Evidence map›Paper›PMID 39467551›Full record

ArticleJMIR formative research2024

Exploring the Potential of Electronic Patient-Generated Health Data for Evaluating Treatment Response to Intramuscular Steroids in Rheumatoid Arthritis: Case Series.

Mariam Al-Attar, Kesmanee Assawamartbunlue, Julie Gandrup, Sabine N van der Veer, William G Dixon

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Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mariam Al-AttarCentre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-3450-5803
Kesmanee AssawamartbunlueSchool of Medical Sciences, University of Manchester, Manchester, United Kingdom.ORCID 0009-0009-7415-4428
Julie GandrupCentre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-4109-4889
Sabine N van der VeerCentre for Health Informatics, Division of Informatics, Imaging and Data Science, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom.ORCID 0000-0003-0929-436X
William G DixonCentre for Epidemiology Versus Arthritis, University of Manchester, Manchester, United Kingdom.ORCID 0000-0001-5881-4857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health devices are increasingly available, presenting exciting opportunities to remotely collect high-frequency, electronic patient-generated health data (ePGHD). This novel data type may provide detailed insights into disease activity outside usual clinical settings. Assessing treatment responses, which can be hampered by the infrequency of appointments and recall bias, is a promising, novel application of ePGHD. Drugs with short treatment effects, such as intramuscular steroid injections, illustrate the challenge, as patients are unlikely to accurately recall treatment responses at follow-ups, which often occur several months later. Retrospective assessment means that responses may be over- or underestimated. High-frequency ePGHD, such as daily, app-collected, patient-reported symptoms between clinic appointments, may bridge this gap. However, the potential of ePGHD remains untapped due to the absence of established definitions for treatment response using ePGHD or established methodological approaches for analyzing this type of data.

objectiveThis study aims to explore the feasibility of evaluating treatment responses to intramuscular steroid therapy in a case series of patients with rheumatoid arthritis tracking daily symptoms using a smartphone app.

methodsWe report a case series of patients who collected ePGHD through the REmote Monitoring Of Rheumatoid Arthritis (REMORA) smartphone app for daily remote symptom tracking. Symptoms were tracked on a 0-10 scale. We described the patients' longitudinal pain scores before and after intramuscular steroid injections. The baseline pain score was calculated as the mean pain score in the 10 days prior to the injection. This was compared to the pain scores in the days following the injection. "Response" was defined as any improvement from the baseline score on the first day following the injection. The response end time was defined as the first date when the pain score exceeded the pre-steroid baseline.

resultsWe included 6 patients who, between them, received 9 steroid injections. Average pre-injection pain scores ranged from 3.3 to 9.3. Using our definitions, 7 injections demonstrated a response. Among the responders, the duration of response ranged from 1 to 54 days (median 9, IQR 7-41), average pain score improvement ranged from 0.1 to 5.3 (median 3.3, IQR 2.2-4.0), and maximum pain score improvement ranged from 0.1 to 7.0 (median 4.3, IQR 1.7 to 6.0).

conclusionsThis case series demonstrates the feasibility of using ePGHD to evaluate treatment response and is an important exploratory step toward developing more robust methodological approaches for analysis of this novel data type. Issues highlighted by our analysis include the importance of accounting for one-off data points, varying response start times, and confounders such as other medications. Future analysis of ePGHD across a larger population is required to address issues highlighted by our analysis and to develop meaningful consensus definitions for treatment response in time-series data.

Indexed as

Arthritis, RheumatoidAdultAgedFemaleHumansInjections, IntramuscularMaleMiddle AgedMobile ApplicationsRetrospective StudiesSteroidsTreatment OutcomeSteroidsappcase seriesintramuscular steroid injectionsmobile healthpain scorepatient-generated health datapatient-reported outcome measuresremote monitoringrheumatoid arthritissymptom tracking

Identifiers

PMID39467551
PMCPMC11555448

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.