Healthcare Resource Use and Direct Costs in Patients with Ankylosing Spondylitis and Psoriatic Arthritis in a Large US Cohort
Bibliographic record
Abstract
OBJECTIVE: Direct costs of ankylosing spondylitis (AS) and psoriatic arthritis (PsA) have not been well characterized in the United States. This study assessed healthcare resource use and direct cost of AS and PsA, and identified predictors of all-cause medical and pharmacy costs. METHODS: Adults aged ≥ 18 with a diagnosis of AS and PsA were identified in the MarketScan databases between October 1, 2011, and September 30, 2012. Patients were continuously enrolled with medical and pharmacy benefits for 12 months before and after the index date (first diagnosis). Baseline demographics and comorbidities were identified. Direct costs included hospitalizations, emergency room and office visits, and pharmacy costs. Multivariable regression was used to determine whether baseline covariates were associated with direct costs. RESULTS: Patients with AS were younger and mostly men compared with patients with PsA. Hypertension and hyperlipidemia were the most common comorbidities in both cohorts. A higher percentage of patients with PsA used biologics and nonbiologic disease-modifying drugs (61.1% and 52.4%, respectively) compared with patients with AS (52.5% and 21.8%, respectively). Office visits were the most commonly used resource by patients with AS and PsA (∼11 visits). Annual direct medical costs [all US dollars, mean (SD)] for patients with AS and PsA were $6514 ($32,982) and $5108 ($22,258), respectively. Prescription drug costs were higher for patients with PsA [$14,174 ($15,821)] compared with patients with AS [$11,214 ($14,249)]. Multivariable regression analysis showed higher all-cause direct costs were associated with biologic use, age, and increased comorbidities in patients with AS or PsA (all p < 0.05). CONCLUSION: Biologic use, age, and comorbidities were major determinants of all-cause direct costs in patients with AS and PsA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".