Abstract
Objective:
New opportunities have emerged for early diagnosis with the arrival of new technologies that assess the impact of genomics, proteomics, metabolomics, and cytomics on rheumatoid arthritis (RA) risk. This early health technology assessment study assesses the short-term cost effectiveness of 4 add-on diagnostic tests in early inflammatory arthritis patients at risk of RA.
Methods:
We modeled 4 diagnostic add-on tests to the American College of Rheumatology/European League Against Rheumatism 2010 RA classification criteria, covering the first year after diagnosis, using Rotterdam Early Arthritis Cohort data. Sensitivity, specificity, and costs were assigned to the magnetic resonance imaging of hands and feet (sensitivity 0.90, specificity 0.60, cost €756), interleukin-6 (IL-6) serum level test (sensitivity 0.70, specificity 0.53, cost €50), B cell–related gene expression (sensitivity 0.60, specificity 0.90, cost €150), and gene assay for RA (sensitivity 0.40, specificity 0.85, cost €750), based on literature and expert opinion. Outcomes were evaluated using the unweighted diagnostic net benefit (UDNB) and the incremental cost-effectiveness ratio (ICER) in all patients (n = 552), intermediate-risk patients (n = 263), and seronegative patients (n = 329).
Results:
The highest UDNB was found when using the B cell assay in intermediate-risk patients (43%, ICER €5,314), while the IL-6 test in seronegative patients resulted in the lowest UDNB (−11.4%, ICER €7,650). If a threshold of €20,000 is applied, the B cell assay would be preferred over the other alternatives, with a 78% probability of being cost effective for intermediate-risk patients, 57% for all patients, and 73% for seronegative patients.
Conclusion:
Diagnostic add-on tests favoring specificity over sensitivity with a headroom less than €370 per test are cost effective, with the largest diagnostic benefit occurring in intermediate-risk patients.
New opportunities have emerged for early diagnosis with the arrival of new technologies that assess the impact of genomics, proteomics, metabolomics, and cytomics on rheumatoid arthritis (RA) risk. This early health technology assessment study assesses the short-term cost effectiveness of 4 add-on diagnostic tests in early inflammatory arthritis patients at risk of RA.
Methods:
We modeled 4 diagnostic add-on tests to the American College of Rheumatology/European League Against Rheumatism 2010 RA classification criteria, covering the first year after diagnosis, using Rotterdam Early Arthritis Cohort data. Sensitivity, specificity, and costs were assigned to the magnetic resonance imaging of hands and feet (sensitivity 0.90, specificity 0.60, cost €756), interleukin-6 (IL-6) serum level test (sensitivity 0.70, specificity 0.53, cost €50), B cell–related gene expression (sensitivity 0.60, specificity 0.90, cost €150), and gene assay for RA (sensitivity 0.40, specificity 0.85, cost €750), based on literature and expert opinion. Outcomes were evaluated using the unweighted diagnostic net benefit (UDNB) and the incremental cost-effectiveness ratio (ICER) in all patients (n = 552), intermediate-risk patients (n = 263), and seronegative patients (n = 329).
Results:
The highest UDNB was found when using the B cell assay in intermediate-risk patients (43%, ICER €5,314), while the IL-6 test in seronegative patients resulted in the lowest UDNB (−11.4%, ICER €7,650). If a threshold of €20,000 is applied, the B cell assay would be preferred over the other alternatives, with a 78% probability of being cost effective for intermediate-risk patients, 57% for all patients, and 73% for seronegative patients.
Conclusion:
Diagnostic add-on tests favoring specificity over sensitivity with a headroom less than €370 per test are cost effective, with the largest diagnostic benefit occurring in intermediate-risk patients.
| Original language | English |
|---|---|
| Pages (from-to) | 927-935 |
| Number of pages | 9 |
| Journal | Arthritis Care & Research |
| Volume | 68 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2015 |
Research programs
- EMC NIHES-05-63-02 Quality
- EMC MUSC-01-31-01