Are peak flow and symptom measures good predictors of asthma hospitalizations and unscheduled visits?

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Epidemiologic studies of pediatric respiratory health often include objective measures such as peak expiratory flow (PEF), and subjective measures such as symptom reports. These measures, however, are poorly correlated with each other, and there is little evidence that PEF is useful in predicting important health outcomes. Within a cohort of 791 inner-city children with asthma, we examined correlations between a series of five peak flow measures and five symptom scores obtained from 2-week diaries. The strongest correlations were found between "total peak flow lability" defined as: [(diary maximum - diary minimum)/diary mean] and "% of days with chest tightness" (r = 0.31). Logistic models evaluated peak flow and symptoms as predictors of an important health outcome: hospitalization or emergency department or unscheduled clinic visit for asthma within 30 days of starting the diary. Each of the peak flow and symptom measures was significantly related to utilization. However, the predictive power of each measure was low (range of area under ROC curve, 0.54-0.67). Models including only peak flow or symptoms had greater prediction than models with risk factors such as atopy, asthma persistence, and age. The prediction from a model with the risk factors and symptoms was not improved by adding a peak flow measure to the model (increase in area under ROC, 0.67-0.68). Stratified analyses suggest that prediction was similar in the fall vs. winter, spring, and summer months. Greater prediction of health outcomes was found among more persistent asthmatics and children who were nonatopic. These findings suggest that in a research setting, peak flow monitoring in children did not add prediction beyond that obtained from symptom reports. Pediatr Pulmonol. 2001; 31:190-197. Published 2001 Wiley-Liss, Inc.