This proposal will provide Dr. Runsheng Wang with the vital training needed to achieve her long-term goal of becoming an independent clinical investigator in comparative effectiveness research in axial spondyloarthritis (axSpA), with an overall research program aimed at optimizing clinical management of patients with axSpA and improving axSpA outcomes. Limited evidence is available to guide clinicians and patients to make an individualized treatment plan based on current group level effectiveness and safety data of therapeutic agents. Traditional head-to-head randomized clinical trials are limited by small number of study arms, high cost, and inability to measure individual treatment effects. N-of-1 trials use multi-crossover to address patient-treatment interaction and to measure individual responses to different therapies. Recent advances in biomedical informatics make it possible to transform everyday clinical care to robust well designed n-of-1 trials. An EHR-based computable phenotyping algorithm would improve cohort identification and reduce the complexity of patient recruitment during such trials. Therefore, I hypothesize that N-of-1 trials would identify the most effective therapeutic agents for symptom control in individuals. In the long-term, pragmatic, large scale N-of-1 trials would provide the opportunity to study comparative effectiveness of different drugs in the real world setting. Innovative trial design and bioinformatics tools for cohort identification and systemic data collection will be key elements, among others, in facilitating future comparative effectiveness research in axSpA. The overall goal of this proposal is to test the feasibility of N-of-1 trials of two NSAIDs in axSpA and to develop informatics tools to facilitate the planning and implementation of such trials in a larger scale. The proposed series of N-of-1 trials will provide a framework for comparative effectiveness of other therapeutic agents in patients with axSpA. Coupled with an EHR-based cohort identification tool, this trial design will increase therapeutic precision in individual patients and promote patient-centered research and personalized medicine in axSpA.
This proposal will focus on 1) development and validation of a computable algorithm to identify patients with axial spondyloarthritis (axSpA) using EHR data and 2) implementing a pilot series of N-of-1 trials to test feasibility and inform key design features for future larger scale N-of-1 trials in patients with axSpA. This study will provide pilot data and tools for future comparative effectiveness research of axSpA and increase therapeutic precision for individual patients.
