28. Development and Validation of a Simulation Model for Maintenance Treatment in ANCA-Associated Vasculitis
Creators: name: Zachary Wallace1,2,3
name: John Stone1, 3
name: Hyon Choi1,2,3,
name: Emily Hyle1,2,3
Publisher: name: Zenodo
Year: 2022
Subjects: Vasculitis
ANCA
Abstracts
Giant Cell Arthritis
MPA
GPA
EGPA
Takayasu
IgA vasculitis

description: <strong>Background:</strong> ANCA-associated vasculitis (AAV) care has evolved over the last two decades with several approaches to remission maintenance. However, these approaches have trade-offs regarding the risk of flare, infection, end-stage renal disease (ESRD), and other outcomes which impact morbidity, mortality, and costs. We developed a simulation model to project clinical outcomes in individuals with specific disease features, which can be used to inform clinical decision-making and identify uncertainties that strongly affect outcomes. <strong>Methods:</strong> We developed a state-transition, microsimulation model of people with AAV (TreeAge Pro Healthcare 2020). Individuals remain in or transition between health states monthly. At model start, individuals draw for demographic and disease-specific characteristics and then transition between the active AAV or inactive states (i.e., relapse/remission, stratified by major/minor severity) and are at risk for severe infection, ESRD, or death. Transition rates are stratified by demographic and disease-specific characteristics. The distribution of baseline demographics (i.e., age, sex, ANCA type, renal involvement) are from the MAINRITSAN 2 trial, which compared fixed-schedule rituximab (RTX) to a tailored approach based on rising ANCA or B cell titers for remission maintenance. We obtained probabilities of relapse, severe infection, and ESRD from MAINRITSAN 2, and other clinical trials, cohort studies, and national registries. We estimated mortality based on disease-specific features and background age- and sex-adjusted rates derived from US life tables. We then used the AAV model to project outcomes with tailored vs fixed schedule RTX among people in remission at baseline over 28 months, as studied in MAINRITSAN 2. To evaluate external validation, we repeated these steps and compared projected outcomes of fixed treatment in the AAV model to those observed in MAINRITSAN 1 and an observational study of continuous B cell depletion by Pendergraft, et al. We used mean average percent error (MAPE) and coefficient of variation of root mean-square error (CV-RMSE) to assess how the model-projected outcomes compared to those observed in MAINRITSAN 1 and 2, as well as the observational study. <strong>Results: </strong>Over 28 months, the AAV model projected fewer minor and major relapses with fixed vs tailored RTX (7.4% vs 9.7% and 4.5% vs 7.0%). More patients had at least one severe infection in the fixed vs tailored group (20.5% vs 11.4%). ESRD was uncommon in both groups (0.3% vs 0.3%). Relapse free survival at 28 months was higher in fixed vs tailored treatment (85.2% vs 81.6%). Compared to the MAINRITSAN 2 trials results (Table 1), the projected rates of relapse-free survival, relapse, severe infection, ESRD, and death in the AAV model were similar with acceptable MAPE. When evaluating the projected relapse-free survival observed in the AAV model to that observed in MAINRITSAN 2, the CV-RMSE indicated good fit (CV-RMSE 2.2% for fixed treatment and 2.4% for tailored treatment). Similar observations were made when comparing the projected outcomes of the AAV model to those observed in MAINRITSAN 1 and the observational study. Limitations include that we made assumptions regarding differences in mortality rates during active vs inactive disease states. <strong>Conclusions:</strong> We established the face validity and internal and external validation of a novel AAV state-transition model that projects key outcomes, including minor and major relapse, severe infection, ESRD, and death. This model can be adapted to compare other strategies (e.g., azathioprine) and incorporate other health states (e.g., steroid toxicity), quality of life, and costs. <strong>Disclosures:</strong> ZSW is supported by NIH/NIAMS [K23AR073334]. ZSW reports research support from Bristol-Myers Squibb and Principia/Sanofi and consulting fees from Viela Bio and Medpace.