Asthma exacerbations during pregnancy are common and can be associated with substantial maternal and fetal morbidity. Treatment decisions based on sputum eosinophil counts reduce exacerbations in non-pregnant women with asthma, but results with the fraction of exhaled nitric oxide (FENO) to guide management are equivocal. We tested the hypothesis that a management algorithm for asthma in pregnancy based on FENO and symptoms would reduce asthma exacerbations.
We undertook a double-blind, parallel-group, controlled trial in two antenatal clinics in Australia. 220 pregnant, non-smoking women with asthma were randomly assigned, by a computer-generated random number list, before 22 weeks’ gestation to treatment adjustment at monthly visits by an algorithm using clinical symptoms (control group) or FENO concentrations (active intervention group) used to uptitrate (FENO >29 ppb) or downtitrate (FENO <16 ppb) inhaled corticosteroid dose. Participants, caregivers, and outcome assessors were masked to group assignment. Longacting β2 agonist and minimum dose inhaled corticosteroid were used to treat symptoms when FENO was not increased. The primary outcome was total asthma exacerbations (moderate and severe). Analysis was by intention to treat. This study is registered with the Australian and New Zealand Clinical Trials Registry, number 12607000561482.
111 women were randomly assigned to the FENO group (100 completed) and 109 to the control group (103 completed). The exacerbation rate was lower in the FENO group than in the control group (0·288 vs 0·615 exacerbations per pregnancy; incidence rate ratio 0·496, 95% CI 0·325—0·755; p=0·001). The number needed to treat was 6. In the FENO group, quality of life was improved (score on short form 12 mental summary was 56·9 [95% CI 50·2—59·3] in FENO group vs 54·2 [46·1—57·6] in control group; p=0·037) and neonatal hospitalisations were reduced (eight [8%] vs 18 [17%]; p=0·046).
Asthma exacerbations during pregnancy can be significantly reduced with a validated FENO-based treatment algorithm.
National Health and Medical Research Council of Australia.