Physician-derived asthma diagnoses made on the basis of questionnaire data are in good agreement with interview-based diagnoses and are not affected by objective tests.

BACKGROUND

Defining the phenotype is critical for investigating the genetic etiology of asthma. As part of the Collaborative Study on the Genetics of Asthma (CSGA), the primary objective of which is to identify asthma susceptibility loci, an algorithm was designed to determine diagnoses of definite asthma, probable asthma, less than probable asthma, or no asthma. A respiratory questionnaire was designed to assist in the process of characterizing the asthma phenotype.

OBJECTIVE

This study was designed to determine the validity of the CSGA algorithm for the diagnosis of asthma, to determine agreement in assessing an asthma diagnosis between the information obtained by the CSGA questionnaire versus a patient interview by a panel of specialist physicians, and to determine the degree to which objective tests would alter the questionnaire-based certainty of asthma diagnosis.

METHODS

An expert panel of asthma clinicians (n = 4) indicated to what degree they were certain that a subject (n = 48) had asthma as determined by using a 6-point Likert scale based on a 20-minute interview (phase I), a review of the CSGA questionnaire (phase II), a review of the questionnaire plus skin test and peripheral blood eosinophilia data (phase III), and a review of phase III information plus pulmonary data (spirometry and methacholine-reversibility testing; IV). Intraclass correlation coefficients (ICCs) were calculated between the physicians' interpretation of the likelihood of asthma based on the information they received during each of the phases and between the CSGA algorithm and each of the phases.

RESULTS

Interjudge reliability with regard to the degree of certainty with which an asthma diagnosis could be made by interview was excellent (ICC, 98; 95% confidence intervals [95% CIs], 0.87-0.99). We also found that the agreement between the physicians' interview with the patients (phase I) and the CSGA algorithm was good and at least as good with the addition of the CSGA questionnaire data and objective data (ICC, 0. 65-0.75). Good agreement was also observed between the average certainty score from the interview and the CSGA questionnaire (ICC, 92; 95% CI, 0.76-0.93), and ICCs determining the agreement on asthma diagnosis between phase I and phases III and IV, in which objective data were introduced, did not change from the ICCs comparing phase I with phase II (ICC of 0.93 [95% CI, 0.79-0.96] and ICC of 0.91 [95% CI 0.73-0.95], respectively).

CONCLUSION

We conclude that the CSGA algorithm is a valid tool for which the diagnosis of asthma can be made at an acceptable level of certainty and that the CSGA questionnaire, interpreted by an asthma specialist, is a useful tool for the diagnosis of asthma in clinical or epidemiologic studies.