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A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model
BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage renal disease (ESRD); however, the natural course of disease progression is heterogeneous between patients. This study aimed to develop a natural history model of ADPKD that predicted progr...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5810027/ https://www.ncbi.nlm.nih.gov/pubmed/29439650 http://dx.doi.org/10.1186/s12882-017-0804-2 |
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author | McEwan, Phil Bennett Wilton, Hayley Ong, Albert C. M. Ørskov, Bjarne Sandford, Richard Scolari, Francesco Cabrera, Maria-Cristina V. Walz, Gerd O’Reilly, Karl Robinson, Paul |
author_facet | McEwan, Phil Bennett Wilton, Hayley Ong, Albert C. M. Ørskov, Bjarne Sandford, Richard Scolari, Francesco Cabrera, Maria-Cristina V. Walz, Gerd O’Reilly, Karl Robinson, Paul |
author_sort | McEwan, Phil |
collection | PubMed |
description | BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage renal disease (ESRD); however, the natural course of disease progression is heterogeneous between patients. This study aimed to develop a natural history model of ADPKD that predicted progression rates and long-term outcomes in patients with differing baseline characteristics. METHODS: The ADPKD Outcomes Model (ADPKD-OM) was developed using available patient-level data from the placebo arm of the Tolvaptan Efficacy and Safety in Management of ADPKD and its Outcomes Study (TEMPO 3:4; ClinicalTrials.gov identifier NCT00428948). Multivariable regression equations estimating annual rates of ADPKD progression, in terms of total kidney volume (TKV) and estimated glomerular filtration rate, formed the basis of the lifetime patient-level simulation model. Outputs of the ADPKD-OM were compared against external data sources to validate model accuracy and generalisability to other ADPKD patient populations, then used to predict long-term outcomes in a cohort matched to the overall TEMPO 3:4 study population. RESULTS: A cohort with baseline patient characteristics consistent with TEMPO 3:4 was predicted to reach ESRD at a mean age of 52 years. Most patients (85%) were predicted to reach ESRD by the age of 65 years, with many progressing to ESRD earlier in life (18, 36 and 56% by the age of 45, 50 and 55 years, respectively). Consistent with previous research and clinical opinion, analyses supported the selection of baseline TKV as a prognostic factor for ADPKD progression, and demonstrated its value as a strong predictor of future ESRD risk. Validation exercises and illustrative analyses confirmed the ability of the ADPKD-OM to accurately predict disease progression towards ESRD across a range of clinically-relevant patient profiles. CONCLUSIONS: The ADPKD-OM represents a robust tool to predict natural disease progression and long-term outcomes in ADPKD patients, based on readily available and/or measurable clinical characteristics. In conjunction with clinical judgement, it has the potential to support decision-making in research and clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12882-017-0804-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5810027 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58100272018-02-16 A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model McEwan, Phil Bennett Wilton, Hayley Ong, Albert C. M. Ørskov, Bjarne Sandford, Richard Scolari, Francesco Cabrera, Maria-Cristina V. Walz, Gerd O’Reilly, Karl Robinson, Paul BMC Nephrol Research Article BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage renal disease (ESRD); however, the natural course of disease progression is heterogeneous between patients. This study aimed to develop a natural history model of ADPKD that predicted progression rates and long-term outcomes in patients with differing baseline characteristics. METHODS: The ADPKD Outcomes Model (ADPKD-OM) was developed using available patient-level data from the placebo arm of the Tolvaptan Efficacy and Safety in Management of ADPKD and its Outcomes Study (TEMPO 3:4; ClinicalTrials.gov identifier NCT00428948). Multivariable regression equations estimating annual rates of ADPKD progression, in terms of total kidney volume (TKV) and estimated glomerular filtration rate, formed the basis of the lifetime patient-level simulation model. Outputs of the ADPKD-OM were compared against external data sources to validate model accuracy and generalisability to other ADPKD patient populations, then used to predict long-term outcomes in a cohort matched to the overall TEMPO 3:4 study population. RESULTS: A cohort with baseline patient characteristics consistent with TEMPO 3:4 was predicted to reach ESRD at a mean age of 52 years. Most patients (85%) were predicted to reach ESRD by the age of 65 years, with many progressing to ESRD earlier in life (18, 36 and 56% by the age of 45, 50 and 55 years, respectively). Consistent with previous research and clinical opinion, analyses supported the selection of baseline TKV as a prognostic factor for ADPKD progression, and demonstrated its value as a strong predictor of future ESRD risk. Validation exercises and illustrative analyses confirmed the ability of the ADPKD-OM to accurately predict disease progression towards ESRD across a range of clinically-relevant patient profiles. CONCLUSIONS: The ADPKD-OM represents a robust tool to predict natural disease progression and long-term outcomes in ADPKD patients, based on readily available and/or measurable clinical characteristics. In conjunction with clinical judgement, it has the potential to support decision-making in research and clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12882-017-0804-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-13 /pmc/articles/PMC5810027/ /pubmed/29439650 http://dx.doi.org/10.1186/s12882-017-0804-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article McEwan, Phil Bennett Wilton, Hayley Ong, Albert C. M. Ørskov, Bjarne Sandford, Richard Scolari, Francesco Cabrera, Maria-Cristina V. Walz, Gerd O’Reilly, Karl Robinson, Paul A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model |
title | A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model |
title_full | A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model |
title_fullStr | A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model |
title_full_unstemmed | A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model |
title_short | A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model |
title_sort | model to predict disease progression in patients with autosomal dominant polycystic kidney disease (adpkd): the adpkd outcomes model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5810027/ https://www.ncbi.nlm.nih.gov/pubmed/29439650 http://dx.doi.org/10.1186/s12882-017-0804-2 |
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