Longitudinal tracking of skin dynamic stiffness to quantify evolution of sclerosis in chronic graft-versus-host disease

Expanding Personalized, Data-Driven Dermatology: Leveraging Digital Health Technology and Machine Learning to Improve Patient Outcomes

“…Note that the data in the framework are comprised of not only traditionally gathered clinical data but also data generated by patients (e.g., tracking their symptoms and self-reported outcomes as well as physiologic measurements ranging from home blood pressure and glucose levels to step count and sleep duration/quality) and through digital technology such as ones enabling skin measurements of stiffness and wound healing. An example of data that can be collected include measurements of skin stiffness as shown in the plot, where dynamic stiffness measurements are shown over time where each color corresponds to a different patient's trajectory (gray: clinically stable, gold: disease progression, blue: clinical improvement, green: no skin involvement; modified from Baker et al 2021b). These data can be collected longitudinally to enable tools in three main categories: 1) risk prediction & early detection, 2) individualized therapy and longitudinal monitoring of treatment response, and 3) patient engagement with digital tools allowing for individualized patient education and selfmonitoring.…”

“…For example, including physiologic measurements such as home blood pressure and glucose levels to step count and sleep duration/quality can help inform skin disease biology and management as well as underscore the relationship of skin diseases with other systemic conditions. (BSA: Body Surface Area); Images: MyotonPRO Device (Baker et al 2021b); image capturing erythematous lesion severity of GVHD (Tkaczyk et al 2018)…”

“…Furthermore, skin stiffness is a clinical manifestation that has traditionally been difficult J o u r n a l P r e -p r o o f to monitor accurately. However, with the introduction of the MyotonPRO Device, skin stiffness can now be quantified and tracked dynamically (Baker et al 2021b). With skin biomechanical parameters measured using the MyotonPRO, recent investigation using logistic regression and machine learning models found that the frequency and relaxation time offered the highest diagnostic yield for distinguishing sclerotic cGVHD patients from post-hematopoietic cell transplantation controls.…”

National Institutes of Health Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-versus-Host Disease: IIa. The 2020 Clinical Implementation and Early Diagnosis Working Group Report

“…These signs and symptoms should be assessed serially and prospectively to determine sensitivity and specificity for future development of sclerotic disease. Diagnostic assessment: Early detection of subclinical sclerotic chronic GVHD remains an urgent need, and technologies such as magnetic resonance imaging (MRI) [ 77 ], variants of ultrasound [ 78 , 79 ], and the Myoton device (Myoton AS, Tallinn, Estonia) [ 80 , 81 ] are being studied. Patient engagement: Self-assessment at regular intervals between clinic visits using the P-ROM scale could be performed and recorded in a logbook or app.…”

“…Diagnostic assessment: Early detection of subclinical sclerotic chronic GVHD remains an urgent need, and technologies such as magnetic resonance imaging (MRI) [ 77 ], variants of ultrasound [ 78 , 79 ], and the Myoton device (Myoton AS, Tallinn, Estonia) [ 80 , 81 ] are being studied.…”