Are asthma symptom intensity scales better than biomarkers for diagnosing asthma? A prospective observational study

Background: Misdiagnosis of asthma in primary care (PC) has been reported in the literature, producing adverse consequences to patients’ health-related quality of life and to health care systems.

Aims and objectives: Our main objective was to explore the diagnostic power of each classical symptoms of asthma, measured through visual analogue scales (VAS), and to compare them with classic biomarkers.

Methods: We conducted a prospective observational study (01/03/18 - 31/12/19) including 177 patients with suspected asthma recruited from the University asthma clinic of Liège (Belgium). They were asked to rate the intensity level of the 5 classic asthma symptoms (cough, chest tightness, secretion, dyspnea & wheezing) using VAS. Predicting values (PV) of symptom intensity, biomarkers (blood eosinophils, total serum IgE, FeNO) and spirometric indices to make asthma diagnosis (GINA criteria) were assessed by ROC curves.

Results: Among the 177 patients 107 had a confirmed asthma diagnosis. The area under the curve (AUC) of the ROC curves showed that wheezing was the symptom which predicted the best the presence of asthma (AUC=0.64 ;95% CI: 0.56 - 0.72). None of the biomarkers had sufficient PV. FEV1/FVC ratio, and to a lesser extent FEV1, had significant PV, with an AUC equal to 0.75 (0.67-0.82) and 0.71 (0.64-0.79) respectively. Combining wheezing with FEV1 and FEV1/FVC provided a good discriminative capacity with an AUC of 0.79 (0.72-0.85) (p<0.001).

Conclusion: Combining wheezing to spirometry yields very good PV for correct diagnosis. Our model should now be tested and validated in a PC setting, because it offers a quick and minimally invasive way to diagnose asthma.