Korean childhood asthma study (KAS): A prospective, observational cohort of Korean asthmatic children

Dong In Suh, Dae-Jin Song, Hey Sung Baek, Meeyong Shin, Young Yoo, Ji Won Kwon, Gwang Cheon Jang, Hyeon Jong Yang, Eun Lee, Hwan Soo Kim, Ju Hee Seo, Sung Il Woo, Hyung Young Kim, Youn Ho Shin, Ju Suk Lee, Jisun Yoon, Sungsu Jung, Minkyu Han, Eunjin Eom, Jinho YuWoo Kyung Kim, Dae Hyun Lim, Jin Tack Kim, Woo Sung Chang, Jeom Kyu Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Asthma is a syndrome composed of heterogeneous disease entities. Although it is agreed that proper asthma endo-typing and appropriate type-specific interventions are crucial in the management of asthma, little data are available regarding pediatric asthma. Methods: We designed a cluster-based, prospective, observational cohort study of asthmatic children in Korea (Korean childhood Asthma Study [KAS]). A total of 1000 Korean asthmatic children, aged from 5 to 15 years, will be enrolled at the allergy clinics of the 19 regional tertiary hospitals from August 2016 to December 2018. Physicians will verify the relevant histories of asthma and comorbid diseases, as well as airway lability from the results of spirometry and bronchial provocation tests. Questionnaires regarding subjects' baseline characteristics and their environment, self-rating of asthma control, and laboratory tests for allergy and airway inflammation will be collected at the time of enrollment. Follow-up data regarding asthma control, lung function, and environmental questionnaires will be collected at least every 6 months to assess outcome and exacerbation-related aggravating factors. In a subgroup of subjects, peak expiratory flow rate will be monitored by communication through a mobile application during the overall study period. Cluster analysis of the initial data will be used to classify Korean pediatric asthma patients into several clusters; the exacerbation and progression of asthma will be assessed and compared among these clusters. In a subgroup of patients, big data-based deep learning analysis will be applied to predict asthma exacerbation. Discussion: Based on the assumption that asthma is heterogeneous and each subject exhibits a different subset of risk factors for asthma exacerbation, as well as a different disease progression, the KAS aims to identify several asthma clusters and their essential determinants, which are more suitable for Korean asthmatic children. Thereafter we may suggest cluster-specific strategies by focusing on subjects' personalized aggravating factors during each exacerbation episode and by focusing on disease progression. The KAS will provide a good academic background with respect to each interventional strategy to achieve better asthma control and prognosis.

Original languageEnglish
Article number64
JournalBMC Pulmonary Medicine
Volume19
Issue number1
DOIs
Publication statusPublished - 2019 Mar 15

Fingerprint

Asthma
Prospective Studies
Disease Progression
Hypersensitivity
Mobile Applications
Bronchial Provocation Tests
Pediatrics
Peak Expiratory Flow Rate
Spirometry
Korea
Tertiary Care Centers
Observational Studies
Cluster Analysis
Cohort Studies
Communication
Learning
Inflammation
Physicians

Keywords

  • Asthma
  • Child
  • Cluster
  • Cohort study
  • Korea
  • Prospective

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Cite this

Korean childhood asthma study (KAS) : A prospective, observational cohort of Korean asthmatic children. / In Suh, Dong; Song, Dae-Jin; Baek, Hey Sung; Shin, Meeyong; Yoo, Young; Kwon, Ji Won; Jang, Gwang Cheon; Yang, Hyeon Jong; Lee, Eun; Kim, Hwan Soo; Seo, Ju Hee; Woo, Sung Il; Kim, Hyung Young; Shin, Youn Ho; Lee, Ju Suk; Yoon, Jisun; Jung, Sungsu; Han, Minkyu; Eom, Eunjin; Yu, Jinho; Kim, Woo Kyung; Lim, Dae Hyun; Kim, Jin Tack; Chang, Woo Sung; Lee, Jeom Kyu.

In: BMC Pulmonary Medicine, Vol. 19, No. 1, 64, 15.03.2019.

