Clinical Utility Findings of a Transcriptomic Psoriasis Biologic Test Demonstrate Altered Physician Prescribing...

Area of Science:

• Dermatology
• Computational Biology
• Translational Medicine

Background:

• Psoriasis management often involves a trial-and-error approach for biologic selection.
• Predicting patient response to biologics is crucial for effective psoriasis treatment.

Purpose of the Study:

• To evaluate the clinical utility of Mind.Px, a machine learning tool predicting biologic response in psoriasis patients.
• To assess if Mind.Px test results influence physician decision-making and improve patient outcomes.

Main Methods:

• A randomized prospective study (MATCH) enrolled 210 biologic-naïve or switching psoriasis patients.
• Physicians in the informed arm received Mind.Px test results prior to biologic selection.
• Patient outcomes were assessed using Psoriasis Area and Severity Index (PASI) at weeks 4 and 12.

Main Results:

• Physician concordance with Mind.Px results was significantly higher (92.3%) compared to standard care (62.9%).
• Patients whose physicians utilized Mind.Px showed significantly higher rates of achieving PASI75 at 12 weeks (p=5.4×10⁻⁴) and week 4 (p=0.01).

Conclusions:

• Mind.Px demonstrates clinical utility by guiding biologic selection and improving patient outcomes in psoriasis management.
• The tool minimizes trial-and-error treatment, offering benefits for physicians, patients, and healthcare systems.
• Improved patient outcomes may lead to potential healthcare cost savings.