Longitudinal asthma phenotypes by multi-trajectory analysis

Affiliations

¹ Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
² Department of Information Medicine, Big Data Research Center, Asan Medical Center, Seoul, Korea.

Duong Duc Pham et al. Allergy. 2024 May.

. 2024 May;79(5):1342-1345.

doi: 10.1111/all.15958. Epub 2023 Nov 29.

¹ Department of Allergy and Clinical Immunology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
² Department of Information Medicine, Big Data Research Center, Asan Medical Center, Seoul, Korea.

No abstract available

References

1. Kuruvilla ME, Lee FE, Lee GB. Understanding asthma phenotypes, endotypes, and mechanisms of disease. Clin Rev Allergy Immunol. 2019;56(2):219‐233. doi:10.1007/s12016-018-8712-1
1. Hastie AT, Mauger DT, Denlinger LC, et al. Mixed sputum granulocyte longitudinal impact on lung function in the severe asthma research program. Am J Respir Crit Care Med. 2021;203(7):882‐892. doi:10.1164/rccm.202009-3713OC
1. Park SY, Jung HW, Lee JM, et al. Novel trajectories for identifying asthma phenotypes: a longitudinal study in Korean asthma cohort, COREA. J Allergy Clin Immunol Pract. 2019;7(6):1850‐1857.e4. doi:10.1016/j.jaip.2019.02.011
1. Nagin DS, Jones BL, Passos VL, Tremblay RE. Group‐based multi‐trajectory modeling. Stat Methods Med Res. 2018;27(7):2015‐2023. doi:10.1177/0962280216673085
1. Magrini A. Assessment of agricultural sustainability in European Union countries: a group‐based multivariate trajectory approach. Asta‐Adv Stat Anal. 2022;106(3):525‐526. doi:10.1007/s10182-022-00438-8