Research output: Contribution to journalArticle

In Suh, D, Song, D-J, Baek, HS, Shin, M, Yoo, Y, Kwon, JW, Jang, GC, Yang, HJ, Lee, E, Kim, HS, Seo, JH, Woo, SI, Kim, HY, Shin, YH, Lee, JS, Yoon, J, Jung, S, Han, M, Eom, E, Yu, J, Kim, WK, Lim, DH, Kim, JT, Chang, WS & Lee, JK 2019, 'Korean childhood asthma study (KAS): A prospective, observational cohort of Korean asthmatic children', BMC Pulmonary Medicine, vol. 19, no. 1, 64. https://doi.org/10.1186/s12890-019-0829-3
In Suh, Dong ; Song, Dae-Jin ; Baek, Hey Sung ; Shin, Meeyong ; Yoo, Young ; Kwon, Ji Won ; Jang, Gwang Cheon ; Yang, Hyeon Jong ; Lee, Eun ; Kim, Hwan Soo ; Seo, Ju Hee ; Woo, Sung Il ; Kim, Hyung Young ; Shin, Youn Ho ; Lee, Ju Suk ; Yoon, Jisun ; Jung, Sungsu ; Han, Minkyu ; Eom, Eunjin ; Yu, Jinho ; Kim, Woo Kyung ; Lim, Dae Hyun ; Kim, Jin Tack ; Chang, Woo Sung ; Lee, Jeom Kyu. / Korean childhood asthma study (KAS) : A prospective, observational cohort of Korean asthmatic children. In: BMC Pulmonary Medicine. 2019 ; Vol. 19, No. 1.
@article{da5aab18dc344a05a839e33a6fcf6285,
title = "Korean childhood asthma study (KAS): A prospective, observational cohort of Korean asthmatic children",
abstract = "Background: Asthma is a syndrome composed of heterogeneous disease entities. Although it is agreed that proper asthma endo-typing and appropriate type-specific interventions are crucial in the management of asthma, little data are available regarding pediatric asthma. Methods: We designed a cluster-based, prospective, observational cohort study of asthmatic children in Korea (Korean childhood Asthma Study [KAS]). A total of 1000 Korean asthmatic children, aged from 5 to 15 years, will be enrolled at the allergy clinics of the 19 regional tertiary hospitals from August 2016 to December 2018. Physicians will verify the relevant histories of asthma and comorbid diseases, as well as airway lability from the results of spirometry and bronchial provocation tests. Questionnaires regarding subjects' baseline characteristics and their environment, self-rating of asthma control, and laboratory tests for allergy and airway inflammation will be collected at the time of enrollment. Follow-up data regarding asthma control, lung function, and environmental questionnaires will be collected at least every 6 months to assess outcome and exacerbation-related aggravating factors. In a subgroup of subjects, peak expiratory flow rate will be monitored by communication through a mobile application during the overall study period. Cluster analysis of the initial data will be used to classify Korean pediatric asthma patients into several clusters; the exacerbation and progression of asthma will be assessed and compared among these clusters. In a subgroup of patients, big data-based deep learning analysis will be applied to predict asthma exacerbation. Discussion: Based on the assumption that asthma is heterogeneous and each subject exhibits a different subset of risk factors for asthma exacerbation, as well as a different disease progression, the KAS aims to identify several asthma clusters and their essential determinants, which are more suitable for Korean asthmatic children. Thereafter we may suggest cluster-specific strategies by focusing on subjects' personalized aggravating factors during each exacerbation episode and by focusing on disease progression. The KAS will provide a good academic background with respect to each interventional strategy to achieve better asthma control and prognosis.",
keywords = "Asthma, Child, Cluster, Cohort study, Korea, Prospective",
author = "{In Suh}, Dong and Dae-Jin Song and Baek, {Hey Sung} and Meeyong Shin and Young Yoo and Kwon, {Ji Won} and Jang, {Gwang Cheon} and Yang, {Hyeon Jong} and Eun Lee and Kim, {Hwan Soo} and Seo, {Ju Hee} and Woo, {Sung Il} and Kim, {Hyung Young} and Shin, {Youn Ho} and Lee, {Ju Suk} and Jisun Yoon and Sungsu Jung and Minkyu Han and Eunjin Eom and Jinho Yu and Kim, {Woo Kyung} and Lim, {Dae Hyun} and Kim, {Jin Tack} and Chang, {Woo Sung} and Lee, {Jeom Kyu}",
year = "2019",
month = "3",
day = "15",
doi = "10.1186/s12890-019-0829-3",
language = "English",
volume = "19",
journal = "BMC Pulmonary Medicine",
issn = "1471-2466",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Korean childhood asthma study (KAS)

