Unmet Need
According to the Scleroderma Foundation, it is estimated that 300,000 people in the United States are living with scleroderma. Scleroderma is a disease that may affect many organs of the body and is characterized by progressive fibrosis, vascular disease and immunological derangements. Scleroderma is highly variable in clinical phenotype, trajectory, treatment response and mortality. Many different complications can occur, and while there are risk factors for these complications that have been identified in population studies, it has been difficult to translate this information to clinical practice at the patient level to inform targeted screening or therapeutic intervention. Aggregating complex, longitudinal data to understand patients’ health state and risk of major clinical events requires a tremendous time investment on the part of the treating provider. To facilitate improved medical decision making, there is a strong need for a technology that provides longitudinal, multisystem data for scleroderma patients, along with risk assessments for future clinical events.
Technology Overview
Researchers at Johns Hopkins have developed a tool that collects patient-level data in a manner that is easily accessible to clinicians, integrates knowledge of known outcomes from other patients that share key clinical characteristics, and generates personalized risk estimates for multiple complications to improve medical decision making for patients with scleroderma. This tool harnesses information in patients’ baseline risk factors and past trajectories in multiple dimensions to provide precise estimates of a patient’s disease state, trajectory and risks of major clinical events. This innovative technology has the potential for broad applicability to other complex diseases.
Stage of Development
A web application has been developed and internally validated on prospectively collected data.
Publication:
Kim, Ji Soo, et al. "Predicting clinical events using Bayesian multivariate linear mixed models with application to scleroderma." BMC medical research methodology 21 (2021): 1-12.
