Phenotypical spectrum of asthma patients presenting to the outpatient clinic

Several diagnostic and treatment algorhythms regarding asthma have been described in previous guidelines. Yet these descriptions fail at reflecting different phenotypes of asthma encountered in clinical practice. The purpose of this study is to retrospectively analyze the data of asthma patients that have presented to the Gazi University Medical Faculty (GUMF), Pulmonary Diseases outpatient clinic and to group the patients according to the pre-bronchodilator FEV1 value, post-bronchodilator FEV1 value, age of asthma onset while evaluating the common characteristics of the different clusters. Patients that had presented to the GUMF Pulmonary Diseases outpatient clinic between 1995-2003 were analyzed for the study. Of these patients, 246 patients that had been diagnosed with asthma and had complete data records were recruited for this study. These patients were categorized under five phenotypic clusters according to the three variables (pre-bronchodilator FEV1 value, post-bronchodilator FEV1 value, age of asthma onset) of the SARP algorhythm and were evaluated accordingly. Cluster 4 had the highest number of patients while Cluster 5 had the least number of patients within our study. Allergic rhinitis and sinusitis were mostly encountered in Clusters 1 and 2. Obesity and gastro-esophageal reflux was thought to be the reason behind the fixed obstruction seen in patients of Cluster 5. Multiple drug treatment regimens were also mostly used for patients in Cluster 5. This led us to think that Cluster 5 asthma was the most difficult group to obtain control. Unlike the SARP study, atopy was encountered the most in Cluster 2. In conclusion, phenotypical distribution and cluster analysis using the pre-bronchodilator FEV1 value, post-bronchodilator FEV1 value and age of asthma onset is an easy and effective classification system that can both be used for the Turkish population and to set guidelines and strategies for treatment of difficult asthma cases according to different clusters.