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Multiple Biologics for Multiple T2 Diseases: A Pharmacoepidemiological Algorithm for Sorting Out Patients by
Jeremy Charriot1, Vincent Descamps2, Roger Jankowski3
1Department of Respiratory Diseases, University of Montpellier, PhyMedExp, INSERM, CNRS UMR, CHU Montpellier, Montpellier, France.
An algorithm successfully identified patients with Type 2 (T2) diseases, such as severe asthma and atopic dermatitis, receiving biologics (Bx) and targeted synthetic drugs (TSD). This method aids in tracking prescription trends for these advanced therapies.
Area of Science:
- Pharmacology
- Immunology
- Data Science
Background:
- Several biologics (Bx) and targeted synthetic drugs (TSD) are available for treating Type 2 (T2) inflammatory diseases.
- These conditions include chronic spontaneous urticaria (CSU), severe asthma (SA), chronic rhinosinusitis with nasal polyposis (CRSwNP), and atopic dermatitis (AD).
Purpose of the Study:
- To develop and validate an algorithm for identifying patients treated with Bx/TSD using a dynamic dispensing database.
- To determine the primary indications for Bx/TSD prescriptions within a real-world setting.
Main Methods:
- Utilized the LRx database, covering approximately 45% of French retail pharmacies.
- Included patients with at least one Bx/TSD dispensing between April 2021 and March 2022.
- Designed a 3-step algorithm analyzing prior drug dispensations since March 2012 to ascertain prescription indications.
Main Results:
- The algorithm identified 21,677 patients receiving Bx/TSD, with 91.7% having a confirmed T2 disease indication.
- Severe asthma (SA) was the most common reason for Bx/TSD initiation (52%), followed by atopic dermatitis (AD) (29%).
- Specific drug patterns emerged, with omalizumab frequently used for SA and dupilumab predominantly for AD.
Conclusions:
- The developed algorithm effectively identifies patients with T2 diseases undergoing Bx/TSD treatment.
- This methodology offers a valuable tool for monitoring future prescription patterns and treatment evolutions in T2 diseases.
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