Evidence map›Paper›PMID 35330802›Full record

ArticleEClinicalMedicine2022

Associations of Four sensitization patterns revealed by Latent Class Analysis with Clinical symptoms: A multi-center study of China.

Xiangqing Hou, Wenting Luo, Liting Wu, Yuemin Chen, Guoping Li, Rongfang Zhang, Hong Zhang, Jing Wu, Yun Sun, Lina Xu and 5 more

Abstract read
In one paragraph

Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. [Pollen-food allergy syndrome: association between allergen cross-reactivity and symptom severity].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025
    Article
  5. Article
  6. High sensitization toThe World Allergy Organization journal · 2025
    Article
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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

15 authors.

Xiangqing HouFaculty of Health Sciences, University of Macau 999078, Macau, China.
Wenting LuoDepartment of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou 510120, Guangdong, China.
Liting WuDepartment of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou 510120, Guangdong, China.
Yuemin ChenDepartment of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou 510120, Guangdong, China.
Guoping LiDepartment of Pulmonary and Critical Care Medicine, Laboratory of Allergy and Precision Medicine, Chengdu Institute of Respiratory Health, the Third People's Hospital of Chengdu, Branch of National Clinical, 610000, Chengdu, China.
Rongfang ZhangDepartment of Pediatrics, Gansu Provincial Maternity and Child Care Hospital 730400, Gansu, China.
Hong ZhangDepartment of Pediatrics, Gansu Provincial Hospital 730400, Gansu, China.
Jing WuDepartment of Allergy and Clinical Immunology, Inner Mongolia Cancer Hospital 021000, Inner Mongolia, China.
Yun SunDepartment of Pediatrics, Yinchuan Maternal and Child Health Care Hospital 750001, Yinchuan, China.
Lina XuDepartment of Respirology, Children's Hospital, Soochow University 215025, Suzhou, China.
Peiru XuDepartment of Pediatrics, First Affiliated Hospital of Xinjiang Medical University 830000, China.
Yongmei YuDepartment of Pediatrics, First Affiliated Hospital of Kunming Medical University 650000, Kunming, China.
Dongming HuangDepartment of Pediatrics, Bo'ai Hospital of Zhongshan City 511462, Zhongshan, China.
Chuangli HaoDepartment of Respirology, Children's Hospital, Soochow University 215025, Suzhou, China.
Baoqing SunDepartment of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou 510120, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Because of the significant regional differences in the distribution of allergens, the relationship between anaphylaxis and allergic sensitization is complex in China. Using this large-scale epidemiologic survey, we explore the potential patterns of sensitization to common allergens in mainland China and investigate their relationship with various clinical symptoms. Method: The participants were recruited from 13 medical centers in mainland China from October 2019 to June 2021. Skin prick test (SPT) results that cover 18 common allergens were utilized to diagnose atopic sensitization. The demographic characteristics and clinical information were collected through questionnaires during routine medical follow-up. Latent class analysis (LCA) was conducted to determine the optimal sensitization patterns. The logistic regression was used to assess the associations of different sensitization patterns with allergy symptoms. Findings: A total of 1089 patients who had a positive SPT to at least one of 18 allergens were included for formal analysis. An optimal LCA model with 4 classes was obtained in this study, and the corresponding labels were as follows: Class1, house dust mite sensitization; Class2, low pollen sensitization; Class3, middle pollen sensitization; Class4, high pollen sensitization. The prevalence of different classes varied widely in geographical distribution, which was characterized by Class1 being very common in south and east as well as Class2 in north and west of China. Compared with patients in Class1, those in middle and high pollen sensitization clusters had the higher odds ratios (ORs) of allergic rhinitis and allergic conjunctivitis when controlling for other confounders. However, there was no significant difference between low pollen sensitization and house dust mite sensitization groups in the risks for various clinical performances except dermatitis. Additionally, the adjusted ORs (95% confidence interval) of allergic conjunctivitis and dermatitis for participants in pollen sensitization clusters (Class2, 3 and 4) were 1.56 (1.18, 2.06) and 1.43 (1.09, 1.88) respectively compared with those in Class1. Interpretation: In this study, we identified four sensitization clusters with specific risks of various clinical symptoms using common allergens by adopting LCA. Our findings may contribute to improved diagnosis and potential immunotherapy approaches to allergy in mainland China. Funding: This study was supported by the National Natural Science Foundation of China (81802076 and 81871736), the Guangzhou Science and Technology Foundation (202102010327), the Foundation of SKLRD (MS-2019-06 and Z-2022-09), and the Foundation of GYYY (ZH201904) and ZNSA-2020012.

Indexed as

95% CI, 95% confidence intervalAIC, Akaike Information CriterionAR, allergic rhinitisAS, asthmaBIC, Bayesian Information CriterionCAIC, the “consistent AIC”clinical symptomsCRD, component-resolved diagnosisIgE, Immunoglobulin Elatent class analysisLCA, latent class analysissensitization patternssIgE, specific IgEskin prick testSPT, skin prick testSSA-BIC, the adjusted BIC using Rissanen's sample size adjustment

Identifiers

PMID35330802
PMCPMC8938883

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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.