A five-year model to assess the early cost-effectiveness of new diagnostic tests in the early diagnosis of rheumatoid arthritis

Background: There is a lack of information about the sensitivity, specificity and costs new diagnostic tests should have to improve early diagnosis of rheumatoid arthritis (RA). Our objective was to explore the early cost-effectiveness of various new diagnostic test strategies in the workup of patients with inflammatory arthritis (IA) at risk of having RA. Methods: A decision tree followed by a patient-level state transition model, using data from published literature, cohorts and trials, was used to evaluate diagnostic test strategies. Alternative tests were assessed as add-on to or replacement of the ACR/EULAR 2010 RA classification criteria for all patients and for intermediate-risk patients. Tests included B-cell gene expression (sensitivity 0.60, specificity 0.90, costs €150), MRI (sensitivity 0.90, specificity 0.60, costs €756), IL-6 serum level (sensitivity 0.70, specificity 0.53, costs €50) and genetic assay (sensitivity 0.40, specificity 0.85, costs €750). Patients with IA at risk of RA were followed for 5 years using a societal perspective. Guideline treatment was assumed using tight controlled treatment based on DAS28; if patients had a DAS28 >3.2 at 12 months or later patients could be eligible for starting biological drugs. The outcome was expressed in incremental cost-effectiveness ratios (€2014 per quality-adjusted life year (QALY) gained) and headroom. Results: The B-cell test was the least expensive strategy when used as an add-on and as replacement in intermediate-risk patients, making it the dominant strategy, as it has better health outcomes and lower costs. As add-on for all patients, the B-cell test was also the most cost-effective test strategy. When using a willingness-to-pay threshold of €20,000 per QALY gained, the IL-6 and MRI strategies were not cost-effective, except as replacement. A genetic assay was not cost-effective in any strategy. Probabilistic sensitivity analysis revealed that the B-cell test was consistently superior in all strategies. When performing univariate sensitivity analysis for intermediate-risk patients, specificity and DAS28 in the B-cell add-on strategy, and DAS28 and sensitivity in the MRI add-on strategy had the largest impact on the cost-effectiveness. Conclusions: This early cost-effectiveness analysis indicated that new tests to diagnose RA are most likely to be cost-effective when the tests are used as an add-on in intermediate-risk patients, and have high specificity, and the test costs should not be higher than €200–€300.