scholarly journals Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Using Biosensor and Patient-Reported Outcome Data: Protocol for a Real-World Study

10.2196/14665 ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. e14665 ◽  
Author(s):  
William Benjamin Nowell ◽  
Jeffrey R Curtis ◽  
Sandra K Nolot ◽  
David Curtis ◽  
Shilpa Venkatachalam ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Digital Technology ◽  
Subjective Experience ◽  
Patient Reported Outcome ◽  
Mobile App ◽  
Smartphone App ◽  
Activity Data ◽  
Physician Visits ◽  
Study Results ◽  
Patient Reported

Background Rheumatoid arthritis (RA) is a condition with symptoms that vary over time. The typical 3- to 6-month interval between physician visits may lead to patients failing to recall or underreporting symptoms experienced during the interim. Wearable digital technology enables the regular passive collection of patients’ biometric and activity data. If it is shown to be strongly related to data captured by patient-reported outcome (PRO) measures, information collected passively from wearable digital technology could serve as an objective proxy or be complementary to patients’ subjective experience of RA symptoms. Objective The goal of this study is to characterize the extent to which digital measures collected from a consumer-grade smartwatch agree with measures of RA disease activity and other PROs collected via a smartphone app. Methods This observational study will last 6 months for each participant. We aim to recruit 250 members of the ArthritisPower registry with an RA diagnosis who will receive a smartwatch to wear for the period of the study. From the ArthritisPower mobile app on their own smartphone device, participants will be prompted to answer daily and weekly electronic PRO (ePRO) measures for the first 3 months. Results The study was launched in December 2018 and will require up to 18 months to complete. Study results are expected to be published by the end of 2021. Conclusions The completion of this study will provide important data regarding the following: (1) the relationship between passively collected digital measures related to activity, heart rate, and sleep collected from a smartwatch with ePROs related to pain, fatigue, physical function, and RA flare entered via smartphone app; (2) determine predictors of adherence with smartwatch and smartphone app technology; and (3) assess the effect of study-specific reminders on adherence with the smartwatch. International Registered Report Identifier (IRRID) DERR1-10.2196/14665

scholarly journals Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Using Biosensor and Patient-Reported Outcome Data: Protocol for a Real-World Study (Preprint)

2019 ◽  
Author(s):  
William Benjamin Nowell ◽  
Jeffrey R Curtis ◽  
Sandra K Nolot ◽  
David Curtis ◽  
Shilpa Venkatachalam ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Digital Technology ◽  
Subjective Experience ◽  
Patient Reported Outcome ◽  
Mobile App ◽  
Smartphone App ◽  
Activity Data ◽  
Physician Visits ◽  
Study Results ◽  
Patient Reported

BACKGROUND Rheumatoid arthritis (RA) is a condition with symptoms that vary over time. The typical 3- to 6-month interval between physician visits may lead to patients failing to recall or underreporting symptoms experienced during the interim. Wearable digital technology enables the regular passive collection of patients’ biometric and activity data. If it is shown to be strongly related to data captured by patient-reported outcome (PRO) measures, information collected passively from wearable digital technology could serve as an objective proxy or be complementary to patients’ subjective experience of RA symptoms. OBJECTIVE The goal of this study is to characterize the extent to which digital measures collected from a consumer-grade smartwatch agree with measures of RA disease activity and other PROs collected via a smartphone app. METHODS This observational study will last 6 months for each participant. We aim to recruit 250 members of the ArthritisPower registry with an RA diagnosis who will receive a smartwatch to wear for the period of the study. From the ArthritisPower mobile app on their own smartphone device, participants will be prompted to answer daily and weekly electronic PRO (ePRO) measures for the first 3 months. RESULTS The study was launched in December 2018 and will require up to 18 months to complete. Study results are expected to be published by the end of 2021. CONCLUSIONS The completion of this study will provide important data regarding the following: (1) the relationship between passively collected digital measures related to activity, heart rate, and sleep collected from a smartwatch with ePROs related to pain, fatigue, physical function, and RA flare entered via smartphone app; (2) determine predictors of adherence with smartwatch and smartphone app technology; and (3) assess the effect of study-specific reminders on adherence with the smartwatch. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/14665

