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

Publication date: Available online 12 September 2017
Source:Journal of Clinical Epidemiology
Author(s): Antonius Schneider, Klaus Linde, Johannes B. Reitsma, Susanne Steinhauser, Gerta Rücker
ObjectiveMeasurement of fractional exhaled nitric oxide (FENO) might substitute bronchial provocation for diagnosing asthma. However, optimal FENO thresholds for diagnosing asthma remain unclear. We re-analyzed data collected for a systematic review investigating the diagnostic accuracy of FENO measurement to exploit all available thresholds under consideration of pre-test probabilities using a newly developed statistical model.Study Design150 data-sets for a total of 53 different cut-offs extracted from 26 studies with 4518 participants were analyzed with the multiple thresholds model. This model allows identifying thresholds at which the test is likely to perform best.ResultsDiagnosing asthma might only be possible in a meaningful manner when the pre-test probability of asthma is at least 30%. In that case, FENO > 50ppb leads to a positive predictive value of 0.76 (95%CI 0.29 – 0.96). Excluding asthma might only be possible, when the pre-test probability of asthma is 30% at maximum. Then FENO < 20ppb leads to a negative predictive value of 0.86 (95%CI 0.66 – 0.95).ConclusionThe 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 FENO measurement.



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