Jukka Koskela1, Milla Katajisto1, Aleksi Kallio2, Maritta Kilpeläinen3, Ari Lindqvist1, Tarja Laitinen1,3. 1. a Clinical Research Unit for Pulmonary Diseases and Division of Pulmonology , Helsinki University Central Hospital , Helsinki , Finland. 2. b CSC- IT Center for Science Ltd., Department of Information and Computer Science, Aalto University , Helsinki Institute for Information Technology (HIIT) , Helsinki , Finland. 3. c Division of Medicine, Dept. of Pulmonary Diseases and Clinical Allergology , Turku University Hospital and University of Turku , Turku , Finland.
Abstract
OBJECTIVE: We aim to make use of clinical spirometry data in order to identify individual COPD-patients with divergent trajectories of lung function over time. STUDY DESIGN AND SETTING: Hospital-based COPD cohort (N = 607) was followed on average 4.6 years. Each patient had a mean of 8.4 spirometries available. We used a Hierarchical Bayesian Model (HBM) to identify the individuals presenting constant trends in lung function. RESULTS: At a probability level of 95%, one third of the patients (180/607) presented rapidly declining FEV1 (mean -78 ml/year, 95% CI -73 to -83 ml) compared to that in the rest of the patients (mean -26 ml/year, 95% CI -23 to -29 ml, p ≤ 2.2 × 10(-16)). Constant improvement of FEV1 was very rare. The rapid decliners more frequently suffered from exacerbations measured by various outcome markers. CONCLUSION: Clinical data of unique patients can be utilized to identify diverging trajectories of FEV1 with a high probability. Frequent exacerbations were more prevalent in FEV1-decliners than in the rest of the patients. The result confirmed previously reported association between FEV1 decline and exacerbation rate and further suggested that in clinical practice HBM could improve the identification of high-risk individuals at early stages of the disease.
OBJECTIVE: We aim to make use of clinical spirometry data in order to identify individual COPD-patients with divergent trajectories of lung function over time. STUDY DESIGN AND SETTING: Hospital-based COPD cohort (N = 607) was followed on average 4.6 years. Each patient had a mean of 8.4 spirometries available. We used a Hierarchical Bayesian Model (HBM) to identify the individuals presenting constant trends in lung function. RESULTS: At a probability level of 95%, one third of the patients (180/607) presented rapidly declining FEV1 (mean -78 ml/year, 95% CI -73 to -83 ml) compared to that in the rest of the patients (mean -26 ml/year, 95% CI -23 to -29 ml, p ≤ 2.2 × 10(-16)). Constant improvement of FEV1 was very rare. The rapid decliners more frequently suffered from exacerbations measured by various outcome markers. CONCLUSION: Clinical data of unique patients can be utilized to identify diverging trajectories of FEV1 with a high probability. Frequent exacerbations were more prevalent in FEV1-decliners than in the rest of the patients. The result confirmed previously reported association between FEV1 decline and exacerbation rate and further suggested that in clinical practice HBM could improve the identification of high-risk individuals at early stages of the disease.
Authors: Anne Lindberg; Robert Linder; Helena Backman; Jonas Eriksson Ström; Andreas Frølich; Ulf Nilsson; Eva Rönmark; Viktor Johansson Strandkvist; Annelie F Behndig; Anders Blomberg Journal: Eur Clin Respir J Date: 2017-12-17
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Authors: Hannah R Whittaker; Jeanne M Pimenta; Deborah Jarvis; Steven J Kiddle; Jennifer K Quint Journal: Int J Chron Obstruct Pulmon Dis Date: 2020-11-25
Authors: Jonas Eriksson Ström; Jamshid Pourazar; Robert Linder; Anders Blomberg; Anne Lindberg; Anders Bucht; Annelie F Behndig Journal: Respir Res Date: 2020-12-14