Evidence map›Paper›PMID 31432000›Full record

ArticleRheumatology advances in practice2019

Exploring sub-optimal response to tumour necrosis factor inhibitors in axial spondyloarthritis.

Fariz Yahya, Karl Gaffney, Raj Sengupta

Open access · goldAbstract read
In one paragraph

Article in Rheumatology advances in practice, 2019. 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
0.9field-weighted citation impact, top 25% 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, 5 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 2 countries.

Fariz YahyaDepartment of Rheumatology, Royal National Hospital for Rheumatic Diseases, RUH NHS Foundation Trust, Bath, UK.ORCID 0000-0001-8139-7764
Karl GaffneyDepartment of Rheumatology, Norfolk and Norwich University Hospital NHS Foundation Trust, Norwich.
Raj SenguptaDepartment of Rheumatology, Royal National Hospital for Rheumatic Diseases, RUH NHS Foundation Trust, Bath, UK.ORCID 0000-0002-9720-0396
Royal National Hospital for Rheumatic Diseases · GBNorfolk and Norwich University Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim was to define sub-optimal response to TNF inhibitors (TNFi), compare long-term drug survival rates and identify predictors of sub-optimal response in axial spondyloarthritis (axSpA) patients in a UK cohort.

methodsAll axSpA patients attending two centres who commenced TNFi between 2002 and 2016 were included. Routinely recorded patient data were reviewed retrospectively. Patients with paired BASDAI at baseline, 3 and/or 6 months were included for analysis. Sub-optimal response was defined as achieving a ≥ 2-point reduction in BASDAI but not BASDAI50, post-treatment BASDAI remaining at ≥4, and in the opinion of the treating physician these patients demonstrated a meaningful clinical response.

resultsFour hundred and ninety-nine patients were included: 82 (16.4%) patients were classified as having a sub-optimal response; 64 (78%) males, 78 (95.1%) AS and 55/67 (82.1%) HLA-B27 positive. Results are reported as the mean (s.d.). Time to diagnosis was 10 (8.6) years, age at diagnosis was 37 (11.7) years, and age at initiating index TNFi was 48 (11.1) years. Individual index TNFi were Humira (adalimumab,

conclusionA significant proportion of patients continued TNFi despite demonstrated sub-optimal response. Further research needs to be undertaken in order to understand this group.

Indexed as

axial spondyloarthritispredictorssub-optimal responsesurvival ratesTNF inhibitors

Identifiers

PMID31432000
PMCPMC6649897
OpenAlexW2945685421

What OpenQuestion holds

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LicenceCC BY
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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.