Evidence map›Paper›PMID 37301840›Full record

ReviewClinical proteomics2023

Tailored therapeutic decision of rheumatoid arthritis using proteomic strategies: how to start and when to stop?

Shuo-Fu Chen, Fu-Chiang Yeh, Ching-Yun Chen, Hui-Yin Chang

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical proteomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Trial
  2. 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

4 authors at 4 institutions in 1 country.

Shuo-Fu ChenDepartment of Heavy Particles & Radiation Oncology, Taipei Veterans General Hospital, Taipei, Taiwan.
Fu-Chiang YehDivision of Rheumatology, Immunology and Allergy, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
Ching-Yun ChenDepartment of Biomedical Sciences and Engineering, Institute of Biomedical Engineering and Nanomedicine, National Central University, Taoyuan, Taiwan.
Hui-Yin ChangDepartment of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central University, No. 300, Zhongda Rd., Zhongli District, Taoyuan, 320317, Taiwan. dr.chuiyin@gmail.com.ORCID http://orcid.org/0000-0003-1767-1874
National Central University · TWNational Health Research Institutes · TWTaipei Veterans General Hospital · TWTri-Service General Hospital · TW

Funding

Ministry of Science and Technology, Taiwan MOST-110-2320-B-008-001-MY2
6 · The paper itself

Abstract

Unpredictable treatment responses have been an obstacle for the successful management of rheumatoid arthritis. Although numerous serum proteins have been proposed, there is a lack of integrative survey to compare their relevance in predicting treatment outcomes in rheumatoid arthritis. Also, little is known about their applications in various treatment stages, such as dose modification, drug switching or withdrawal. Here we present an in-depth exploration of the potential usefulness of serum proteins in clinical decision-making and unveil the spectrum of immunopathology underlying responders to different drugs. Patients with robust autoimmunity and inflammation are more responsive to biological treatments and prone to relapse during treatment de-escalation. Moreover, the concentration changes of serum proteins at the beginning of the treatments possibly assist early recognition of treatment responders. With a better understanding of the relationship between the serum proteome and treatment responses, personalized medicine in rheumatoid arthritis will be more achievable in the near future.

Indexed as

BiomarkersPredictionProteomicsRheumatoid arthritisTreatment response

Identifiers

PMID37301840
PMCPMC10257292
OpenAlexW4380203580

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.