Evidence map›Paper›PMID 35397561›Full record

ArticleRespiratory research2022

Clinical phenotyping in sarcoidosis using cluster analysis.

Nancy W Lin, Jaron Arbet, Margaret M Mroz, Shu-Yi Liao, Clara I Restrepo, Annyce S Mayer, Li Li, Briana Q Barkes, Sarah Schrock, Nabeel Hamzeh and 3 more

Open access · goldAbstract read
In one paragraph

Article in Respiratory research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 22 citations in OpenAlex.

  1. New Therapies for Sarcoidosis: Molecular and Pathophysiological Basis.International journal of molecular sciences · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Big data in sarcoidosis.Current opinion in pulmonary medicine · 2024
    Review
  11. The textures of sarcoidosis: quantifying lung disease through variograms.medRxiv : the preprint server for health sciences · 2024
    Article
  12. Article
  13. Article
  14. Pulmonary Function in Pulmonary Sarcoidosis.Journal of clinical medicine · 2023
    Review
  15. Article
  16. Review
  17. Article
  18. Decoding sarcoidosis chronicity through phenotypic profiling.Therapeutic advances in respiratory disease
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 1 country.

Nancy W LinDivision of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado, Aurora, CO, USA.
Jaron ArbetColorado School of Public Health, Aurora, CO, USA.
Margaret M MrozDivision of Environmental and Occupational Health Sciences, Department of Medicine, National Jewish Health, Denver, CO, USA.
Shu-Yi LiaoDivision of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado, Aurora, CO, USA.
Clara I RestrepoDivision of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado, Aurora, CO, USA.
Annyce S MayerDivision of Environmental and Occupational Health Sciences, Department of Medicine, National Jewish Health, Denver, CO, USA.
Li LiDivision of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado, Aurora, CO, USA.
Briana Q BarkesDivision of Environmental and Occupational Health Sciences, Department of Medicine, National Jewish Health, Denver, CO, USA.
Sarah SchrockColorado School of Public Health, Aurora, CO, USA.
Nabeel HamzehDepartment of Medicine, University of Iowa, Iowa City, IA, USA.
Tasha E FingerlinColorado School of Public Health, Aurora, CO, USA.
Nichole E CarlsonColorado School of Public Health, Aurora, CO, USA.
Lisa A MaierDivision of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado, Aurora, CO, USA. maierl@njhealth.org.ORCID http://orcid.org/0000-0001-6872-1769
Colorado School of Public Health · USNational Jewish Health · USUniversity of Colorado Hospital · USUniversity of Iowa · US

Funding

Genetic Risk for Granulomatous Interstitial Lung DiseaseR01HL114587 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI FINGERLIN, TASHA E. · 2013 to 2018
$3.2M
Novel integrative approaches for disease phenotyping, utilizing radiomics in SarcoidosisR01HL142049 · NHLBI · NATIONAL JEWISH HEALTH · PI CARLSON, NICHOLE, FINGERLIN, TASHA E. · 2019 to 2022
$2.6M
NHLBI NIH HHS R01 HL114587NHLBI NIH HHS R01 HL142049NIH HHS 1R01 HL142049-03NIH HHS 5R01HL114587-06
6 · The paper itself

Abstract

backgroundMost 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.

methodsWe 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.

resultsCluster 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.

conclusionsCluster 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.

Indexed as

SarcoidosisCluster AnalysisHumansPhenotypeRetrospective StudiesSeverity of Illness IndexCluster analysisDisease severityPhenotypesPulmonarySarcoidosis

Identifiers

PMID35397561
PMCPMC8994095
OpenAlexW4225545056

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.