Modelling Treatment Sequences in Immunology: Optimizing Patient Outcomes

Area of Science:

• Immunology and Pharmacoepidemiology
• Health Economics and Outcomes Research

Background:

• Limited evidence exists on optimal treatment sequencing for immune-mediated disorders.
• Treatment selection impacts patient outcomes and healthcare system costs.
• Investigating treatment sequences is crucial for improving care in conditions like ankylosing spondylitis and rheumatoid arthritis.

Purpose of the Study:

• To model the impact of optimal treatment sequencing on effectiveness and budget reallocation.
• To analyze treatment sequences for ankylosing spondylitis, Crohn's disease, plaque psoriasis, rheumatoid arthritis, and ulcerative colitis in an Italian setting.
• To identify best practices for sequencing biological or disease-modifying treatments.

Main Methods:

• A 3-year state-transition model simulated potential effectiveness improvements and budget considerations.
• Analyzed sequences of three biological or disease-modifying treatments followed by best supportive care.
• Utilized published network meta-analyses and real-world data, differentiating between biologic-naïve and experienced populations.

Main Results:

• Optimal sequences consistently involved using the most efficacious therapies earlier in the treatment pathway.
• Significant improvements in prescribing practice were identified, particularly for ulcerative colitis.
• Using top-tier sequences reduced treatment failures by 15.1% with a 1.59% increase in drug costs.

Conclusions:

• Prioritizing more efficacious treatments earlier in the sequence enhances patient outcomes.
• Strategic treatment sequencing minimizes treatment failures across various immune-mediated diseases.
• Optimized sequencing offers a pathway to improved patient care and resource management.