Background: Unbiased cluster analysis has identified several asthma phenotypes. However, these phenotypes did not consistently predict disease prognosis and reflect temporal variability in airway inflammation. Objective: We aimed to identify longitudinal trajectories in terms of pulmonary function parameters and investigated whether the trajectories are associated with prognosis. Methods: Data were extracted from the Cohort for Reality and Evolution of Adult Asthma in Korea (COREA). Three-year pulmonary function test results were used to apply finite mixture models for group-based trajectory in 486 patients with eligible data set. Results: Two main sets of longitudinal trajectories were identified in terms of FEV1% predicted, and FEV1 variability. In the 4 trajectories determined with FEV1% predicted, the pulmonary function showed a consistent course in 4 stratified levels during 3 years of follow-up, which was associated with unexpected hospital visits and the use of steroid bursts due to exacerbation. The variability in pulmonary function showed 3 different patterns, and we found that higher blood and sputum eosinophil levels were associated with the higher variability in pulmonary function and more exacerbations. Conclusions: Trajectory analysis is a novel method that provides longitudinal asthma phenotypes and aids in prediction of future risk of exacerbation. Further analysis is needed to validate the usefulness of these trajectories in an independent population.
|Journal||Journal of Allergy and Clinical Immunology: In Practice|
|Publication status||Published - 2019 Jul 1|
Bibliographical noteFunding Information:
This study was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare,Republic of Korea (grant no. HC15C1335). This study was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare,Republic of Korea (grant no. HC15C1335). We thank the members of the study centers for participating in this study. The COREA Study Group includes the following investigators: Tae-Bum Kim, Woo-Jung Song, Hyouk-Soo Kwon, and You Sook Cho (University of Ulsan, Seoul, Korea); Sae-Hoon Kim (Bundang Seoul National University, Seongnam, Korea); Byoung Whui Choi and Jae-Woo Jung (Chung-Ang University, Seoul, Korea); Young-Joo Cho and Min-Hye Kim (Ewha Womans University, Seoul, Korea); An-Soo Jang (Soonchunhyang University, Bucheon, Korea); Yoo Seob Shin (Ajou University, Suwon, Korea); Ji-Yong Moon (Hanyang University, Guri, Korea), Ho Joo Yoon (Hanyang University, Seoul, Korea), Jae-Woo Kwon (Kangwon National University, Chuncheon, Korea); Sang-Hoon Kim and So Young Park (Eulji University, Seoul, Korea); Taehoon Lee (University of Ulsan, Ulsan, Korea); Sujeong Kim (Kyungpook National University, Daegu, Korea); Chan Sun Park (Inje University, Haeundae Paik Hospital, Busan, Korea); Joo-Hee Kim (Hallym University, Sacred Heart Hospital, Anyang, Korea); Jeong-Hee Choi (Hallym University, Dongtan Sacred Heart Hospital, Hwaseong, Korea); Young-Hee Nam (Dong-A University, Busan, Korea); Sun-Young Yoon (University of Konkuk, Chungju, Korea); Hyun Jung Jin (Yeungnam University, Daegu, Korea); Min-Suk Yang (Seoul National University, Boramae Medical Center, Seoul, Korea); Jaechun Lee (Jeju National University, Jeju, Korea); Hye-Kyung Park (Pusan National University, Busan, Korea); Gyu Young Hur (Korea University, Seoul, Korea); Hee-Kyoo Kim (Kosin University, Busan, Korea); and Sang Ha Kim (Yonsei University, Wonju, Korea). This study was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare,Republic of Korea (grant no. HC15C1335).
All Science Journal Classification (ASJC) codes
- Immunology and Allergy