THU0564 PARTICIPANT ENGAGEMENT IN AN ARTHRITISPOWER REAL-WORLD STUDY TO CAPTURE SMARTWATCH AND PATIENT-REPORTED OUTCOME DATA AMONG RHEUMATOID ARTHRITIS PATIENTS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 523-524
Author(s):  
W. B. Nowell ◽  
J. Curtis ◽  
F. Xie ◽  
H. Zhao ◽  
D. Curtis ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Real World ◽  
Rating Scales ◽  
Patient Reported Outcome ◽  
Time Of Day ◽  
Main Study ◽  
Time Zone ◽  
Activity Data ◽  
Patient Reported ◽  
Passive Data

Background:Clear characterization of how different types of patient-generated data reflect patient experience is needed to guide integration of electronic patient-reported outcome (ePRO) measures and biometrics in generating real-word evidence (RWE) related to rheumatoid arthritis (RA).Objectives:To characterize the level of participant (pt) engagement/adherence and data completeness in an ongoing study of 250 RA pts enrolled in the Digital Tracking of Arthritis Longitudinally (DIGITAL) study1of the ArthritisPower real-world registry.Methods:ArthritisPower pts with RA were invited to join a digital RWE study with 14-day lead-in and 12-week main study period. In the lead-in, pts were required to electronically complete: a) two daily single-item Pain and Fatigue numeric rating scales and b) longer weekly sets of ePROs. Successful completers of the lead-in were mailed a smartwatch (Fitbit Versa) and study materials. The smartwatch collected activity, heart rate, and sleep duration/quality biosensor data; a study-specific customization of the ArthritisPower mobile application collected ePROs. The main study period included automated and manual reminders/prompts about completing ePROs, wearing the smartwatch and regularly syncing it. Study coordinators monitored pt data and contacted pts via email, text and/or phone to resolve adherence issues during the conduct of the study based on pre-determined rules triggering pt contact. Rules were based chiefly on consecutive spans of missing data. Pts were considered adherent in giving complete data for each week if providing (1) daily ePROs for ≥5 of 7 days/week, (2) weekly ePROs and (3) ≥80% of synced activity data for ≥5 of 7 days/week. Composite adherence for the first month of the main study period required meeting >70% weekly adherence parameters during the first 30 days, ie completing daily ePROs for ≥5 of 7 days/week, weekly ePROs ≥3 of 4 weeks and ≥80% of synced activity data for ≥5 of 7 days/week.Results:As of December 2019, 170 ArthritisPower members enrolled and completed at least 30 days of the main study period; 92.9% female with mean (SD) age 52.5 (10.7) and 10.5 (10.4) years since diagnosis. The overall conversion rate from initial interest to successful completion of the lead-in period was 49.0%. Pts who advanced to the main study were significantly more likely than those who did not to be currently employed (52.9% vs. 41.8%, p=0.038) and be on biologic DMARD monotherapy (64.7% vs. 47.5%, p=0.001). Overall, daily ePRO data had the lowest adherence with 70.0% of pts providing >70% of the requested data consistently across the first 30 days of the main study period (Figure 1). Composite adherence was met by 66.5% of pts. The most common time of day to provide ePRO data was morning, in the hours around scheduled app and email notifications at 10 a.m. in pt’s local time zone. Activity data had the highest adherence and persistence, with 92.9% of pts providing 80% or more of activity data for each 24-hour period in the first 30 days (Figures 1 & 2). Observed weekly adherence did not decline over time. Of 5100 possible person days in the study at day 30, we observed 643 days (91.0% of actual to maximum possible total patient days) where activity data was provided for at least 80% of the 24-hour period.Conclusion:RWE studies involving passive data collection in RA require pt-centric implementation and design to minimize pt burden, promote longitudinal engagement and maximize adherence. Passive data capture via activity trackers such as smartwatches, along with regular contact such as automated reminders, may facilitate greater pt adherence in providing longitudinal data for clinical trials.References:[1]Nowell WB, et al. JMIR Res Protoc. 2019;8(9):e14665.Disclosure of Interests:W. Benjamin Nowell: None declared, Jeffrey Curtis Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Corrona, Janssen, Lilly, Myriad, Pfizer, Regeneron, Roche, UCB, Fenglong Xie: None declared, Hong Zhao: None declared, David Curtis: None declared, Kelly Gavigan: None declared, Shilpa Venkatachalam: None declared, Laura Stradford: None declared, Jessica Boles: None declared, Justin Owensby: None declared, Cassie Clinton: None declared, Ilya Lipkovich Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Amy Calvin Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Virginia S. Haynes Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company

