Evidence map›Paper›PMID 42394977›Full record

SynthesisFrontiers in pharmacology2026

Periostin in allergic rhinitis: from pathogenic mediator to predictive biomarker and therapeutic target.

Han Wang, Qihang Zhang, Miao Hu, Junhao Shao, Guangke Wang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Han WangDepartment of Otorhinolaryngology and Head and Neck Surgery, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Qihang ZhangDepartment of Otorhinolaryngology and Head and Neck Surgery, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Miao HuDepartment of Otorhinolaryngology and Head and Neck Surgery, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Junhao ShaoDepartment of Otorhinolaryngology and Head and Neck Surgery, People's Hospital of Henan University, Zhengzhou, Henan, China.
Guangke WangDepartment of Otorhinolaryngology and Head and Neck Surgery, Henan Provincial People's Hospital, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allergic rhinitis (AR) is a common disease around the world, mediated by type 2 immune responses, and some patients don't respond well to current standard treatments. This shows AR isn't a single type of disease but a complex syndrome caused by different internal body mechanisms. Periostin is a key matrix protein sitting downstream of the interleukin-4 (IL-4) and interleukin-13 (IL-13) pathways, connecting type 2 immune responses and nasal mucosal tissue remodeling. This article explains periostin's many roles in AR: it breaks down the epithelial barrier, makes eosinophils gather, and causes fibrosis, and these things form a never-ending "inflammation-repair" vicious cycle. In clinical use, periostin levels in different biological samples matter-they relate to how severe the disease is and show how patients respond to glucocorticoids and biologics. Targeting periostin directly might offer new ways to help with hard-to-treat tissue remodeling. Based on these findings, we suggest a way to classify AR using periostin levels, which aims to guide personalized treatment in the future and help AR diagnosis and therapy become true precision medicine.

Indexed as

allergic rhinitisbiomarkerperiostinprecision medicinetissue remodelingtype 2 inflammation

Identifiers

PMID42394977
PMCPMC13322882

What OpenQuestion 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 OpenQuestion graph.