How do multiple long-term conditions impact on the cost-of-illness in early rheumatoid arthritis?
Bibliographic record
Abstract
OBJECTIVE: Multiple long-term conditions (MLTCs) are prevalent in rheumatoid arthritis (RA) and associated with worse outcomes and greater economic burden. However, little is known about the impact of MLTCs on the cost-of-illness (COI) in early RA, including direct and indirect costs. The objective of this study was to quantify this impact on COI. METHODS: The Scottish Early Rheumatoid Arthritis study is a national cohort of adults with new-onset RA. Direct costs were estimated applying relevant unit costs to health resource utilisation; indirect costs were measured by productivity loss due to health conditions. Two-part models were used, adjusting for age, gender, baseline functional disability and health-related quality of life. The Charlson Comorbidity Index score was calculated using ICD-10 diagnoses. Individuals were defined as 'RA alone', 'RA plus LTC' and 'RA plus MLTCs' according to the number of coexisting LTCs. RESULTS: Data were available for 818 participants. Average annualised direct costs incurred by people with early RA plus MLTCs (£4444; 95% CI £3100 to £6371) were twice as, and almost five times higher than, those with a single LTC (£2184; 95% CI £1596 to £2997) and those without LTC (£919; 95% CI £694 to £1218), respectively. Indirect costs incurred by RA plus MLTCs (£842; 95% CI £377to £1521) were 3.1 times higher than RA alone (£530; 95% CI £273to £854). The relative proportion of direct costs increased with LTC category, ranging from 77.2% to 84.1%. In addition to increased costs with LTCs, costs also increased with age and were higher for men regardless of LTC category. CONCLUSIONS: MLTCs impact on COI early in the course of RA. The presence of LTCs is associated with significant increases in both direct and indirect costs among people with early RA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".