Evidence map›Paper›PMID 28755058›Full record

ReviewClinical drug investigation2017

Novel Biologic Agents Targeting Interleukin-23 and Interleukin-17 for Moderate-to-Severe Psoriasis.

Zeyu Chen, Yu Gong, Yuling Shi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical drug investigation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

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  8. Discovery ofACS medicinal chemistry letters · 2020
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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

3 authors at 1 institution in 1 country.

Zeyu ChenDepartment of Dermatology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, No. 301, Middle Yanchang Road, Jing'an District, Shanghai, 200072, China.
Yu GongDepartment of Dermatology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, No. 301, Middle Yanchang Road, Jing'an District, Shanghai, 200072, China.
Yuling ShiDepartment of Dermatology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, No. 301, Middle Yanchang Road, Jing'an District, Shanghai, 200072, China. shiyuling1973@tongji.edu.cn.ORCID http://orcid.org/0000-0002-1273-7881
Tongji University · CN

Funding

National Science Foundation of China 81673050National Science Foundation of Shanghai 16ZR1426800
6 · The paper itself

Abstract

Psoriasis is a common, chronic inflammatory skin disease and cannot be cured. The treatment of moderate-to-severe plaque psoriasis has been revolutionized with the development of biologic agents for nearly 20 years. Current studies show that interleukin-23 and interleukin-17 play remarkable roles in the pathogenesis of psoriasis. Interleukin-23 can sustain the differentiation and maintenance of T helper-17 lineage. Interleukin-17 can recruit and stimulate many cells, which play important parts in psoriasis through interacting with the interleukin-17 receptor. Several biologic agents targeting interleukin-23, interleukin-17, or their receptors are now in different stages: some are approved or clinical trials are in progress. Ustekinumab targets interleukin-23/interleukin-12p40; risankizumab, guselkumab, and tildrakizumab target interleukin-23p19; secukinumab and ixekizumab target interleukin-17A; and brodalumab targets the interleukin-17 receptors. All of these agents have good efficacy in treating moderate-to-severe psoriasis.

Indexed as

Biological FactorsHumansInterleukin-17Interleukin-23PsoriasisBiological FactorsInterleukin-17Interleukin-23

Identifiers

PMID28755058
OpenAlexW2741718485

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.