| author_sort | Bilgin Osmanodja |
| collection | DOAJ |
| description | Repeated vaccination against SARS-CoV-2 increases serological response in kidney transplant recipients (KTR) with high interindividual variability. No decision support tool exists to predict SARS-CoV-2 vaccination response to third or fourth vaccination in KTR. We developed, internally and externally validated five different multivariable prediction models of serological response after the third and fourth vaccine dose against SARS-CoV-2 in previously seronegative, COVID-19-naïve KTR. Using 20 candidate predictor variables, we applied statistical and machine learning approaches including logistic regression (LR), least absolute shrinkage and selection operator (LASSO)-regularized LR, random forest, and gradient boosted regression trees. For development and internal validation, data from 590 vaccinations were used. External validation was performed in four independent, international validation cohorts comprising 191, 184, 254, and 323 vaccinations, respectively. LASSO-regularized LR performed on the whole development dataset yielded a 20- and 10-variable model, respectively. External validation showed AUC-ROC of 0.840, 0.741, 0.816, and 0.783 for the sparser 10-variable model, yielding an overall performance 0.812. A 10-variable LASSO-regularized LR model predicts vaccination response in KTR with good overall accuracy. Implemented as an online tool, it can guide decisions whether to modulate immunosuppressive therapy before additional active vaccination, or to perform passive immunization to improve protection against COVID-19 in previously seronegative, COVID-19-naïve KTR. |
| first_indexed | 2024-04-12T03:32:54Z |
| format | Article |
| id | doaj.art-0a5ce3319f95403bb4325b54e79aab5c |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-12T03:32:54Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-0a5ce3319f95403bb4325b54e79aab5c2022-12-22T03:49:30ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-10-011310.3389/fimmu.2022.997343997343Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipientsBilgin Osmanodja0Johannes Stegbauer1Marta Kantauskaite2Lars Christian Rump3Andreas Heinzel4Roman Reindl-Schwaighofer5Rainer Oberbauer6Ilies Benotmane7Sophie Caillard8Christophe Masset9Clarisse Kerleau10Gilles Blancho11Klemens Budde12Fritz Grunow13Michael Mikhailov14Eva Schrezenmeier15Eva Schrezenmeier16Simon Ronicke17Department of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, GermanyDepartment of Nephrology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, GermanyDepartment of Nephrology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, GermanyDepartment of Nephrology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, GermanyDivision of Nephrology and Dialysis, Department of Internal Medicine III, Medical University Vienna, Vienna, AustriaDivision of Nephrology and Dialysis, Department of Internal Medicine III, Medical University Vienna, Vienna, AustriaDivision of Nephrology and Dialysis, Department of Internal Medicine III, Medical University Vienna, Vienna, AustriaDepartment of Nephrology and Transplantation, University Hospitals of Strasbourg, INSERM Unit 1109, Strasbourg, FranceDepartment of Nephrology and Transplantation, University Hospitals of Strasbourg, INSERM Unit 1109, Strasbourg, FranceInstitut de Transplantation Urologie Néphrologie, Centre Hospitalier Universitaire de Nantes, Centre de Recherche en Transplantation et Immunologie, UMR 1064, INSERM, Nantes Université, Nantes, FranceInstitut de Transplantation Urologie Néphrologie, Centre Hospitalier Universitaire de Nantes, Centre de Recherche en Transplantation et Immunologie, UMR 1064, INSERM, Nantes Université, Nantes, FranceInstitut de Transplantation Urologie Néphrologie, Centre Hospitalier Universitaire de Nantes, Centre de Recherche en Transplantation et Immunologie, UMR 1064, INSERM, Nantes Université, Nantes, FranceDepartment of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, GermanyDepartment of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, GermanyDepartment of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, GermanyDepartment of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, GermanyBerlin Institute of Health, Berlin, GermanyDepartment of Nephrology and Medical Intensive Care, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, GermanyRepeated vaccination against SARS-CoV-2 increases serological response in kidney transplant recipients (KTR) with high interindividual variability. No decision support tool exists to predict SARS-CoV-2 vaccination response to third or fourth vaccination in KTR. We developed, internally and externally validated five different multivariable prediction models of serological response after the third and fourth vaccine dose against SARS-CoV-2 in previously seronegative, COVID-19-naïve KTR. Using 20 candidate predictor variables, we applied statistical and machine learning approaches including logistic regression (LR), least absolute shrinkage and selection operator (LASSO)-regularized LR, random forest, and gradient boosted regression trees. For development and internal validation, data from 590 vaccinations were used. External validation was performed in four independent, international validation cohorts comprising 191, 184, 254, and 323 vaccinations, respectively. LASSO-regularized LR performed on the whole development dataset yielded a 20- and 10-variable model, respectively. External validation showed AUC-ROC of 0.840, 0.741, 0.816, and 0.783 for the sparser 10-variable model, yielding an overall performance 0.812. A 10-variable LASSO-regularized LR model predicts vaccination response in KTR with good overall accuracy. Implemented as an online tool, it can guide decisions whether to modulate immunosuppressive therapy before additional active vaccination, or to perform passive immunization to improve protection against COVID-19 in previously seronegative, COVID-19-naïve KTR.https://www.frontiersin.org/articles/10.3389/fimmu.2022.997343/fullkidney transplantationCOVID-19vaccinationclinical decision supportimmunosuppression therapy |
| spellingShingle | Bilgin Osmanodja Johannes Stegbauer Marta Kantauskaite Lars Christian Rump Andreas Heinzel Roman Reindl-Schwaighofer Rainer Oberbauer Ilies Benotmane Sophie Caillard Christophe Masset Clarisse Kerleau Gilles Blancho Klemens Budde Fritz Grunow Michael Mikhailov Eva Schrezenmeier Eva Schrezenmeier Simon Ronicke Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients Frontiers in Immunology kidney transplantation COVID-19 vaccination clinical decision support immunosuppression therapy |
| title | Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients |
| title_full | Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients |
| title_fullStr | Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients |
| title_full_unstemmed | Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients |
| title_short | Development and validation of multivariable prediction models of serological response to SARS-CoV-2 vaccination in kidney transplant recipients |
| title_sort | development and validation of multivariable prediction models of serological response to sars cov 2 vaccination in kidney transplant recipients |
| topic | kidney transplantation COVID-19 vaccination clinical decision support immunosuppression therapy |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.997343/full |
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