Evidence map›Paper›PMID 34085123›Full record

ArticleHandbook of experimental pharmacology2022

Precision Medicine in Chronic Rhinosinusitis: Where Does Allergy Fit In?

Xinni Xu, Yew Kwang Ong, De Yun Wang

Abstract read
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In one paragraph

Article in Handbook of experimental pharmacology, 2022. 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
0.8field-weighted citation impact, top 22% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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

3 authors at 3 institutions in 1 country.

Xinni XuDepartment of Otolaryngology-Head and Neck Surgery, National University Hospital System (NUHS), Singapore, Singapore.
Yew Kwang OngDepartment of Otolaryngology-Head and Neck Surgery, National University Hospital System (NUHS), Singapore, Singapore.
De Yun WangDepartment of Otolaryngology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. entwdy@nus.edu.sg.
National University Health System · SGNational University Hospital · SGNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic rhinosinusitis (CRS) is a clinical syndrome stemming from persistent inflammation of the sinonasal mucosa. Phenotypically, it is traditionally and widely described according to the presence or absence of polyps. While this distinction is simple to use, it has little bearing on prognosis and treatment, for CRS is essentially an inflammatory disease resulting from dysregulated interaction between a multitude of host and environmental factors. Allergy is merely one of them and, like many of the proposed aetiologies, has been subject to much debate which will be discussed here. As our understanding of CRS continues to evolve, previous so-called conventional wisdom about phenotypes (e.g. CRS with nasal polyps is associated with Type 2 inflammation) is being challenged, and new phenotypes are also emerging. In addition, there is growing interest in defining the endotypes of CRS to deliver precise and personalised treatment, especially pertaining to the development of biologics for the group of severe, difficult-to-treat CRS patients. A proposed model of precision medicine tailored to management of CRS will also be introduced to readers, which can be continually modified to adapt to new discoveries about this exciting condition.

Indexed as

HypersensitivityNasal PolypsRhinitisSinusitisChronic DiseaseHumansPrecision MedicineAllergyChronic rhinosinusitisEndotypePrecision medicine

Identifiers

PMID34085123
OpenAlexW3164243741

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.