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Serum IgE and eosinophil count in allergic rhinitis--analysis using a modified Bayes' theorem
M Demirjian1, J S Rumbyrt, V C Gowda
1Division of Allergy & Immunology, Department of Medicine, Veterans Affairs Greater Los Angeles Healthcare System, The David Geffen School of Medicine at UCLA, CA, USA. mdemirjian@mednet.ucla.edu
Background:
To use probability theory to establish threshold values for total serum IgE and eosinophil counts that support a diagnosis of allergic rhinitis and to compare our results with previously published data.
Methods:
Prospective study of rhinitis patients using a modified version of Bayes' theorem. Study included 125 patients at the West Los Angeles VA Medical Center diagnosed with rhinitis who completed allergy consultation and immediate hypersensitivity skin testing.
Results:
Eighty-nine of 125 patients were atopic by prick and/or intradermal skin testing. Using a modified version of Bayes' theorem and positive and negative probability weights, calculations for different thresholds of serum IgE and eosinophil counts were summated and a posttest probability for atopy was calculated. Calculated posttest probabilities varied according to the threshold used to determine a positive or negative test; however, IgE thresholds greater than 140IU/ml and eosinophil counts greater that 80cells/ml were found to have a high probability of predicting atopy in patients with rhinitis. Moreover, IgE had a greater influence than eosinophil count in determining posttest probability of allergy in this population. Considerable differences were noted in the IgE levels of atopic and non-atopic patients, including those with asthma or a history of smoking. However, these differences were not observed with eosinophil levels.
Conclusions:
Using a modified version of Bayes' theorem to determine posttest probability, IgE threshold levels greater than 140IU/ml and eosinophil counts greater than 80cells/ml in an individual with clinical signs and symptoms of rhinitis are likely to correlate with an atopic aetiology. This model of probability may be helpful in evaluating individuals for diagnostic skin testing and certain types of allergy-modifying treatment.
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