Use of discriminant analysis in assessing pulmonary function worsening in patients with sarcoidosis by a panel of inflammatory biomarkers View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-12-23

AUTHORS

Gregorino Paone, Alvaro Leone, Sandro Batzella, Vittoria Conti, Francesco Belli, Laura De Marchis, Alice Mannocci, Giovanni Schmid, Claudio Terzano

ABSTRACT

Objectives and designTo date, no sufficiently sensitive and specific single marker has been found to predict the clinical course of sarcoidosis. We designed a cohort study to investigate whether a panel of biomarkers measured in bronchoalveolar lavage (BAL) and peripheral blood could help predict pulmonary function worsening during the clinical course of sarcoidosis.MethodsWe analyzed 30 individuals with histologically proven sarcoidosis. At baseline, participants underwent pulmonary function tests (PFTs), fiberoptic bronchoscopy and radiological investigations. BAL and blood cellular profiles were obtained from all individuals and six pro-inflammatory molecules were quantified in BAL and serum. PFTs were performed at follow-up visits over a 2-year period. Using discriminant function analysis, a canonical variable was generated to optimize the accuracy of selected variables in predicting pulmonary function worsening and was validated on a subset of nine consecutive individuals with sarcoidosis.ResultsA combination of 6 markers from BAL was able to predict pulmonary function worsening in 96 % of patients [95 % confidence interval (CI) 84.4–99.81]. We validated the generated formula on a group of nine patients with sarcoidosis, obtaining 77.8 % correct classification (95 % CI 45.3–93.7).ConclusionsOur results show that a combinational approach could contribute to identifying individuals likely to experience pulmonary function worsening, thus helping to decide the correct therapeutic strategies. More... »

PAGES

325-332

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00011-012-0585-9

DOI

http://dx.doi.org/10.1007/s00011-012-0585-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1031399329

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23262919


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