STATISTICAL APPROACHES TO THE IDENTIFICATION OF LATE ASTHMATIC REACTIONS

Late asthmatic reactions can be difficult to recognize because of thei r prolonged time course and the confounding effects of superimposed ci rcadian rhythms of ventilatory function. Conventional methods of analy sis are rather arbitrary. They depend for example on a 15 or 20% fall in forced expiratory volume in one second (FEV(1)) from baseline or fr om time-matched control measurements. We have, therefore, investigated whether statistical approaches applied to individual subjects can ass ist in the identification of late asthmatic reactions. In two separate series of aerosol inhalation tests, three symptomatic workers, three asthmatic controls and three nonasthmatic controls were challenged bli ndly with increasing doses of two chemical agents, and saline. One of the agents, sodium isononanoyl oxybenzene sulphonate (SINOS) was a sus pected cause of occupational asthma Prior to the challenges, FEV(1) wa s measured hourly on three control days. Cumulative late changes on bo th control and active challenge days were quantified as the area betwe en a line extrapolated from a 10.00 h baseline and the actual measurem ents from 12.00-22.00 h (the 2-12 h area decrement). The area decremen t measurements on control and active challenge days were compared usin g Student's t-tests. The sensitivity of this method for detecting late asthmatic reactions among potentially positive tests (SINOS challenge tests in the workers) was examined, as was its specificity. The latte r was determined from the false positive rate among the negative tests . A second statistical method based on the pooled standard deviation o f serial (hourly) FEV(1) measurements was investigated in the same way . In total, the data from 220 challenge and 30 control days were avail able for analysis. Late responses associated with falls in FEV(1) of 8 -16% were statistically significant when a t-test was used to compare area decrement on each active challenge day with three control days. T his approach was, therefore, potentially more sensitive than conventio nal techniques for identifying late asthmatic reactions. The false pos itive rate was 4%. The serial FEV(1) method was more sensitive, identi fying a further five positive tests, but was less specific, with a fal se positive rate of 7%. These results suggest that when the day-to-day variability of lung function has been estimated from at least three c ontrol days, statistical tests can be applied to potential late asthma tic reactions, allowing them to be identified with greater precision t han conventional clinical techniques.