A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Individual FEV1 Trajectories Can Be Identified from a COPD Cohort
Tekijät: Koskela J, Katajisto M, Kallio A, Kilpelainen M, Lindqvist A, Laitinen T
Kustantaja: TAYLOR & FRANCIS INC
Julkaisuvuosi: 2016
Journal: COPD: Journal of Chronic Obstructive Pulmonary Disease
Tietokannassa oleva lehden nimi: COPD-JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE
Lehden akronyymi: COPD
Vuosikerta: 13
Numero: 4
Aloitussivu: 425
Lopetussivu: 430
Sivujen määrä: 6
ISSN: 1541-2555
eISSN: 1541-2563
DOI: https://doi.org/10.3109/15412555.2015.1043423
Tiivistelmä
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 x 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 x 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.
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