Reference values for methacholine reactivity (SAPALDIA study) - Jayet, Pierre-Yves (BioMed Central, 2005)
BACKGROUND: The distribution of airway responsiveness in a general population of non-smokers without respiratory symptoms has not been established, limiting its use in clinical and epidemiological practice. We derived reference equations depending on individual characteristics (i.e., sex, age, baseline lung function) for relevant percentiles of the methacholine two-point dose-response slope. METHODS: In a reference sample of 1567 adults of the SAPALDIA cross-sectional survey (1991), defined by excluding subjects with respiratory conditions, responsiveness during methacholine challenge was quantified by calculating the two-point dose-response slope (O'Connor). Weighted L1-regression was used to estimate reference equations for the 95(th ), 90(th ), 75(th )and 50(th )percentiles of the two-point slope. RESULTS: Reference equations for the 95(th ), 90(th ), 75(th )and 50(th )percentiles of the two-point slope were estimated using a model of the form a + b* Age + c* FEV(1 )+ d* (FEV(1))(2 ), where FEV(1 )corresponds to the pre-test (or baseline) level of FEV(1). For the central half of the FEV(1 )distribution, we used a quadratic model to describe the dependence of methacholine slope on baseline FEV(1). For the first and last quartiles of FEV(1), a linear relation with FEV(1 )was assumed (i.e., d was set to 0). Sex was not a predictor term in this model. A negative linear association with slope was found for age. We provide an Excel file allowing calculation of the percentile of methacholine slope of a subject after introducing age – pre-test FEV(1 )– and results of methacholine challenge of the subject. CONCLUSION: The present study provides equations for four relevant percentiles of methacholine two-point slope depending on age and baseline FEV(1 )as basic predictors in an adult reference population of non-obstructive and non-atopic persons. These equations may help clinicians and epidemiologists to better characterize individual or population airway responsiveness.