Predicting allergen immunotherapy efficacy based on early maintenance phase response in routine clinical practice

While allergen-specific immunotherapy (AIT) is acknowledged as an effective treatment, its efficacy varies, and consensus on predictive indicators for AIT responders remains elusive.

This study aimed to identify alternative parameters for predicting AIT responders based on clinical data collected in daily practice.

We conducted a retrospective analysis of patients with house-dust-mite-driven asthma and/or rhinitis who completed 3 years of subcutaneous AIT (3y-AIT). We assessed the efficacy of AIT using the estimated daily symptom and medication score (edSMS) during different treatment periods, including up-dosing, maintenance I, II, and III phases. These scores were derived from detailed records of symptoms and medication use for AIT injections. A responder was defined as an individual with a reduction in edSMS of at least 30% from up-dosing to maintenance III phase (ΔedSMS_U-M3).

A cohort of 133 patients was analyzed, revealing a significant overall improvement in the disease condition after 3y-AIT. Responders demonstrated lower rates of polysensitization, daily tobacco smoke exposure, and milder pretreatment disease severity compared to non-responders (p = 0.003, p = 0.001, and p = 0.019, respectively). We observed 8 clinical response patterns among included subjects, but only a small group of patients (16/133, 12.03%) demonstrated consistent improvement throughout the 3y-AIT. Serum total immunoglobulin E (tIgE), specific immunoglobulin E (sIgE), sIgE/tIgE ratios, and edSMS during the up-dosing phase failed to differentiate the clinical response patterns or correlate with 3y-AIT efficacy. Notably, the reduction in edSMS from up-dosing phase to maintenance I phase (ΔedSMS_U-M1) significantly associated with the 3y-AIT outcome (r = 0.443, p < 0.001). Receiver-operating characteristic curves indicated that ΔedSMS_U-M1, with a cut-off of 18.40%, effectively predicted responders (AUC: 0.75, sensitivity: 76.20%, specificity: 76.70%).

The individualized clinical responses to AIT may pose challenges in identifying predictors for treatment efficacy. Nonetheless, despite this complexity, our study highlights that the effectiveness observed in the early maintenance phase serves as a suitable predictor of 3y-AIT outcomes.