Simulation model provides range of outcomes for different AAV therapy strategies
Click Here to Manage Email Alerts
A new simulation model can predict a range of clinical outcomes for various therapy strategies in patients with ANCA-associated vasculitis, according to data published in Arthritis Care & Research.
“There have been tremendous advances over the last 20 years in the management of ANCA-associated vasculitis (AAV), such that clinicians and patients now have several options and approaches to choose from when caring for patients with AAV,” Zachary Wallace, MD, MSc, of the division of rheumatology, allergy and immunology at Massachusetts General Hospital, in Boston, told Healio. “However, we do not yet have a great sense of the optimal approaches for management of AAV in day-to-day care.”
“Microsimulation models like AAV-Sim are complementary approaches to cohort studies and clinical trials, which can be used to help us better understand the clinical outcomes of different strategies in AAV subgroups, over longer time horizons, and with regard to outcomes not typically measured in clinical trials,” he added.
Wallace and colleagues created the microsimulation model, called AAV-Sim, to predict clinical outcomes for different treatment strategies in patients with ANCA-associated vasculitis experiencing remission for the first time after induction therapy. At the beginning of the investigation, the model drew from a limited pool of information, including patient demographics and disease-specific characteristics, including kidney interaction and ANCA type. Meanwhile, outcomes on a month-to-month basis included disease relapse, death, end-stage renal disease or serious infection.
The model was intended to predict outcomes in patients who have achieved remission of AAV, including the monthly likelihood of patients developing relapses or infection. According to the researchers, the likelihood of each outcome was based on a fixed or tailored retreatment strategy. The fixed strategy saw patients undergo therapy with rituximab (Rituxan, Genentech) every 6 months, while the tailored strategy used rituximab when ANCA titer or a “repopulation” of CD19+B cells increased. Potential projected outcomes included minor relapses, major relapses, relapse-free survival, severe infection, end-stage renal disease and all-cause mortality.
Wallace and colleagues performed one round of internal, and two rounds of external, validation. The results were compared with published data from the MAINRITSAN2 trial.
According to the researchers, the model demonstrated “similar” accuracy across three rounds of validation. Regarding minor relapses, AAV-Sim projected a 6% rate on fixed therapy vs. 7.3% rate for tailored therapy, compared with MAINRITSAN2, which demonstrated rates of 6.2% vs 8.6%, respectively. For major relapses, AAV-Sim projected a 3.5% rate on fixed therapy vs. 5.5% rate for tailored therapy, compared with 3.7% vs. 7.4% for MAINRITSAN2.
For severe infection, AAV-Sim projected a rate of 19.4% for fixed therapy vs. 11.1% for tailored therapy, compared with MAINRITSAN2, which demonstrated rates of 19.8% and 10.2%, respectively. Finally, regarding relapse-free survival, AAV-Sim projected a rate of 84.8% on fixed therapy, vs. 82.3% for tailored therapy, compared with 86% vs. 84% for MAINRITSAN2.
“In this study, we validated AAV-Sim to demonstrate that it accurately projects clinical outcomes by comparing model-projected outcomes to those observed in clinical trials and a large cohort study,” Wallace said. “Therefore, AAV-Sim can be used to expand our understanding of optimal approaches to AAV management during the remission phase of treatment.
“Because it can help us efficiently and reliably project outcomes with different management strategies, we think that studies using AAV-Sim will help inform clinical guidelines for the management of AAV, and identify key areas of uncertainty and knowledge gaps which should be prioritized in future studies,” he added.
Collapse
Click Here to Manage Email Alerts