Evidence map›Paper›PMID 33763493›Full record

ArticleJournal of immunology research2021

Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA.

Po-Ku Chen, Joung-Liang Lan, Yi-Ming Chen, Hsin-Hua Chen, Shih-Hsin Chang, Chia-Min Chung, Nurul H Rutt, Ti-Myen Tan, Raja Nurashirin Raja Mamat, Nur Diana Anuar and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-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

8 citing papers in PubMed, 16 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Po-Ku ChenTranslational Medicine Laboratory, Rheumatic Diseases Research Center, China Medical University Hospital, Taichung, Taiwan.
Joung-Liang LanCollege of Medicine, China Medical University, Taichung, Taiwan.
Yi-Ming ChenDepartment of Medical Research, Taichung Veterans General Hospital, Taiwan.
Hsin-Hua ChenDepartment of Medical Research, Taichung Veterans General Hospital, Taiwan.
Shih-Hsin ChangCollege of Medicine, China Medical University, Taichung, Taiwan.
Chia-Min ChungCenter for Drug Abuse and Addiction, China Medical University Hospital, Taichung, Taiwan.
Nurul H RuttSengenics Corporation Pte Ltd., Singapore.
Ti-Myen TanSengenics Corporation Pte Ltd., Singapore.
Raja Nurashirin Raja MamatSengenics Corporation Pte Ltd., Singapore.
Nur Diana AnuarSengenics Corporation Pte Ltd., Singapore.
Jonathan M BlackburnSengenics Corporation Pte Ltd., Singapore.
Der-Yuan ChenTranslational Medicine Laboratory, Rheumatic Diseases Research Center, China Medical University Hospital, Taichung, Taiwan.ORCID https://orcid.org/0000-0003-1266-1423
China Medical University · TWNational Yang Ming Chiao Tung University · TWNational Chung Hsing University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anti-drug antibody (ADAb) development is associated with secondary therapeutic failure in biologic-treated rheumatoid arthritis (RA) patients. With a treat-to-target goal, we aimed to identify biomarkers for predicting ADAb development and therapeutic response in adalimumab-treated patients. Three independent cohorts were enrolled. In Cohort-1, 24 plasma samples (6 ADAb-positive and 6 ADAb-negative patients at baseline and week 24 of adalimumab therapy, respectively) were assayed with immune-related microarray containing 1,636 correctly folded functional proteins. Next, we executed statistically powered autoantibody profiling analysis of 50 samples in Cohort-2 (24 ADAb-positive and 26 ADAb-negative patients). Subsequently, immunofluorescence assay was performed on 48 samples in Cohort-3 to correlate with ADAb titers and drug levels. The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 (median = 0.024

Indexed as

AdalimumabAdultAntibodiesAntirheumatic AgentsArthritis, RheumatoidAutoantibodiesAutoantigensBiomarkers, PharmacologicalCohort StudiesDrug HypersensitivityDrug-Related Side Effects and Adverse ReactionsFemaleHumansImmunoassayMaleMicroarray AnalysisAdalimumabAntibodiesAntirheumatic AgentsAutoantibodiesAutoantigensBiomarkers, PharmacologicalRibonucleoproteinsRNA, Small CytoplasmicRO60 protein, humanSS-A Antigen

Identifiers

PMID33763493
PMCPMC7963899
OpenAlexW3134525900

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.