scholarly journals AB0051 THE EFFECTS OF NON-INVASIVE VAGUS NERVE STIMULATION ON IMMUNOLOGICAL RESPONSES AND PATIENT REPORTED OUTCOME MEASURES OF FATIGUE IN PATIENTS WITH CHRONIC FATIGUE SYNDROME, FIBROMYALGIA, AND RHEUMATOID ARTHRITIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1057.3-1058
Author(s):  
E. Traianos ◽  
B. Dibnah ◽  
D. Lendrem ◽  
Y. Clark ◽  
V. Macrae ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Daytime Sleepiness ◽  
Vagus Nerve Stimulation ◽  
Chronic Fatigue ◽  
Patient Reported Outcome Measures ◽  
Patient Reported Outcome ◽  
Physical Fatigue ◽  
Fatigue Syndrome ◽  
Tnf Α ◽  
Patient Reported

Background:Fatigue is reported as a common symptom among autoimmune and other chronic diseases such as fibromyalgia (FM), a long-term condition with uncertain pathophysiology. Previous studies from our group suggest that non-invasive vagus nerve stimulation (nVNS) may contribute to the improvement of patient reported outcome measures (PROMs) of fatigue in patients with primary Sjögren’s Syndrome (1).Objectives:This follow-up study uses the gammaCore device (electroCore) to assess the effect of nVNS on PROMs of fatigue and immune responses in chronic fatigue syndrome (CFS), FM and rheumatoid arthritis (RA).Methods:The study included thirteen CFS, fourteen FM and fifteen RA patients who used the gammaCore nVNS device twice daily over a 26-day period. Pre- and post- nVNS bloods were drawn at baseline and final visits. Whole blood samples were stimulated with 2 ng/mL lipopolysaccharide (LPS) and the IL-6 and TNF-α cytokine concentrations were quantified at 24 hours. In addition, the epidermal growth factor (EGF), IFN-γ, IL-6, IP-10, MIP-1α, and TNF-α levels were measured in ‘pre-nVNS’ serum and flow cytometric profiles of whole blood immune cells were analysed. The patient reported outcome measures (PROMs) recorded at each visit were the Visual Analogue Scale (VAS) (0-100 cm) of abnormal fatigue, Hospital Anxiety and Depression (HAD) Scale, Orthostatic Grading Scale, Epworth Sleepiness Scale (daytime sleepiness), and Profile of fatigue (PRO-F) for Physical and Mental fatigue. Paired t-tests were performed to assess for changes in PROMs, cytokine levels, and cell subset distribution and associations of cytokine response with PROMs were investigated by correlation analyses.Results:Eleven CFS, twelve FM and fourteen RA patients completed the study. There was a significant reduction in daytime sleepiness in CFS (p =0.0321) and FM (p =0.0294) patients between the final and baseline visits and a significant reduction in HAD depression (p =0.0413) in FM (Fig.1). Improvement in VAS for abnormal fatigue, HAD-Anxiety, HAD-Depression, PRO-F Physical and Mental fatigue was observed in all three groups over the study period with a reduction in VAS fatigue in 64% of CFS, 67% of FM and 62% of RA patients. There were no significant changes in the immune cell subsets or in cytokine