The added value of predictive biomarkers in treat-to-target strategies for rheumatoid arthritis patients: a conceptual modelling study
Main finding · Time in LDA or remissionResult — go to the resultDifference 2.9 monthsAuthors' conclusion
The use of a biomarker for prediction of response to b/tsDMARD treatment in RA can be of added value to current treat-to-target clinical care. However, gains in efficacy are modest and cost gains are depending on a combination of early proactive tapering and high medication costs.
Study context
- Population
- RA patients starting biologic therapy (modelled)
- Comparison
- Biomarker-steered strategy vs usual care T2T strategy
- Outcome
- Time spent in remission or low disease activity (LDA), and costs
- Follow-up
- 48 months
Methodological detailsMarkov model, scenario analyses
- Markov model
- Scenario analyses
Main finding
Time in LDA or remission
Difference
2.9 months
As reported in the abstract
Further findings
Total costs · 48 months · base model
- Total costs — Treatment costs share of total costs, both scenarios
- 91%
Scenario analyses (cost-effectiveness drivers)
- Cost-effectiveness not so much driven by costs or test characteristics of the biomarker (scenarios 1/2), but by level of early proactive tapering and drug costs (scenarios 3/4)
Original publication
The added value of predictive biomarkers in treat-to-target strategies for rheumatoid arthritis patients: a conceptual modelling study. Rheumatology (Oxford). Published 20 December 2022. doi:10.
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