A novel statistical model for analyzing data of a systematic review generates optimal cutoff values for fractional exhaled nitric oxide for asthma diagnosis.

Schneider, Antonius; Linde, Klaus; Reitsma, Johannes B; Steinhauser, Susanne; Rücker, Gerta

doi:10.1016/j.jclinepi.2017.09.001

2017

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Title:: A novel statistical model for analyzing data of a systematic review generates optimal cutoff values for fractional exhaled nitric oxide for asthma diagnosis.
Document type:: Journal Article; Review; Review
Author(s):: Schneider, Antonius; Linde, Klaus; Reitsma, Johannes B; Steinhauser, Susanne; Rücker, Gerta
Abstract:: Measurement of fractional exhaled nitric oxide (FE) might substitute bronchial provocation for diagnosing asthma. However, optimal FE thresholds for diagnosing asthma remain unclear. We reanalyzed data collected for a systematic review investigating the diagnostic accuracy of FE measurement to exploit all available thresholds under consideration of pretest probabilities using a newly developed statistical model.One hundred and fifty data sets for a total of 53 different cutoffs extracted from 26 studies with 4,518 participants were analyzed with the multiple thresholds model. This model allows identifying thresholds at which the test is likely to perform best.Diagnosing asthma might only be possible in a meaningful manner when the pretest probability of asthma is at least 30%. In that case, FE > 50 ppb leads to a positive predictive value of 0.76 [95% confidence interval (CI): 0.29-0.96]. Excluding asthma might only be possible, when the pretest probability of asthma is 30% at maximum. Then, FE < 20 ppb leads to a negative predictive value of 0.86 (95% CI 0.66-0.95).The multiple thresholds model generates a more comprehensive and more clinically useful picture of the effects of different thresholds, which facilitates the determination of optimal thresholds for diagnosing or excluding asthma with FE measurement.
Journal title abbreviation:: J Clin Epidemiol
Year:: 2017
Journal volume:: 92
Pages contribution:: 69-78
Language:: eng
Fulltext / DOI:: doi:10.1016/j.jclinepi.2017.09.001
Pubmed ID:: http://view.ncbi.nlm.nih.gov/pubmed/28916487
Print-ISSN:: 0895-4356
TUM Institution:: Lehrstuhl für Allgemeinmedizin (Prof. Schneider) (keine SAP-Zuordnung!)
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mediaTUM Gesamtbestand Hochschulbibliographie 2017 Fakultäten Medizin Institut für Allgemeinmedizin (keine SAP-Zuordnung!)

mediaTUM Gesamtbestand Einrichtungen Schools TUM School of Medicine and Health Departments Clinical Medicine Institut für Allgemeinmedizin und Versorgungsforschung (Prof. Schneider)Lehrstuhl für Allgemeinmedizin (Prof. Schneider)2017