Clinical and Economic Burden of Antineutrophil Cytoplasmic Antibody–associated Vasculitis in the United States
Bibliographic record
Abstract
OBJECTIVE: To describe the prevalence of major relapse and healthcare costs among patients with granulomatosis with polyangiitis (GPA); to find patients with microscopic polyangiitis (MPA) in administrative databases, because no MPA diagnosis code exists; and to describe the clinical and economic burden associated with MPA. METHODS: Adults (≥ 18 yrs) with ≥ 2 diagnoses of GPA [International Classification of Diseases-9-Clinical Modification (ICD-9-CM 446.4)] during 2009-2013 were extracted from the Truven Health MarketScan Commercial and Medicare Supplemental databases. Evidence of major relapse (based on the Birmingham Vasculitis Activity Score) and healthcare costs were collected during 12-month and 24-month followup periods. Adults with ≥ 2 diagnoses of unspecified arteritis (ICD-9-CM 447.6) were found as potential patients with MPA and additional criteria based on clinical input were applied to refine the sample. Major relapse-associated conditions and healthcare costs in the 6 months pre- and post-diagnosis were measured. Costs were inflated to 2013 US$. RESULTS: A total of 2784 patients with GPA were found and 18.7% experienced a major relapse in the 12-month followup period. The patients with a major relapse incurred higher average all-cause (12-month: $88,065 vs $30,682; p < 0.0001) and GPA-related costs (12-month: $61,636 vs $15,748; p < 0.0001) than patients without a relapse. Trends were consistent over the 24-month followup period. There were 612 incident patients with MPA. Following MPA diagnosis, healthcare costs nearly doubled ($30,166 vs $56,642; p < 0.0001). CONCLUSION: In a real-world setting, patients with GPA who experience major relapse have higher economic burden, compared to patients without a relapse. MPA diagnosis was associated with nearly a 2-fold increase in healthcare costs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".