INTRODUCTION
As a high prevalent condition, asthma generates a substantial economic
burden to the society and health care systems (1,2). Allergic asthma
(AA) is the most frequent phenotype and is defined by the presence of
sensitization to environmental allergens. Patients with AA experience a
considerable burden in terms of poor health-related quality-of-life,
productivity loss and healthcare resource utilization (HCRU) that
increases with severity (3).
Inhaled corticosteroids (ICS) are the first line therapy recommended for
the control of asthma symptoms due to their high anti-inflammatory
effect. Despite its proven cost-effectiveness, their efficacy depends on
its constant use over time and some patients remain with persistent
symptoms resulting in adverse events in the long-term (4,5). New
strategies with potential disease modifying effects should be evaluated
in terms of their clinical and economic implications. Allergen
immunotherapy (AIT) is the only therapy that can modify the progression
of allergic diseases by inducing immune tolerance (6). It is associated
with reduction of HCRU and protective effect that can translate in
potential cost-savings (7–9). Previous research suggests that AIT may
be cost-effective for the treatment of patients with asthma (10,11).
However, studies evaluating the cost-effectiveness of SCIT with HDM have
been frequently based in randomized controlled trials (RCTs), and the
use of relevant outcomes like exacerbations and medication step down is
lacking. Potential differences in the cost-effectiveness across
populations (e.g., children vs adults, patients with AA-only vs patients
with AA and allergic rhinitis [AR]) have also been underexplored
(10,12).
Model-based cost-effectiveness evaluations allows the combination of
multiple sources of evidence, extrapolating results beyond the study
length of clinical trials and converting treatment effects into
policy-relevant outcomes (10,12). In this study, we sought to evaluate
the cost-effectiveness of SCIT + ICS vs ICS for pediatric and adult
patients with AA and AA with AR in Colombia through a decision-analytic
modeling approach and multiple data sources, including parameters from
real-world studies.