Evidence map›Paper›PMID 37546687›Full record

ReviewFrontiers in molecular biosciences2023

Clinical application of serum biomarkers for detecting and monitoring of chronic plaque psoriasis.

Criselda Jean G Cruz, Chao-Chun Yang

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Psoriasis Area and Severity Index (PASI) Objectivisation by Flow Cytometry Analysis of Major Lymphocytes Subsets.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2023
    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

2 authors.

Criselda Jean G CruzDepartment of Dermatology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Chao-Chun YangDepartment of Dermatology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psoriasis, a chronic, multisystemic inflammatory disease affecting millions of people globally, manifests as erythematous, thick, scaly plaques on the skin. Clinical evaluation remains to be the benchmark for diagnosis and monitoring of this debilitating disease. With current advancements in targeted molecular therapy for psoriasis such as biologics, molecular detection methods may also help guide clinical decisions and therapeutic strategies through quantification of circulating biomarkers, which could reflect the underlying pathogenic events happening at a certain point of the disease course. In this review, we will discuss how biomarkers are detected in serum samples using enzyme-linked immunosorbent assay (ELISA). This review will feature candidate biomarkers supported by clinical data for psoriasis including, but not limited to, cytokines, chemokines, adipokines, and antimicrobial peptides. A better understanding of the common method used for biomarker detection would enable physicians to interpret and correlate laboratory results with the disease pathogenesis and clinical outcomes, e.g., severity assessment and/or therapeutic response. With better health outcomes as the main goal, the utility of such information to evaluate and even predict treatment response would be a major step closer towards patient-tailored management.

Indexed as

biologicsbiomarkersELISAinterleukinspsoriasisskin inflammation

Identifiers

PMID37546687
PMCPMC10403288

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.