response. Finally, higher baseline pre-nVNS supernatant IL-6 levels were predictive of an improvement in VAS fatigue (p =0.0006), Daytime Sleepiness (p =0.0466) and PRO-F Physical fatigue (p =0.0196) in RA, while higher baseline TNF-α levels were predictive of an improvement in VAS fatigue (p =0.0003), Daytime Sleepiness (p =0.0380), Orthostatic (p =0.0281) and PRO-F Physical fatigue (p =0.0007) in FM.Conclusion:Our findings suggest that nVNS may contribute to the improvement of PROMs of fatigue in CFS, FM and RA. NVNS led to significant reductions in daytime sleepiness in CFS and FM, and depression in FM. Further studies and a larger sample size are needed to investigate the potential effects of nVNS on diseases characterised by persistent fatigue.References:[1]Tarn J, Legg S, Mitchell S, Simon B, Ng WF. The Effects of Noninvasive Vagus Nerve Stimulation on Fatigue and Immune Responses in Patients With Primary Sjögren’s Syndrome. Neuromodulation Technol Neural Interface. 2018;22(5):580–5.Figure 1.VAS for abnormal fatigue and PROMs recorded at baseline and final visits in patients with chronic fatigue syndrome (CFS), fibromyalgia (FM) and rheumatoid arthritis (RA). Boxplots show the median, upper, and lower quartiles for PROMs at visit 1 and visit 3 in each disease group. Paired-t tests revealed a significant reduction in daytime sleepiness in CFS and FM (B), and a significant reduction in HAD depression in FM (E). Improvement trends were observed in VAS for abnormal fatigue, HAD-Anxiety, HAD-Depression, PRO-F Physical fatigue and PRO-F Mental fatigue in all three groups over the 26-day study period.Acknowledgements:This study received infrastructural support from the National Institute of Health Research (NIHR) Newcastle Biomedical Research Centre at Newcastle Hospitals Foundation Trust and Newcastle University.Disclosure of Interests:Emmanuella Traianos: None declared, Bethany Dibnah: None declared, Dennis Lendrem: None declared, Yasmin Clark: None declared, Victoria Macrae: None declared, Victoria Slater: None declared, Karl Wood: None declared, David Storey: None declared, Bruce Simon Shareholder of: Bruce Simon is an employee and shareholder of electroCore., Employee of: electroCore, Inc., Justyna Blake Shareholder of: Justyna Blake is an employee of electroCore, and receives stock ownership., Employee of: electroCore, Inc., Jessica Tarn: None declared, Wan Fai Ng: None declared

scholarly journals A Mobile App for Longterm Monitoring of Narcolepsy Symptoms: Design, Development, and Evaluation

10.2196/14939 ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. e14939
Author(s):  
Laury Quaedackers ◽  
Jan De Wit ◽  
Sigrid Pillen ◽  
Merel Van Gilst ◽  
Nikolaos Batalas ◽  
...  
Keyword(s):  
Interaction Design ◽  
Daytime Sleepiness ◽  
Patient Reported Outcome ◽  
Mobile App ◽  
Design Development ◽  
Subjective Burden ◽  
Design Data ◽  
Patient Reported ◽  
Depth Interviews ◽  
Over Time

