Individual FEV1 Trajectories Can Be Identified from a COPD Cohort

Jukka Koskela*, Milla Katajisto, Aleksi Kallio, Maritta Kilpeläinen, Ari Lindqvist, Tarja Laitinen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)425-430
Number of pages6
Issue number4
Publication statusPublished - 25 Jan 2016
MoE publication typeA1 Journal article-refereed


  • COPD
  • FEV development
  • FEV slope
  • hierarchical Bayesian model
  • rapid decline


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