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P005 The economic burden of delayed diagnosis in axial spondyloarthritis in the UK

2024· article· en· W4405595916 on OpenAlexaff
Fernando Zanghelini, Georgios Xydopoulos, Stephanie Howard Wilsher, Oyewumi Afolabi, Dale Webb, Joe Eddison, Karl Gaffney, Richard Fordham

Bibliographic record

VenueLara D. Veeken · 2024
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsArthritis Society
Fundersnot available
KeywordsAxial spondyloarthritisMedicineIntensive care medicineSurgeryAnkylosing spondylitisSacroiliitis

Abstract

fetched live from OpenAlex

Abstract Introduction Timely diagnosis of axial spondyloarthritis (axSpA) remains challenging and delays result in harmful consequences. Few studies have evaluated the cost of delayed axSpA diagnosis. This study aims to develop an economic analysis to determine the annual cost of delaying the axSpA diagnosis, adopting both NHS (UK) and societal perspectives. Methods We developed a Markov economic model to estimate the costs of delayed axSpA diagnosis in the UK. The cohort of patients assessed comprised a mixed population (cohort size: 1,000 patients, 64% males), mean age of symptom onset 26 years. The model captured the resources used and costs related to diagnosing and managing axSpA symptoms until the disease was diagnosed. Results Results are summarised in Table 1. Our economic analysis results show the cost of delayed axSpA diagnosis is substantial and falls mainly on the individuals concerned in the form of productivity losses, out of pocket medical expenses, non-prescribed drug expenses, and travel costs to healthcare services. These costs are higher in younger patients but remain substantial in older groups. With a symptom onset at the age of 26 and an average time to diagnosis of 8.5 years, we estimate that the cumulative cost of delayed diagnosis per person living with axial SpA is £193,512 (CI95%: £108,769 - £306,789). The total annual cost that accrues to delay before the diagnosis of axSpA in the UK was £3.1 billion and £12.4 billion, based on a prevalence of 0.3% and 1.2%, respectively (Table 1). Our results corroborate findings from other studies, showing that patients with a late diagnosis of axSpA had higher costs, reduced incapacity for work, and worse clinical outcomes1,2. P005 Table 1.Nationwide total cost of delaying the axSpA diagnosis based on axSpA prevalence.Prevalence of 0.3%Prevalence of 1.2%ResultsTotal cost - ModelledTotal cost – NASS pop*Total cost – UK adult pop**Total cost – UK adult pop**DSA£23,104.17£4,236,794,775£3,115,805,703£12,463,222,813PSA£24,025.06£4,431,645,007£3,259,101,637£13,036,406,54995% LCI£14,568.52£2,703,455,437£1,988,163,769£7,952,655,07995% UCI£36,950.02£6,595,614,347£4,850,518,822£19,402,075,288Note: 83.4% remaining undiagnosed per year*NASS estimate population: 220,000 patients.**UK adult population (2022): 53,930,490.DSA: deterministic sensitivity analysis, LCI: low confidence interval, pop: population, PSA: probabilistic sensitivity analysis: UCI: upper confidence interval. Conclusion To our knowledge, this is the first UK-specific study and the first internationally to develop an economic analysis to determine the annual cost of delay in diagnosing axSpA, adopting both NHS and societal perspectives. Earlier diagnosis is essential in order to reduce healthcare needs, resource utilisation, and enhance the quality of life for people living with axSpA References 1. Kobelt G, et al. Value Health. 2008 May;11(3):408–15. 2. Grigg SE, et al. ACRARHP Sci Meet 2011. 2011;63(abstract 1308).

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.267
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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