Drivers of hospital costs in ANCA-associated vasculitis patients with long-term follow-up-a real-world cost analysis

Abstract

Background: Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a potentially life-threatening, systemic autoimmune disease with a high risk for relapse and treatment-related toxicity, making AAV a high-costs illness. This study aimed to identify clinical insights for clinicians on considering this costs burden.

Methods: We conducted a detailed, retrospective, single-centre, activity-based cost-analysis and identified clinical variables associated with increased costs. We analysed real-world costs incurred by the hospital between January 2018 and December 2019, omitting the outpatient pharmacy expenditures. Our cohort included both incident and prevalent AAV patients with at least 6 months of follow-up since diagnosis, indicating survival beyond initial diagnosis.

Results: For 180 AAV patients with a median follow-up of 1.8 years the average hospital costs incurred amounted to €9887 per patient year, with inpatient care being the primary cost driver (32%). Merely 15% of costs were attributable to patients experiencing relapse (N = 14/180, 8%). More importantly, 71% of costs were attributable to patients experiencing infections (N = 77/180, 43%). Likewise, 60% of costs were attributable to patients with multi-comorbidity (N = 65/180, 36%). Infections and multi-comorbidity were both strongly associated with corticosteroid (CS) use. Regression and sensitivity analyses suggest that a reduction of infections, comorbidities and maintenance treatment with CS will reduce hospital costs.

Conclusion: This real-world cost analysis demonstrates that the burden of infections and comorbidities, both related to CS use, is higher than that of relapses on hospital costs in AAV patients. Thus, this study implicates clinicians considering hospital costs should focus on reducing CS and achieving CS-free remission to prevent infections and comorbidities.

Keywords: ANCA-associated vasculitis; corticosteroids; healthcare costs; pauci-immune glomerulonephritis; systemic autoimmune disease.

GRAPHICAL ABSTRACT

Figure 1:

Activity based costs analysis for AAV. (A) Flow chart for inclusion of clinical procedures. (B) Hospital expenditures across and within expenditure categories. Chem/Hemat, chemistry and hematology; CYC, cyclophosphamide; ICU, intensive care unit; Immuno, immunology; M, months; Maint. treat, maintenance treatment; Microbio, microbiology; Mepo, mepoluzimab; n, number; Patho, pathology; PLEX, plasmapheresis; pts, patients; RTX, rituximab.

Figure 2:

Comparison between proportions of patients and proportions of costs, in clinically defined subgroups based on A) baseline characteristics, B) disease activity and C) complications. Statistical significant disproportion between the proportions of patients (left side each graph) and the proportions of costs (right sight of each graph) was determined using the Pearson χ² test and the P-value is presented above each graph. P-values <.05 are considered significant and are presented in bold. For characteristics with significant disproportion, the correlation coefficient was determined using Spearman's rho (ρ) (D). MDA, major disease activity; MPA, microscopic polyangiitis; Pts, patients.

Figure 3:

Association between treatments and complications (A–D) and their correlation to high hospital costs in a multivariable analysis (E). Comorb, comorbidity; immuno def, immunodeficiency; MDA, major disease activity; sec, secondary; SID, secondary immunodeficiency; yr, years.

Figure 4:

Sensitivity analysis for impact of proportion of patients with a particular clinical characteristic on hospital costs. MDA, major disease activity; pts, patients; sec. immuno def, secondary immunodeficiency.