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Clinical phenotyping in sarcoidosis using cluster analysis
BACKGROUND: Most phenotyping paradigms in sarcoidosis are based on expert opinion; however, no paradigm has been widely adopted because of the subjectivity in classification. We hypothesized that cluster analysis could be performed on common clinical variables to define more objective sarcoidosis ph...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994095/ https://www.ncbi.nlm.nih.gov/pubmed/35397561 http://dx.doi.org/10.1186/s12931-022-01993-z |
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author | Lin, Nancy W. Arbet, Jaron Mroz, Margaret M. Liao, Shu-Yi Restrepo, Clara I. Mayer, Annyce S. Li, Li Barkes, Briana Q. Schrock, Sarah Hamzeh, Nabeel Fingerlin, Tasha E. Carlson, Nichole E. Maier, Lisa A. |
author_facet | Lin, Nancy W. Arbet, Jaron Mroz, Margaret M. Liao, Shu-Yi Restrepo, Clara I. Mayer, Annyce S. Li, Li Barkes, Briana Q. Schrock, Sarah Hamzeh, Nabeel Fingerlin, Tasha E. Carlson, Nichole E. Maier, Lisa A. |
author_sort | Lin, Nancy W. |
collection | PubMed |
description | BACKGROUND: Most phenotyping paradigms in sarcoidosis are based on expert opinion; however, no paradigm has been widely adopted because of the subjectivity in classification. We hypothesized that cluster analysis could be performed on common clinical variables to define more objective sarcoidosis phenotypes. METHODS: We performed a retrospective cohort study of 554 sarcoidosis cases to identify distinct phenotypes of sarcoidosis based on 29 clinical features. Model-based clustering was performed using the VarSelLCM R package and the Integrated Completed Likelihood (ICL) criteria were used to estimate number of clusters. To identify features associated with cluster membership, features were ranked based on variable importance scores from the VarSelLCM model, and additional univariate tests (Fisher’s exact test and one-way ANOVA) were performed using q-values correcting for multiple testing. The Wasfi severity score was also compared between clusters. RESULTS: Cluster analysis resulted in 6 sarcoidosis phenotypes. Salient characteristics for each cluster are as follows: Phenotype (1) supranormal lung function and majority Scadding stage 2/3; phenotype (2) supranormal lung function and majority Scadding stage 0/1; phenotype (3) normal lung function and split Scadding stages between 0/1 and 2/3; phenotype (4) obstructive lung function and majority Scadding stage 2/3; phenotype (5) restrictive lung function and majority Scadding stage 2/3; phenotype (6) mixed obstructive and restrictive lung function and mostly Scadding stage 4. Although there were differences in the percentages, all Scadding stages were encompassed by all of the phenotypes, except for phenotype 1, in which none were Scadding stage 4. Clusters 4, 5, 6 were significantly more likely to have ever been on immunosuppressive treatment and had higher Wasfi disease severity scores. CONCLUSIONS: Cluster analysis produced 6 sarcoidosis phenotypes that demonstrated less severe and severe phenotypes. Phenotypes 1, 2, 3 have less lung function abnormalities, a lower percentage on immunosuppressive treatment and lower Wasfi severity scores. Phenotypes 4, 5, 6 were characterized by lung function abnormalities, more parenchymal abnormalities, an increased percentage on immunosuppressive treatment and higher Wasfi severity scores. These data support using cluster analysis as an objective and clinically useful way to phenotype sarcoidosis subjects and to empower clinicians to identify those with more severe disease versus those who have less severe disease, independent of Scadding stage. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-022-01993-z. |
format | Online Article Text |
id | pubmed-8994095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89940952022-04-10 Clinical phenotyping in sarcoidosis using cluster analysis Lin, Nancy W. Arbet, Jaron Mroz, Margaret M. Liao, Shu-Yi Restrepo, Clara I. Mayer, Annyce S. Li, Li Barkes, Briana Q. Schrock, Sarah Hamzeh, Nabeel Fingerlin, Tasha E. Carlson, Nichole E. Maier, Lisa A. Respir Res Research BACKGROUND: Most phenotyping paradigms in sarcoidosis are based on expert opinion; however, no paradigm has been widely adopted because of the subjectivity in classification. We hypothesized that cluster analysis could be performed on common clinical variables to define more objective sarcoidosis phenotypes. METHODS: We performed a retrospective cohort study of 554 sarcoidosis cases to identify distinct phenotypes of sarcoidosis based on 29 clinical features. Model-based clustering was performed using the VarSelLCM R package and the Integrated Completed Likelihood (ICL) criteria were used to estimate number of clusters. To identify features associated with cluster membership, features were ranked based on variable importance scores from the VarSelLCM model, and additional univariate tests (Fisher’s exact test and one-way ANOVA) were performed using q-values correcting for multiple testing. The Wasfi severity score was also compared between clusters. RESULTS: Cluster analysis resulted in 6 sarcoidosis phenotypes. Salient characteristics for each cluster are as follows: Phenotype (1) supranormal lung function and majority Scadding stage 2/3; phenotype (2) supranormal lung function and majority Scadding stage 0/1; phenotype (3) normal lung function and split Scadding stages between 0/1 and 2/3; phenotype (4) obstructive lung function and majority Scadding stage 2/3; phenotype (5) restrictive lung function and majority Scadding stage 2/3; phenotype (6) mixed obstructive and restrictive lung function and mostly Scadding stage 4. Although there were differences in the percentages, all Scadding stages were encompassed by all of the phenotypes, except for phenotype 1, in which none were Scadding stage 4. Clusters 4, 5, 6 were significantly more likely to have ever been on immunosuppressive treatment and had higher Wasfi disease severity scores. CONCLUSIONS: Cluster analysis produced 6 sarcoidosis phenotypes that demonstrated less severe and severe phenotypes. Phenotypes 1, 2, 3 have less lung function abnormalities, a lower percentage on immunosuppressive treatment and lower Wasfi severity scores. Phenotypes 4, 5, 6 were characterized by lung function abnormalities, more parenchymal abnormalities, an increased percentage on immunosuppressive treatment and higher Wasfi severity scores. These data support using cluster analysis as an objective and clinically useful way to phenotype sarcoidosis subjects and to empower clinicians to identify those with more severe disease versus those who have less severe disease, independent of Scadding stage. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-022-01993-z. BioMed Central 2022-04-09 2022 /pmc/articles/PMC8994095/ /pubmed/35397561 http://dx.doi.org/10.1186/s12931-022-01993-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Lin, Nancy W. Arbet, Jaron Mroz, Margaret M. Liao, Shu-Yi Restrepo, Clara I. Mayer, Annyce S. Li, Li Barkes, Briana Q. Schrock, Sarah Hamzeh, Nabeel Fingerlin, Tasha E. Carlson, Nichole E. Maier, Lisa A. Clinical phenotyping in sarcoidosis using cluster analysis |
title | Clinical phenotyping in sarcoidosis using cluster analysis |
title_full | Clinical phenotyping in sarcoidosis using cluster analysis |
title_fullStr | Clinical phenotyping in sarcoidosis using cluster analysis |
title_full_unstemmed | Clinical phenotyping in sarcoidosis using cluster analysis |
title_short | Clinical phenotyping in sarcoidosis using cluster analysis |
title_sort | clinical phenotyping in sarcoidosis using cluster analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994095/ https://www.ncbi.nlm.nih.gov/pubmed/35397561 http://dx.doi.org/10.1186/s12931-022-01993-z |
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