TY - JOUR
T1 - A novel statistical model for analyzing data of a systematic review generates optimal cutoff values for fractional exhaled nitric oxide for asthma diagnosis
AU - Schneider, Antonius
AU - Linde, Klaus
AU - Reitsma, Johannes B.
AU - Steinhauser, Susanne
AU - Rücker, Gerta
N1 - Publisher Copyright:
© 2017 The Authors
PY - 2017/12
Y1 - 2017/12
N2 - Objectives Measurement of fractional exhaled nitric oxide (FENO) might substitute bronchial provocation for diagnosing asthma. However, optimal FENO thresholds for diagnosing asthma remain unclear. We reanalyzed data collected for a systematic review investigating the diagnostic accuracy of FENO measurement to exploit all available thresholds under consideration of pretest probabilities using a newly developed statistical model. Study Design and Setting 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. Results Diagnosing asthma might only be possible in a meaningful manner when the pretest probability of asthma is at least 30%. In that case, FENO > 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, FENO < 20 ppb leads to a negative predictive value of 0.86 (95% CI 0.66–0.95). Conclusion 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 FENO measurement.
AB - Objectives Measurement of fractional exhaled nitric oxide (FENO) might substitute bronchial provocation for diagnosing asthma. However, optimal FENO thresholds for diagnosing asthma remain unclear. We reanalyzed data collected for a systematic review investigating the diagnostic accuracy of FENO measurement to exploit all available thresholds under consideration of pretest probabilities using a newly developed statistical model. Study Design and Setting 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. Results Diagnosing asthma might only be possible in a meaningful manner when the pretest probability of asthma is at least 30%. In that case, FENO > 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, FENO < 20 ppb leads to a negative predictive value of 0.86 (95% CI 0.66–0.95). Conclusion 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 FENO measurement.
KW - Asthma
KW - Diagnostic accuracy
KW - Fractional exhaled nitric oxide
KW - Receiver operating characteristic analysis
KW - Sensitivity
KW - Specificity
UR - http://www.scopus.com/inward/record.url?scp=85030644832&partnerID=8YFLogxK
U2 - 10.1016/j.jclinepi.2017.09.001
DO - 10.1016/j.jclinepi.2017.09.001
M3 - Review article
C2 - 28916487
AN - SCOPUS:85030644832
SN - 0895-4356
VL - 92
SP - 69
EP - 78
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
ER -