Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis

RationaleWe hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality.MethodsConsecutive patients with ARDS were included in this prospec...

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Veröffentlicht in:Thorax Jg. 72; H. 10; S. 876 - 883
Hauptverfasser: Bos, L D, Schouten, L R, van Vught, L A, Wiewel, M A, Ong, D S Y, Cremer, O, Artigas, A, Martin-Loeches, I, Hoogendijk, A J, van der Poll, T, Horn, J, Juffermans, N, Calfee, C S, Schultz, M J
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England BMJ Publishing Group LTD 01.10.2017
Schlagworte:
Aged
Angiopoietin-1 - blood
Angiopoietin-2 - blood
Biomarkers - blood
Cluster Analysis
Female
Humans
Intensive care
Intensive Care Units
Interferon-gamma - blood
Interleukin-6 - blood
Male
Middle Aged
Mortality
Phenotype
Plasminogen Activator Inhibitor 1 - blood
Predictive Value of Tests
Prospective Studies
Respiratory Distress Syndrome, Adult - blood
Respiratory Distress Syndrome, Adult - mortality
Respiratory therapy
Cytokine Biology
ARDS
ISSN:0040-6376, 1468-3296, 1468-3296
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Zusammenfassung:RationaleWe hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality.MethodsConsecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality.ResultsTwo phenotypes were identified in 454 patients, which we named ‘uninflamed’ (N=218) and ‘reactive’ (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p<0.001) in the training cohort and 13.6% and 37.5% (p<0.001) in the validation cohort (N=207). The ‘reactive phenotype’ was independent from confounders associated with intensive care unit mortality (training cohort: OR 1.13, 95% CI 1.04 to 1.23; validation cohort: OR 1.18, 95% CI 1.06 to 1.31).ConclusionsPatients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS.
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A complete list of members of the MARS Consortium is given in the appendix
ISSN:0040-6376
1468-3296
1468-3296
DOI:10.1136/thoraxjnl-2016-209719