Evidence map›Paper›PMID 26810813›Full record

Trial reportBritish journal of clinical pharmacology2016

A model-based evaluation of single metrics for discriminating changes in rheumatoid arthritis disease activity.

Jessica Wojciechowski, Michael D Wiese, Susanna M Proudman, David J R Foster, Richard N Upton

Open access · bronzeAbstract readClinical Trial
In one paragraph

Trial report in British journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 95% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Trial
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 at 3 institutions in 1 country.

Jessica WojciechowskiAustralian Centre for Pharmacometrics, University of South Australia, Adelaide.
Michael D WieseSansom Institute for Health Research, University of South Australia, Adelaide.
Susanna M ProudmanRheumatology Unit, Royal Adelaide Hospital, Adelaide.
David J R FosterAustralian Centre for Pharmacometrics, University of South Australia, Adelaide.
Richard N UptonAustralian Centre for Pharmacometrics, University of South Australia, Adelaide.
Australian Centre for Plant Functional Genomics · AUUniversity of South Australia · AUUniversity of Adelaide · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsComposite indices for quantifying rheumatoid arthritis (RA) disease activity such as the 28-joint disease activity score (DAS28) are comprised of single parameters ('metrics') in various combinations. Population modelling methods were used to evaluate single metrics for their ability to reflect changes in disease activity with a view to understanding and improving composite indices.

methodsA total of 11 single metrics of RA disease activity (tender and swollen joint counts, acute phase reactants and global health, pain and physical function assessments) were obtained from 203 patients with recent onset RA. Participants received combination disease-modifying anti-rheumatic drugs (DMARDs) according to a treat-to-target approach with a pre-defined protocol for treatment intensification. Models describing each metric's magnitude and variability of change from baseline to a single 'treated' state in the population were developed using nonmem(®) . Measures that displayed uniformly large changes between states across the population were ranked higher in terms of discriminatory capacity.

resultsJoint counts demonstrated a greater ability to discriminate changes in RA disease activity than others. Correlations between metrics demonstrated that erythrocyte sedimentation rate (ESR) had limited relationships with others for baseline scores and changes in RA disease activity (r generally < 0.2). However it appeared to be important in describing changes for those individuals where ESR levels were initially elevated.

conclusionIt appears unlikely that a single group of metrics may be suitable to capture disease activity changes across all RA patients and defining the most appropriate metric(s) for individual patients will be an important area of future research.

Indexed as

Models, BiologicalSeverity of Illness IndexAdultAgedAntirheumatic AgentsArthritis, RheumatoidFemaleHumansMaleMiddle AgedAntirheumatic Agentsdisease activitydisease modifying anti-rheumatic drugspopulation modellingrheumatoid arthritis

Identifiers

PMID26810813
PMCPMC4876190
OpenAlexW2343732124

What OpenQuestion holds

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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.