Abstract

Background

Many algorithms exist for converting the Health Assessment Questionnaire (HAQ) score to utility in rheumatoid arthritis (RA). Different algorithms convert the same HAQ score to different utility values, and could therefore lead to different cost-effectiveness results.

Objective

To investigate the impact of different mapping algorithms within the same cost-effectiveness model.

Methods

We rebuilt an existing economic model that had previously been used for estimating the cost-effectiveness of second-line biologics in RA. We reviewed the literature to identify algorithms that converted the HAQ score to utility and incorporated them into the model. We compared the cost-effectiveness results using different algorithms, exploring the reasons behind the different results and the potential effect on reimbursement decisions.

Results

We identified 24 different algorithms that estimated utility on the basis of the HAQ score, age, sex, and pain. The incremental cost-effectiveness ratio for rituximab versus disease-modifying antirheumatic drugs varied between £18,407/quality-adjusted life-year and £32,039/quality-adjusted life-year, which we speculate could have changed the recommendations made by the National Institute for Health and Care Excellence.

Conclusions

Using different algorithms to convert the HAQ score to utility affects the cost-effectiveness of second-line biologics for the treatment of RA. Using different algorithms in economic modeling for RA could lead health technology assessment bodies to make different reimbursement decisions.