Predictors of nonresponse to dupilumab in patients with atopic dermatitis: A machine learning analysis

Abstract

Background: Many patients with atopic dermatitis (AD) have a suboptimal response to systemic therapy.

Objective: This study assessed predictors of nonresponse to dupilumab in patients with AD.

Methods: Data (April 2017 through June 2019) for patients aged 12 years and above with AD (International Classification of Diseases-9/10-Clinical Modification: 691.8/L20.x) who initiated dupilumab on or after April 1, 2017 (index date) were collected from an electronic health record and insurance claims database. Nonresponse indicators (dupilumab discontinuation, addition of another systemic therapy or phototherapy, addition of a high-potency topical corticosteroid, AD-related hospital visit, AD-related emergency department visit, incident skin infection) were predicted from available demographic and clinical variables using machine learning.

Results: Among 419 patients (mean age: 45 years), 145 (35%) experienced at least 1 indicator of nonresponse in the 6-month postindex period. In patients with at least 1 indicator, the most common was dupilumab discontinuation (47% [68/145]). Of note, this analysis could not capture nonmedical reasons for dupilumab discontinuation (eg, cost, access). The most common predictors of nonresponse were a claim for ibuprofen (in 69% of patients with a nonresponse indicator) and a Quan-Charlson Comorbidity Index value of 3 to 4 (59%).

Conclusion: Systemic dupilumab therapy for AD can be associated with a relatively high prevalence of nonresponse indicators. Factors associated with these indicators-that is, predictors of nonresponse-may be used to optimize disease management.