Background Narcolepsy is a chronic sleep disorder with a broad variety of symptoms. Although narcolepsy is primarily characterized by excessive daytime sleepiness and cataplexy (loss of muscle control triggered by emotions), patients may suffer from hypnagogic hallucinations, sleep paralysis, and fragmented night sleep. However, the spectrum of narcolepsy also includes symptoms not related to sleep, such as cognitive or psychiatric problems. Symptoms vary greatly among patients and day-to-day variance can be considerable. Available narcolepsy questionnaires do not cover the whole symptom spectrum and may not capture symptom variability. Therefore, there is a clinical need for tools to monitor narcolepsy symptoms over time to evaluate their burden and the effect of treatment. Objective This study aimed to describe the design, development, implementation, and evaluation of the Narcolepsy Monitor, a companion app for long-term symptom monitoring in narcolepsy patients. Methods After several iterations during which content, interaction design, data management, and security were critically evaluated, a complete version of the app was built. The Narcolepsy Monitor allows patients to report a broad spectrum of experienced symptoms and rate their severity based on the level of burden that each symptom imposes. The app emphasizes the reporting of changes in relative severity of the symptoms. A total of 7 patients with narcolepsy were recruited and asked to use the app for 30 days. Evaluation was done by using in-depth interviews and user experience questionnaire. Results We designed and developed a final version of the Narcolepsy Monitor after which user evaluation took place. Patients used the app on an average of 45.3 (SD 19.2) days. The app was opened on 35% of those days. Daytime sleepiness was the most dynamic symptom, with a mean number of changes of 5.5 (SD 3.7) per month, in contrast to feelings of anxiety or panic, which was only moved 0.3 (SD 0.7) times per month. Mean symptom scores were highest for daytime sleepiness (1.8 [SD 1.0]), followed by lack of energy (1.6 [SD 1.4]) and often awake at night (1.5 [SD 1.0]). The personal in-depth interviews revealed 3 major themes: (1) reasons to use, (2) usability, and (3) features. Overall, patients appreciated the concept of ranking symptoms on subjective burden and found the app easy to use. Conclusions The Narcolepsy Monitor appears to be a helpful tool to gain more insight into the individual burden of narcolepsy symptoms over time and may serve as a patient-reported outcome measure for this debilitating disorder.

scholarly journals Which patient reported outcome domains are important to the rheumatologists while assessing patients with rheumatoid arthritis?

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Aprajita Jagpal ◽  
Ronan O’Beirne ◽  
Melanie S. Morris ◽  
Bernadette Johnson ◽  
James Willig ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Patient Reported Outcome ◽  
Patient Reported

scholarly journals Association of age with the non-achievement of clinical and functional remission in rheumatoid arthritis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tadashi Aoki ◽  
Hideki Ito ◽  
Takehisa Ogura ◽  
Ayako Hirata ◽  
Yuji Nishiwaki ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Elderly Patients ◽  
Health Assessment ◽  
Patient Reported Outcome ◽  
Normal Serum ◽  
Functional Health ◽  
Musculoskeletal Symptoms ◽  
Patient Reported ◽  
Remission Criteria ◽  
Effect Of Age

Abstract Patient-reported outcome (PRO) is included in the remission criteria of rheumatoid arthritis (RA). We aimed to determine the effect of age on PRO and the subsequent achievement of clinical and functional RA remission criteria. Three hundred and one patients with non-rheumatic diseases were evaluated using the 0–10 cm visual analog scale (VAS) assessment for musculoskeletal symptoms and a functional health assessment questionnaire-disability index (HAQ-DI). These assessments were compared with those obtained from 149 patients with RA with negative tender/swollen joint counts and normal serum C-reactive levels (objective clinical remission). Of the 301 patients, 32.2%, 26.6%, and 41.2% were classified as non-elderly (< 65 years), early elderly (65–74 years), and late-elderly (≥ 75 years) patients, respectively. VAS > 1 cm and HAQ-DI ≥ 0.5 were observed in 7.3% and 14.5%, respectively, in late-elderly patients, whereas ≤ 1.0% of non-elderly and early elderly patients for the both. Among 149 RA patients in objective remission, however, > 20% and > 10% of early elderly patients (and even non-elderly patients) had VAS > 1 cm and HAQ-DI ≥ 0.5, respectively, and 34.0% and 35.8% of late-elderly patients with RA had VAS > 1 cm and HAQ-DI ≥ 0.5, respectively. Multivariate logistic analysis revealed that age and RA were associated with the non-achievement of VAS ≤ 1 cm and HAQ-DI < 0.5. Therefore, the effect of age, which was independent of the presence of RA even without any objective disease activity, on PRO and the non-achievement of clinical and functional remission criteria was demonstrated.

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