iPROLEPSIS-PDPID
Research type
Research Study
Full title
PsA digital phenotyping and inflammation drivers study (PDPID)
IRAS ID
332916
Contact name
Jolanda Luime
Contact email
Sponsor organisation
ERASMUS Medical centre
Duration of Study in the UK
2 years, 0 months, 0 days
Research summary
Psoriatic arthritis (PsA) is a chronic immune mediated inflammatory arthritis occurring in patients with psoriasis and is usually serum rheumatoid factor negative [1]. PsA affects around 20% of patients with psoriasis, is equally distributed amongst the sexes, has a tendency to be more prevalent in areas distant from the Equator and appears in most patients before age 65 [2, 3]. The disease manifestation can be heterogeneous between subjects, and the resulting musculoskeletal impairment can interfere with physical function as well as quality of life of patients [4]. Depending on disease activity, patients can experience burden at physical, psychological, social and economic levels [4, 5]. In general, the treatments aim for a disease remission state, which means absence of inflammation and related symptoms.
Currently, disease activity is measured by a combination of clinical measures as well as patients’ self-reported symptoms and functional ability. The use of questionnaires to collect patient reported outcome (PRO’s) is a feasible approach, however, from a long term perspective, survey fatigue is a known limiting factor. On the other hand, the widespread use of smart devices by the general population, such as smartphones or smartwatches allows for Unobtrusive Remote Disease activity monitoring (URD) using behavioural data captured by the sensors embedded within the smartphones/smartwatches. Besides, the daily use of these devices allows for real-time disease activity monitoring, as compared to clinical assessment of disease during routine clinical visits.Currently, there are no studies available that evaluate AI-driven digital biomarkers for remote assessment and monitoring of people with PsA. Two early studies in the field RA using activity trackers show promising results for the detection of flares [6, 7]. One focused on the prediction of flares as defined by the clinician while the other assessed the prediction of self-defined flares by the patients. Therefore, we hypothesize that a high level of disease activity in PsA will lead to changes in physical activity as registered by a patient’s smartphone and smart watch as compared to a low disease activity state, and that the information acquired by digital biomarkers will be comparable to the information received through clinical measures and PROs. Additionally, digital biomarkers are likely to provide information on other disease characteristics such as tiredness and sleep problems
Data will be collected from psoriatic arthritis (PsA) patients to (i) provide accurate, factual and clinically relevant records of the self-contained smartphone- and smartwatch-based, AI-driven digital biomarker system in the detection of psoriatic arthritis (PsA) specific inflammation; (ii) predict accurate, factual and clinically relevant PsA specific inflammation. This will include assessment of disease activity using questionnaires and clinical examinations, DNA from blood, cortisol from hair, and gut microbiome using stool samples.REC name
East Midlands - Leicester Central Research Ethics Committee
REC reference
24/EM/0026
Date of REC Opinion
26 Feb 2024
REC opinion
Further Information Favourable Opinion