Background and Significance: Juvenile idiopathic arthritis (JIA) is a major cause of childhood disability. The most common, yet among the most devastating, is the polyarticular form of JIA (pJIA). Treatment decisions made for pJIA and other chronically ill patients are adaptive treatment strategies (ATSs), as they are made adaptive to the course of disease, the disease progression, and the patients’ responses to earlier treatments. ATSs are ubiquitous in clinical practices, but the current methods are seriously limited in evaluating their clinical effectiveness. Motivated to answer a question asked by parents of JIA patient—“Given my child’s responses to the previous treatments, what is the best next treatment option for my child?”—and a question asked by a treating clinician—“What treatment should we recommend to patients who fail to respond to the first (or second) line of treatment?”—our study will develop, refine, and disseminate Bayesian causal inference methods specifically designed to evaluate and inform patient-centered adaptive treatment strategies (PCATSs).
This study has an immediate impact to JIA stakeholders and a broad impact to many chronically ill patients. Successful completion of this project will immediately offer rigorous analytic methods, enable shared-decision-making tools in the near future, and ultimately enable a rapid learning system that will facilitate optimal PCATSs at the point of care. Therefore, it will significantly move PCORI closer to its mission of helping “people make better-informed healthcare decisions and improve healthcare delivery and outcomes.”
Study Aims: Our long-term objective is to improve the health outcomes and experiences in patients with chronic illness by enabling evidence-based shared decision-making tools at the point of care through rigorous analytic method development for PCATSs. The specific aims of the study are: (1) to develop, refine, and disseminate Bayesian causal inference methods evaluating clinical effectiveness and for informing better PCATSs; and (2) to evaluate the clinical effectiveness of the newly recommended ATSs for pJIA patients via conducting and analyzing a large new patient registry study in collaboration with Pediatric Rheumatology Care and Outcomes Improvement Network, a participant in a PCORI-funded PCORnet.
Study Description: We propose to develop Bayesian double-robust causal inference methods that are accurate, vigorous, and efficient for evaluating the clinical effectiveness of ATSs, utilizing electronic health records and registry studies, through working closely with our stakeholder advisory panel. The proposed “PCATS” R package will allow easy application of our methods without requiring R programming skills. We will assess clinical effectiveness of the expert-recommended ATSs for the pJIA patient population using a multicenter new-patient registry study design. The study outcomes are clinical responses and the health-related quality of life after a year of treatment.