Objective
To demonstrate the value of diagnosing axSpA, by comparing health and costs associated with available diagnostic algorithms and perfect diagnosis.
Methods
Using data from SPACE and other cohorts, a model was developed to estimate health (quality-adjusted life-years, QALYs) and costs (healthcare consumption and work productivity losses) of different diagnostic algorithms for axSpA amongst patients with low back pain referred to a rheumatologist, over a 60-year horizon. The model combined a decision-tree (diagnosis) with a state-transition model (treatment). The three algorithms (Berlin [BER, highest specificity], Modification 1 [M1; less strict inflammatory back pain (IBP) criterion] and Modification 2 [M2; IBP not mandatory as entry criterion, highest sensitivity]) were compared. Changes in sensitivity/specificity were explored and the value of perfect diagnosis was investigated.
Results
For each correctly...
Show moreObjective
To demonstrate the value of diagnosing axSpA, by comparing health and costs associated with available diagnostic algorithms and perfect diagnosis.
Methods
Using data from SPACE and other cohorts, a model was developed to estimate health (quality-adjusted life-years, QALYs) and costs (healthcare consumption and work productivity losses) of different diagnostic algorithms for axSpA amongst patients with low back pain referred to a rheumatologist, over a 60-year horizon. The model combined a decision-tree (diagnosis) with a state-transition model (treatment). The three algorithms (Berlin [BER, highest specificity], Modification 1 [M1; less strict inflammatory back pain (IBP) criterion] and Modification 2 [M2; IBP not mandatory as entry criterion, highest sensitivity]) were compared. Changes in sensitivity/specificity were explored and the value of perfect diagnosis was investigated.
Results
For each correctly diagnosed axSpA patient, up to 4.7 QALYs and €60,000 could be gained/saved, considering a societal perspective. Algorithm M2 resulted in more health and lower costs per patient (24.23 QALYs; €157,469), compared to BER (23.96 QALYs; €159,423) and M1 (24.15 QALYs; €158,417). Hypothetical improvements in M2 sensitivity resulted in slightly more value compared to improvements in specificity. Perfect diagnosis can cost €7,500 per patient and still provide enough value.
Conclusion
Correct diagnosis of axSpA results in substantial health and cost benefits for patients and society. Not requiring IBP as mandatory for diagnosis of axSpA (algorithm M2) provides more value and would be preferable. A considerably more expensive diagnostic algorithm with better accuracy than M2 would still be considered good value for money.
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