Evidence map›Paper›PMID 34675298›Full record

Trial reportScientific reports2021

A novel multi-biomarker combination predicting relapse from long-term remission after discontinuation of biological drugs in rheumatoid arthritis.

Katsuya Nagatani, Eiji Sakashita, Hitoshi Endo, Seiji Minota

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
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  7. A broad look into the future of rheumatoid arthritis.Therapeutic advances in musculoskeletal disease · 2022
    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

4 authors at 1 institution in 1 country.

Katsuya Nagatani *Division of Rheumatology and Clinical Immunology, Department of Internal Medicine, Jichi Medical University School of Medicine, Tochigi, Japan.
Eiji Sakashita *Department of Biochemistry, Jichi Medical University School of Medicine, Tochigi, Japan.
Hitoshi EndoDepartment of Biochemistry, Jichi Medical University School of Medicine, Tochigi, Japan.
Seiji MinotaDivision of Rheumatology and Clinical Immunology, Department of Internal Medicine, Jichi Medical University School of Medicine, Tochigi, Japan. sminota@jichi.ac.jp.
Jichi Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological disease modifying anti-rheumatic drugs (bDMARDs) show dramatic treatment efficacy in rheumatoid arthritis (RA). Long-term use of bDMARDs, however, has disadvantages such as high costs and infection risk. Therefore, a methodology is needed to predict any future RA relapse. Herein, we report a novel multi-biomarker combination which predicts relapse after bDMARDs-withdrawal in patients in remission. Forty patients with RA in remission for more than 12 months were enrolled. bDMARDs were withdrawn and they were followed monthly for the next 24 months. Fourteen patients (35%) of 40 in the cohort remained in remission at 24 months, whereas 26 (65%) relapsed at various time-points. Serum samples obtained longitudinally from patients in remission were assessed for the relapse-prediction biomarkers and index from 73 cytokines by the exploratory multivariate ROC analysis. The relapse-prediction index calculated from the 5 cytokines, IL-34, CCL1, IL-1β, IL-2 and IL-19, strongly discriminated between patients who relapsed and those who stayed in remission. These findings could contribute to clinical decision-making as to the timing of when to discontinue bDMARDs in RA treatment.

Indexed as

AdultAgedAntirheumatic AgentsArthritis, RheumatoidBiomarkers, PharmacologicalCytokinesFemaleHumansMaleMiddle AgedPrognosisRecurrenceWithholding TreatmentAntirheumatic AgentsBiomarkers, PharmacologicalCytokines

Identifiers

PMID34675298
PMCPMC8531387
OpenAlexW3207480395

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LicenceCC BY
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Registered trials

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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.