T2 - A prospective, observational cohort of Korean asthmatic children

AU - In Suh, Dong

AU - Song, Dae-Jin

AU - Baek, Hey Sung

AU - Shin, Meeyong

AU - Yoo, Young

AU - Kwon, Ji Won

AU - Jang, Gwang Cheon

AU - Yang, Hyeon Jong

AU - Lee, Eun

AU - Kim, Hwan Soo

AU - Seo, Ju Hee

AU - Woo, Sung Il

AU - Kim, Hyung Young

AU - Shin, Youn Ho

AU - Lee, Ju Suk

AU - Yoon, Jisun

AU - Jung, Sungsu

AU - Han, Minkyu

AU - Eom, Eunjin

AU - Yu, Jinho

AU - Kim, Woo Kyung

AU - Lim, Dae Hyun

AU - Kim, Jin Tack

AU - Chang, Woo Sung

AU - Lee, Jeom Kyu

PY - 2019/3/15

Y1 - 2019/3/15

N2 - Background: Asthma is a syndrome composed of heterogeneous disease entities. Although it is agreed that proper asthma endo-typing and appropriate type-specific interventions are crucial in the management of asthma, little data are available regarding pediatric asthma. Methods: We designed a cluster-based, prospective, observational cohort study of asthmatic children in Korea (Korean childhood Asthma Study [KAS]). A total of 1000 Korean asthmatic children, aged from 5 to 15 years, will be enrolled at the allergy clinics of the 19 regional tertiary hospitals from August 2016 to December 2018. Physicians will verify the relevant histories of asthma and comorbid diseases, as well as airway lability from the results of spirometry and bronchial provocation tests. Questionnaires regarding subjects' baseline characteristics and their environment, self-rating of asthma control, and laboratory tests for allergy and airway inflammation will be collected at the time of enrollment. Follow-up data regarding asthma control, lung function, and environmental questionnaires will be collected at least every 6 months to assess outcome and exacerbation-related aggravating factors. In a subgroup of subjects, peak expiratory flow rate will be monitored by communication through a mobile application during the overall study period. Cluster analysis of the initial data will be used to classify Korean pediatric asthma patients into several clusters; the exacerbation and progression of asthma will be assessed and compared among these clusters. In a subgroup of patients, big data-based deep learning analysis will be applied to predict asthma exacerbation. Discussion: Based on the assumption that asthma is heterogeneous and each subject exhibits a different subset of risk factors for asthma exacerbation, as well as a different disease progression, the KAS aims to identify several asthma clusters and their essential determinants, which are more suitable for Korean asthmatic children. Thereafter we may suggest cluster-specific strategies by focusing on subjects' personalized aggravating factors during each exacerbation episode and by focusing on disease progression. The KAS will provide a good academic background with respect to each interventional strategy to achieve better asthma control and prognosis.

AB - Background: Asthma is a syndrome composed of heterogeneous disease entities. Although it is agreed that proper asthma endo-typing and appropriate type-specific interventions are crucial in the management of asthma, little data are available regarding pediatric asthma. Methods: We designed a cluster-based, prospective, observational cohort study of asthmatic children in Korea (Korean childhood Asthma Study [KAS]). A total of 1000 Korean asthmatic children, aged from 5 to 15 years, will be enrolled at the allergy clinics of the 19 regional tertiary hospitals from August 2016 to December 2018. Physicians will verify the relevant histories of asthma and comorbid diseases, as well as airway lability from the results of spirometry and bronchial provocation tests. Questionnaires regarding subjects' baseline characteristics and their environment, self-rating of asthma control, and laboratory tests for allergy and airway inflammation will be collected at the time of enrollment. Follow-up data regarding asthma control, lung function, and environmental questionnaires will be collected at least every 6 months to assess outcome and exacerbation-related aggravating factors. In a subgroup of subjects, peak expiratory flow rate will be monitored by communication through a mobile application during the overall study period. Cluster analysis of the initial data will be used to classify Korean pediatric asthma patients into several clusters; the exacerbation and progression of asthma will be assessed and compared among these clusters. In a subgroup of patients, big data-based deep learning analysis will be applied to predict asthma exacerbation. Discussion: Based on the assumption that asthma is heterogeneous and each subject exhibits a different subset of risk factors for asthma exacerbation, as well as a different disease progression, the KAS aims to identify several asthma clusters and their essential determinants, which are more suitable for Korean asthmatic children. Thereafter we may suggest cluster-specific strategies by focusing on subjects' personalized aggravating factors during each exacerbation episode and by focusing on disease progression. The KAS will provide a good academic background with respect to each interventional strategy to achieve better asthma control and prognosis.

KW - Asthma

KW - Child

KW - Cluster

KW - Cohort study

KW - Korea

KW - Prospective

UR - http://www.scopus.com/inward/record.url?scp=85062961958&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062961958&partnerID=8YFLogxK

U2 - 10.1186/s12890-019-0829-3

DO - 10.1186/s12890-019-0829-3

M3 - Article

C2 - 30876418

AN - SCOPUS:85062961958

VL - 19

JO - BMC Pulmonary Medicine

JF - BMC Pulmonary Medicine

SN - 1471-2466

IS - 1

M1 - 64

ER -