Predicting clinical remission in biologic-treated severe asthma: development of a practical scoring system from a...

Biologics have improved clinical remission (CR) rates in severe asthma; however, practical tools for predicting CR are lacking. Our goal was to create a straightforward, interview-based scoring system applicable across various care settings.

This retrospective multicentre study formed exploratory and validation cohorts of adults with severe asthma starting biologic treatment. The primary outcome was achievement of 3-domain CR (no maintenance OCS, no exacerbation, asthma control test (ACT) ≥23). Each baseline characteristic was tested using univariable logistic regression; those with p<0.05 were included in a multivariable model to identify independent predictors. These predictors were combined into a point-based score. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) and externally validated.

The analysis included 281 patients in the exploratory cohort and 53 in the validation cohort. Three-domain CR occurred in 37.7% (106/281) of the exploratory cohort and 35.9% (19/53) of the validation cohort. In the exploratory cohort, male sex (OR, 2.34; 95% CI 1.22 to 4.57), ACT score ≥20 (OR, 3.75; 95% CI 1.96 to 7.36) and comorbid chronic rhinosinusitis (CRS) (OR, 3.27; 95% CI 1.61 to 6.93) were associated with 3-domain CR. We developed a scoring system by assigning 1 point each for male sex (M), ACT ≥20 (A) and comorbid CRS (C), termed MAC score, which showed good discrimination (AUC 0.73; 95% CI 0.68 to 0.79) and was externally validated (AUC 0.76; 95% CI 0.60 to 0.91).

The MAC score, a three-item metric derived from routinely accessible information, effectively predicts 3-domain CR and can be implemented across a range of healthcare settings, from primary care clinics to tertiary hospitals.