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Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients
INTRODUCTION: To establish a prediction model to predict immunosuppressive medication (IM) nonadherence in kidney transplant recipients (KTRs) based on a combined theory framework. METHODS: This polycentric, cross-sectional study included 1191 KTRs from October 2020 to February 2021 in China, with 1...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10512851/ http://dx.doi.org/10.1080/0886022X.2023.2238832 |
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author | Dong, Lei Zhu, Xiao Zhao, Hongyu Zhao, Qin Liu, Shan Liu, Jia Gong, Lina |
author_facet | Dong, Lei Zhu, Xiao Zhao, Hongyu Zhao, Qin Liu, Shan Liu, Jia Gong, Lina |
author_sort | Dong, Lei |
collection | PubMed |
description | INTRODUCTION: To establish a prediction model to predict immunosuppressive medication (IM) nonadherence in kidney transplant recipients (KTRs) based on a combined theory framework. METHODS: This polycentric, cross-sectional study included 1191 KTRs from October 2020 to February 2021 in China, with 1011 KTRs enrolled in the derivation set and 180 in the external validation set. Variables selected based on the combined theory of planned behavior (TPB)/health belief model (HBM) theory were analyzed by the least absolute shrinkage and selection operator (LASSO). Internal 10 cross-validation was conducted to determine the optimal lambda value. The receiver operating characteristic (ROC) curve, specificity, and sensitivity were used to evaluate the prediction model, and further assessment was run by external validation. RESULTS: IM nonadherence rate was 38.48% in the derivation set and 37.22% in the validation set. The LASSO model was developed with eight predictors for IM nonadherence: age, preoperative drinking history, education, marital status, perceived barriers, social support, perceived behavioral control, and perceived susceptibility. The model demonstrated acceptable discrimination with the area under the ROC curve of 0.797 (95% CI: 0.745–0.850) in the internal validation set and 0.757 (95% CI: 0.684–0.829) in the external validation set. The specificity and sensitivity in the internal validation and external validation set were 0.741, 0.748, 0.673, and 0.716, respectively. CONCLUSIONS: The LASSO model was developed to guide identifying high-risk nonadherent patients and timely and effective interventions to improve their prognosis and survival. |
format | Online Article Text |
id | pubmed-10512851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-105128512023-09-22 Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients Dong, Lei Zhu, Xiao Zhao, Hongyu Zhao, Qin Liu, Shan Liu, Jia Gong, Lina Ren Fail Clinical Study INTRODUCTION: To establish a prediction model to predict immunosuppressive medication (IM) nonadherence in kidney transplant recipients (KTRs) based on a combined theory framework. METHODS: This polycentric, cross-sectional study included 1191 KTRs from October 2020 to February 2021 in China, with 1011 KTRs enrolled in the derivation set and 180 in the external validation set. Variables selected based on the combined theory of planned behavior (TPB)/health belief model (HBM) theory were analyzed by the least absolute shrinkage and selection operator (LASSO). Internal 10 cross-validation was conducted to determine the optimal lambda value. The receiver operating characteristic (ROC) curve, specificity, and sensitivity were used to evaluate the prediction model, and further assessment was run by external validation. RESULTS: IM nonadherence rate was 38.48% in the derivation set and 37.22% in the validation set. The LASSO model was developed with eight predictors for IM nonadherence: age, preoperative drinking history, education, marital status, perceived barriers, social support, perceived behavioral control, and perceived susceptibility. The model demonstrated acceptable discrimination with the area under the ROC curve of 0.797 (95% CI: 0.745–0.850) in the internal validation set and 0.757 (95% CI: 0.684–0.829) in the external validation set. The specificity and sensitivity in the internal validation and external validation set were 0.741, 0.748, 0.673, and 0.716, respectively. CONCLUSIONS: The LASSO model was developed to guide identifying high-risk nonadherent patients and timely and effective interventions to improve their prognosis and survival. Taylor & Francis 2023-09-19 /pmc/articles/PMC10512851/ http://dx.doi.org/10.1080/0886022X.2023.2238832 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
spellingShingle | Clinical Study Dong, Lei Zhu, Xiao Zhao, Hongyu Zhao, Qin Liu, Shan Liu, Jia Gong, Lina Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
title | Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
title_full | Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
title_fullStr | Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
title_full_unstemmed | Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
title_short | Development and validation of a LASSO-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
title_sort | development and validation of a lasso-based prediction model for immunosuppressive medication nonadherence in kidney transplant recipients |
topic | Clinical Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10512851/ http://dx.doi.org/10.1080/0886022X.2023.2238832 |
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