ESTIMATING THE FINANCIAL IMPACT OF DUPILUMAB FOR COPD USING REAL-WORLD CLAIMS DATA: A PROBABILISTIC BUDGET IMPACT ANALYSIS IN THE BRAZILIAN PRIVATE HEALTH SYSTEM
Author(s)
ANTONIO ELIEZER ARRAIS MOTA FILHO, MD, PhD, Vicente Lima, Sr., MsC, Clara Matias, MBA, THAINARA ALENCAR, MBA, MATEUS SILVA, MBA, Hermano A. Rocha, MPH, PhD, MD, FLAVIO IBIAPINA, MD, PhD;
Unimed Fortaleza, Fortaleza, Brazil
Unimed Fortaleza, Fortaleza, Brazil
OBJECTIVES: To estimate the financial impact of incorporating dupilumab for the treatment of Chronic Obstructive Pulmonary Disease (COPD) within a Private Health Insurance plan in Ceará, Brazil.
METHODS: A budget impact analysis was conducted from the payer perspective using real-world unidentified data from medical claims. The eligible population was composed of 350 thousand insured people, who were sampled based on ICD-10 codes J44 to J44.9 and regulatory guidelines. These guidelines include at least one hospitalization for exacerbation and specific medication use. The model considered a 0.69% annual population growth and a progressive market uptake of dupilumab ranging from 50% (Year 1) to 90% (Year 5). Hospitalization rates were modeled as stochastic variables ranging from 1.05-1.60 events/year (standard care) and 0.7-1.06 events/year (dupilumab) based of systematic literature review. A Probabilistic Sensitivity Analysis (PSA) was performed using a Monte Carlo simulation with 5,000 iterations to assess uncertainty. Treatment costs were estimated based on the year cost of a single treatment. The purchase price of dupilumab was used and the cost of 26 doses, or 1 year of treatment, was calculated.
RESULTS: A total of 34 eligible patients were identified at baseline. In the standard care scenario, hospitalization costs remained the primary driver. The PSA estimated a mean cumulative incremental budget impact of USD 2,272,385 over five years. The 95% confidence interval ranged from USD 2,018,681 to USD 2,522,729. Despite the reduction in hospitalization events, the acquisition cost of the immunobiological therapy remained the dominant factor in the budget increase.
CONCLUSIONS: The probabilistic sensitivity analysis indicates that the incremental costs associated with dupilumab substantially outweigh the cost offsets achieved through avoided hospital admissions. These findings highlight the importance of budget impact analyses to support evidence-based decision making and to inform the development of sustainable reimbursement and implementation strategies.
METHODS: A budget impact analysis was conducted from the payer perspective using real-world unidentified data from medical claims. The eligible population was composed of 350 thousand insured people, who were sampled based on ICD-10 codes J44 to J44.9 and regulatory guidelines. These guidelines include at least one hospitalization for exacerbation and specific medication use. The model considered a 0.69% annual population growth and a progressive market uptake of dupilumab ranging from 50% (Year 1) to 90% (Year 5). Hospitalization rates were modeled as stochastic variables ranging from 1.05-1.60 events/year (standard care) and 0.7-1.06 events/year (dupilumab) based of systematic literature review. A Probabilistic Sensitivity Analysis (PSA) was performed using a Monte Carlo simulation with 5,000 iterations to assess uncertainty. Treatment costs were estimated based on the year cost of a single treatment. The purchase price of dupilumab was used and the cost of 26 doses, or 1 year of treatment, was calculated.
RESULTS: A total of 34 eligible patients were identified at baseline. In the standard care scenario, hospitalization costs remained the primary driver. The PSA estimated a mean cumulative incremental budget impact of USD 2,272,385 over five years. The 95% confidence interval ranged from USD 2,018,681 to USD 2,522,729. Despite the reduction in hospitalization events, the acquisition cost of the immunobiological therapy remained the dominant factor in the budget increase.
CONCLUSIONS: The probabilistic sensitivity analysis indicates that the incremental costs associated with dupilumab substantially outweigh the cost offsets achieved through avoided hospital admissions. These findings highlight the importance of budget impact analyses to support evidence-based decision making and to inform the development of sustainable reimbursement and implementation strategies.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
EE285
Topic
Economic Evaluation
Topic Subcategory
Budget Impact Analysis, Cost/Cost of Illness/Resource Use Studies
Disease
SDC: Respiratory-Related Disorders (Allergy, Asthma, Smoking, Other Respiratory), STA: Biologics & Biosimilars