Evidence map›Paper›PMID 32159792›Full record

ReviewRheumatology (Oxford, England)2020

Assessment of the many faces of PsA: single and composite measures in PsA clinical trials.

Dylan McGagh, Laura C Coates

Abstract readReview
In one paragraph

Review in Rheumatology (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. TheCurrent pharmaceutical biotechnology · 2023
    Article
  6. Article
  7. Observational
  8. Article
  9. Review
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

2 authors at 2 institutions in 1 country.

Dylan McGaghMedical School, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK.
Laura C CoatesNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK.
Nuffield Orthopaedic Centre · GBUniversity of Oxford · GB

Funding

Department of Health CS-2016-16-016
6 · The paper itself

Abstract

PsA is a complex, heterogeneous disease that can place a large burden on patients' psychological and physical well-being. The multifaceted nature of PsA poses a significant assessment challenge, both in randomized control trials and in clinical practice. In recent years, there has been much progress in the development of unidimensional and composite measures of disease activity, as well as of questionnaires that capture the patient's perspective of the condition. Despite these advances, there remains uncertainty around which tools to implement within a research setting. This review aims to summarize the currently available clinical and patient-derived assessment tools, providing a practical and informative resource for the assessment of PsA. This review will also explore recent advancements in digital approaches to the assessment of rheumatological conditions. This will highlight the potential for digitalization in the assessment and monitoring of PsA, outlining innovative means of capturing disease activity and treatment response.

Indexed as

ArthritisArthritis, PsoriaticCost of IllnessEnthesopathyHumansMedical InformaticsOutcome Assessment, Health CarePain MeasurementQuality of LifeRandomized Controlled Trials as TopicSpondylarthropathiesSurveys and QuestionnairesTelemedicinecomposite measuresdisease activityhealth information technologyimpact of diseasemobile healthoutcome measurespatient perspectivepsoriatic arthritis

Identifiers

PMID32159792
PMCPMC7065465
OpenAlexW3012027749

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.