Psoriatic disease exhibits a spectrum of symptoms and can transition from psoriasis (PsO), largely affecting the skin, to psoriatic arthritis (PsA) involving widespread musculoskeletal inflammation. Early detection of the PsO-to-PsA transition and rapid administration of effective treatment is essential, as a delay in diagnosing PsA by as little as 6 months can lead to irreversible joint damage. This ticking clock paradigm drives the need for frequent monitoring and effective therapeutic intervention as early as possible to attenuate or possibly prevent disease progression. Using a suite of smartphone-based measurements in an app called Psorcast (psoriasis forecasts), we aim to aggregate weekly, symptom measurements from participants in a remote, longitudinal observational study to map the trajectories of treatment response and disease progression. In this study, we will explore measurements of psoriatic disease activity at least an order of magnitude more frequently (weekly vs. quarterly) than standard clinical practice or clinical trial designs. This study is not meant to provide a medical diagnosis, treatment, or medical advice. It is meant to provide a scalable, inexpensive, non-invasive and frequent measure and tracking of psoriasis and psoriatic arthritis for research purposes.
The purpose of this study is to understand variation in the symptoms of psoriasis and psoriatic arthritis using simple, scalable smartphone-based measurements. This study uses an iPhone app to record these symptoms through questionnaires and sensors.