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Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods
We evaluated a multivariable logistic regression model predicting 5-year survival derived from a 1993–1997 cohort from the United States Cystic Fibrosis (CF) Foundation Patient Registry to assess whether therapies introduced since 1993 have altered applicability in cohorts, non-overlapping in time,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171119/ https://www.ncbi.nlm.nih.gov/pubmed/32313191 http://dx.doi.org/10.1038/s41598-020-63590-8 |
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author | Liou, Theodore G. Kartsonaki, Christiana Keogh, Ruth H. Adler, Frederick R. |
author_facet | Liou, Theodore G. Kartsonaki, Christiana Keogh, Ruth H. Adler, Frederick R. |
author_sort | Liou, Theodore G. |
collection | PubMed |
description | We evaluated a multivariable logistic regression model predicting 5-year survival derived from a 1993–1997 cohort from the United States Cystic Fibrosis (CF) Foundation Patient Registry to assess whether therapies introduced since 1993 have altered applicability in cohorts, non-overlapping in time, from 1993–1998, 1999–2004, 2005–2010 and 2011–2016. We applied Kaplan-Meier statistics to assess unadjusted survival. We tested logistic regression model discrimination using the C-index and calibration using Hosmer-Lemeshow tests to examine original model performance and guide updating as needed. Kaplan-Meier age-adjusted 5-year probability of death in the CF population decreased substantially during 1993–2016. Patients in successive cohorts were generally healthier at entry, with higher average age, weight and lung function and fewer pulmonary exacerbations annually. CF-related diabetes prevalence, however, steadily increased. Newly derived multivariable logistic regression models for 5-year survival in new cohorts had similar estimated coefficients to the originals. The original model exhibited excellent calibration and discrimination when applied to later cohorts despite improved survival and remains useful for predicting 5-year survival. All models may be used to stratify patients for new studies, and the original coefficients may be useful as a baseline to search for additional but rare events that affect survival in CF. |
format | Online Article Text |
id | pubmed-7171119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71711192020-04-23 Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods Liou, Theodore G. Kartsonaki, Christiana Keogh, Ruth H. Adler, Frederick R. Sci Rep Article We evaluated a multivariable logistic regression model predicting 5-year survival derived from a 1993–1997 cohort from the United States Cystic Fibrosis (CF) Foundation Patient Registry to assess whether therapies introduced since 1993 have altered applicability in cohorts, non-overlapping in time, from 1993–1998, 1999–2004, 2005–2010 and 2011–2016. We applied Kaplan-Meier statistics to assess unadjusted survival. We tested logistic regression model discrimination using the C-index and calibration using Hosmer-Lemeshow tests to examine original model performance and guide updating as needed. Kaplan-Meier age-adjusted 5-year probability of death in the CF population decreased substantially during 1993–2016. Patients in successive cohorts were generally healthier at entry, with higher average age, weight and lung function and fewer pulmonary exacerbations annually. CF-related diabetes prevalence, however, steadily increased. Newly derived multivariable logistic regression models for 5-year survival in new cohorts had similar estimated coefficients to the originals. The original model exhibited excellent calibration and discrimination when applied to later cohorts despite improved survival and remains useful for predicting 5-year survival. All models may be used to stratify patients for new studies, and the original coefficients may be useful as a baseline to search for additional but rare events that affect survival in CF. Nature Publishing Group UK 2020-04-20 /pmc/articles/PMC7171119/ /pubmed/32313191 http://dx.doi.org/10.1038/s41598-020-63590-8 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liou, Theodore G. Kartsonaki, Christiana Keogh, Ruth H. Adler, Frederick R. Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
title | Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
title_full | Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
title_fullStr | Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
title_full_unstemmed | Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
title_short | Evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
title_sort | evaluation of a five-year predicted survival model for cystic fibrosis in later time periods |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171119/ https://www.ncbi.nlm.nih.gov/pubmed/32313191 http://dx.doi.org/10.1038/s41598-020-63590-8 |
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