Dactylitis, Dermatologic Disease, Joint Pain, Plaque Psoriasis, Psoriasis, Psoriatic Arthritis, Psoriatic Conditions, Psoriatic Nail, Rheumatologic Disease
Conditions
Keywords
Psoriasis, Psoriatic Arthritis, Psoriatic Disease, Health app research, mHealth research, Mobile health research
Brief summary
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.
Detailed description
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.
Interventions
BEHAVIORALParticipant self-assessment surveys
At enrollment, participants are asked to complete a baseline health history, family history, and a participant-reported symptom inventory.
BEHAVIORALPsoriasis Draw
Participants are asked to draw the location and size of psoriasis they currently experience. Participants are provided a body template onto which they can draw on their screen. Investigators estimate the percentage of body area affected.
BEHAVIORALPsoriasis Area Photo
Participants are asked to take a picture of a representative psoriasis plaque and indicate the location of the plaque. They are asked to take a picture of the same area over time. The investigators are developing computer vision algorithms to assess the plaque.
BEHAVIORALFinger and Toe Photos
Participants are asked to take pictures of the back of each hand and the top of each foot. These photos can be used to assess finger and toe swelling as well as psoriatic nail involvement. The investigators are developing computer vision algorithms to assess psoriatic nail involvement and digit swelling.
BEHAVIORALDigital Jar Open
Participants are asked to internally and externally rotate the phone as it rests on a flat surface. Participants perform each direction (internal and external) and each arm (left and right) in turn. Gyroscope sensors measure the degree of rotation.
BEHAVIORAL30 Second Walk
Participants are asked to walk in a straight line for 30 seconds. Gait is measured by gyroscope and accelerometer sensors. The investigators examine step-dependent and sequence-dependent features from these sensors. The investigators apply feature selection and classifier algorithms to analyze these data.
OTHERPsorcast mobile application
Participants complete all described behavioral interventions via a dedicated iPhone app, Psorcast.
Sponsors
Sage Bionetworks
Brigham and Women's Hospital
NYU Langone Health
University of Pennsylvania
Harvard Medical School (HMS and HSDM)
New York University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Adult age 18 and older who consent to participate in the study * Own a compatible iPhone or iPod Touch device running iOS 12.2 or above * Be able to read and understand an official language of the country of participation
Exclusion criteria
* Age 17 years or younger * Not a resident of the a country where the app is approved for use * Not have a personal (i.e., not shared) iPhone (4s or newer running iOS 8.0 or later) * Not be able to read and understand an official language of the country of participation
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Results of participant self-assessment surveys | Through study completion, an average of 2 years | Results of participant self-assessment surveys will be analyzed using descriptive statistics. These results may also be compared with other intervention results. |
| Body surface area and location from the Psoriasis Draw assessment | Through study completion, an average of 2 years | The investigators will quantify body surface area and psoriasis area hotspots across the cohort. These results may also be compared with other intervention results. |
| Computer vision features from Psoriasis Area Photo assessment | Through study completion, an average of 2 years | The investigators apply visual processing and classifier algorithms to analyze the images from the Psoriasis Area Photo assessments. These results may also be compared with other intervention results. |
| Computer vision features from Finger/Toe Photos | Through study completion, an average of 2 years | The investigators apply visual processing and classifier algorithms to segment nails and joints from hand and foot photos. These results may also be compared with other intervention results. |
| Gyroscope and accelerometer sensor measurements from Digital Jar Open assessment | Through study completion, an average of 2 years | The investigators examine rotational features from gyroscope and accelerometer sensors. The investigators apply feature selection and classifier algorithms to analyze these data. These results may also be compared with other intervention results. |
| Gyroscope and accelerometer sensor measurements from 30-sec Walk assessment | Through study completion, an average of 2 years | The investigators examine step-dependent and sequence-dependent features from gyroscope and accelerometer sensors. The investigators apply feature selection and classifier algorithms to analyze these data. These results may also be compared with other intervention results. |
| Quantification and distribution of self-reported painful joints | Through study completion, an average of 2 years | The investigators will quantify the self-reported painful joints and, in particular, compare to measurements from the 30-sec Walk and Digital Jar Open to identify correlations. These results may also be compared with other intervention results. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| App usage data for assessment of participant engagement | Through study completion, an average of 2 years | App usage data is used to gauge participant engagement throughout the study period. These results may also be compared with other intervention results. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORSolveig Sieberts, Ph.D
Sage Bionetworks
PRINCIPAL_INVESTIGATORJose Scher, MD
NYU Langone Medical Center
PRINCIPAL_INVESTIGATORJoseph Merola, MD, MMSc
Brigham and Women's Hospital & Harvard Medical School
Outcome results
None listed