Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers
Effective management of chronic kidney disease (CKD), a major health problem worldwide, requires accurate and timely diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for evaluating specific aspects...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/25/7/3678 |
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| author | Harald Rupprecht Lorenzo Catanese Kerstin Amann Felicitas E. Hengel Tobias B. Huber Agnieszka Latosinska Maja T. Lindenmeyer Harald Mischak Justyna Siwy Ralph Wendt Joachim Beige |
| author_facet | Harald Rupprecht Lorenzo Catanese Kerstin Amann Felicitas E. Hengel Tobias B. Huber Agnieszka Latosinska Maja T. Lindenmeyer Harald Mischak Justyna Siwy Ralph Wendt Joachim Beige |
| author_sort | Harald Rupprecht |
| collection | DOAJ |
| description | Effective management of chronic kidney disease (CKD), a major health problem worldwide, requires accurate and timely diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for evaluating specific aspects of CKD have been proposed in the literature, many of which are based on a small number of samples. Based on the evidence presented in relevant studies, a comprehensive overview of the different biomarkers applicable for clinical implementation is lacking. This review aims to compile information on the non-invasive diagnostic, prognostic, and predictive biomarkers currently available for the management of CKD and provide guidance on the application of these biomarkers. We specifically focus on biomarkers that have demonstrated added value in prospective studies or those based on prospectively collected samples including at least 100 subjects. Published data demonstrate that several valid non-invasive biomarkers of potential value in the management of CKD are currently available. |
| first_indexed | 2024-04-24T10:43:24Z |
| format | Article |
| id | doaj.art-736e40b136044da9a375bd453d5283c0 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-04-24T10:43:24Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-736e40b136044da9a375bd453d5283c02024-04-12T13:19:26ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672024-03-01257367810.3390/ijms25073678Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive BiomarkersHarald Rupprecht0Lorenzo Catanese1Kerstin Amann2Felicitas E. Hengel3Tobias B. Huber4Agnieszka Latosinska5Maja T. Lindenmeyer6Harald Mischak7Justyna Siwy8Ralph Wendt9Joachim Beige10Department of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, 95445 Bayreuth, GermanyDepartment of Nephrology, Angiology and Rheumatology, Klinikum Bayreuth GmbH, 95445 Bayreuth, GermanyDepartment of Nephropathology, Institute of Pathology, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, GermanyIII Department of Medicine, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, GermanyIII Department of Medicine, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, GermanyMosaiques Diagnostics GmbH, 30659 Hannover, GermanyIII Department of Medicine, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, GermanyMosaiques Diagnostics GmbH, 30659 Hannover, GermanyMosaiques Diagnostics GmbH, 30659 Hannover, GermanyDepartment of Nephrology, Hospital St. Georg, 04129 Leipzig, GermanyDepartment of Nephrology, Hospital St. Georg, 04129 Leipzig, GermanyEffective management of chronic kidney disease (CKD), a major health problem worldwide, requires accurate and timely diagnosis, prognosis of progression, assessment of therapeutic efficacy, and, ideally, prediction of drug response. Multiple biomarkers and algorithms for evaluating specific aspects of CKD have been proposed in the literature, many of which are based on a small number of samples. Based on the evidence presented in relevant studies, a comprehensive overview of the different biomarkers applicable for clinical implementation is lacking. This review aims to compile information on the non-invasive diagnostic, prognostic, and predictive biomarkers currently available for the management of CKD and provide guidance on the application of these biomarkers. We specifically focus on biomarkers that have demonstrated added value in prospective studies or those based on prospectively collected samples including at least 100 subjects. Published data demonstrate that several valid non-invasive biomarkers of potential value in the management of CKD are currently available.https://www.mdpi.com/1422-0067/25/7/3678biomarkerkidney diseaseresponse predictionprogressionfibrosis |
| spellingShingle | Harald Rupprecht Lorenzo Catanese Kerstin Amann Felicitas E. Hengel Tobias B. Huber Agnieszka Latosinska Maja T. Lindenmeyer Harald Mischak Justyna Siwy Ralph Wendt Joachim Beige Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers International Journal of Molecular Sciences biomarker kidney disease response prediction progression fibrosis |
| title | Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers |
| title_full | Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers |
| title_fullStr | Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers |
| title_full_unstemmed | Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers |
| title_short | Assessment and Risk Prediction of Chronic Kidney Disease and Kidney Fibrosis Using Non-Invasive Biomarkers |
| title_sort | assessment and risk prediction of chronic kidney disease and kidney fibrosis using non invasive biomarkers |
| topic | biomarker kidney disease response prediction progression fibrosis |
| url | https://www.mdpi.com/1422-0067/25/7/3678 |
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