Using EP50 to forecast treatment adherence in individuals with multiple sclerosis

Area of Science:

• Decision Science
• Behavioral Economics
• Neuroscience

Background:

• Probability discounting, akin to delay discounting, is linked to pro-health behaviors.
• A Medical Decision Making Questionnaire (MDMQ) previously assessed how multiple sclerosis (MS) patients weigh costs and benefits for treatment adherence.

Purpose of the Study:

• To re-analyze existing data using a novel EP50 measure.
• To develop a model predicting cost-benefit ratios influencing adherence in MS patients.

Main Methods:

• Re-analysis of previously collected data on MS patient adherence.
• Application of a novel EP50 measure within a predictive model framework.
• Quantification of cost-benefit ratios influencing adherence decisions.

Main Results:

• The EP50 framework model successfully predicted cost-benefit ratios for adherence.
• Identified thresholds where non-adherent patient choices mirrored adherent ones, and vice versa.
• Demonstrated the utility of the EP50 measure in understanding adherence variability.

Conclusions:

• The developed analytic tools can inform the creation of new therapeutics.
• These tools may also assist in evaluating and improving treatment adherence strategies for chronic conditions.
• Understanding probability discounting is crucial for optimizing patient adherence.