Evidence map›Paper›PMID 38306157›Full record

ArticleJMIR formative research2024

Exploring the Perspectives of Patients Living With Lupus: Retrospective Social Listening Study.

Erica Spies, Thomas Andreu, Matthias Hartung, Josephine Park, Paul Kamudoni

Abstract read
In one paragraph

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 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Natural language processing in dermatology: A systematic literature review and state of the art.Journal of the European Academy of Dermatology and Venereology : JEADV · 2024
    Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Erica SpiesEMD Serono, Billerica, MA, United States.ORCID https://orcid.org/0009-0008-2006-9933
Thomas AndreuSemalytix GmbH, Bielefeld, Germany.ORCID https://orcid.org/0009-0005-7304-0569
Matthias HartungSemalytix GmbH, Bielefeld, Germany.ORCID https://orcid.org/0000-0001-6549-066X
Josephine ParkEMD Serono, Billerica, MA, United States.ORCID https://orcid.org/0009-0000-5270-1835
Paul KamudoniThe Healthcare Business of Merck KGaA, Darmstadt, Germany.ORCID https://orcid.org/0000-0002-4669-0647

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystemic lupus erythematosus (SLE) is a chronic autoimmune inflammatory disease affecting various organs with a wide range of clinical manifestations. Cutaneous lupus erythematosus (CLE) can manifest as a feature of SLE or an independent skin ailment. Health-related quality of life (HRQoL) is frequently compromised in individuals living with lupus. Understanding patients' perspectives when living with a disease is crucial for effectively meeting their unmet needs. Social listening is a promising new method that can provide insights into the experiences of patients living with their disease (lupus) and leverage these insights to inform drug development strategies for addressing their unmet needs.

objectiveThe objective of this study is to explore the experience of patients living with SLE and CLE, including their disease and treatment experiences, HRQoL, and unmet needs, as discussed in web-based social media platforms such as blogs and forums.

methodsA retrospective exploratory social listening study was conducted across 13 publicly available English-language social media platforms from October 2019 to January 2022. Data were processed using natural language processing and knowledge graph tagging technology to clean, format, anonymize, and annotate them algorithmically before feeding them to Pharos, a Semalytix proprietary data visualization and analysis platform, for further analysis. Pharos was used to generate descriptive data statistics, providing insights into the magnitude of individual patient experience variables, their differences in the magnitude of variables, and the associations between algorithmically tagged variables.

resultsA total of 45,554 posts from 3834 individuals who were algorithmically identified as patients with lupus were included in this study. Among them, 1925 (authoring 5636 posts) and 106 (authoring 243 posts) patients were identified as having SLE and CLE, respectively. Patients frequently mentioned various symptoms in relation to SLE and CLE including pain, fatigue, and rashes; pain and fatigue were identified as the main drivers of HRQoL impairment. The most affected aspects of HRQoL included "mobility," "cognitive capabilities," "recreation and leisure," and "sleep and rest." Existing pharmacological interventions poorly managed the most burdensome symptoms of lupus. Conversely, nonpharmacological treatments, such as exercise and meditation, were frequently associated with HRQoL improvement.

conclusionsPatients with lupus reported a complex interplay of symptoms and HRQoL aspects that negatively influenced one another. This study demonstrates that social listening is an effective method to gather insights into patients' experiences, preferences, and unmet needs, which can be considered during the drug development process to develop effective therapies and improve disease management.

Indexed as

autoimmuneblogblogschronicCLEcutaneouscutaneous lupus erythematosusdermatologicaldermatologyexperienceexperiencesforumforumshealth-related quality of lifeHRQoLinflammationinflammatoryinfodemiologyinfoveillanceknowledge graphlupusmachine learningnatural language processingquality of liferareskinSLEsocial listeningsocial mediasocial media listeningsystemic lupus erythematosustaggedtaggingvisualizationvisualizations

Identifiers

PMID38306157
PMCPMC10873798

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.