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Individualized prediction of lung-function decline in chronic obstructive pulmonary disease

Zafari, Zafar; Sin, Don D.; Postma, Dirkje S.; Löfdahl, Claes Göran LU ; Vonk, Judith; Bryan, Stirling; Lam, Stephen; Tammemagi, C. Martin; Khakban, Rahman and Man, S. F Paul, et al. (2016) In Canadian Medical Association Journal 188(14). p.1004-1010
Abstract

Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline... (More)

Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being -124 to -15 mL/yr for smokers and -83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD.

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Canadian Medical Association Journal
volume
188
issue
14
pages
7 pages
publisher
Cma-Canadian Medical Assoc
external identifiers
  • scopus:84990062823
  • wos:000385652400016
ISSN
0820-3946
DOI
10.1503/cmaj.151483
language
English
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yes
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d96616eb-bf28-4654-bff3-f5189d176503
date added to LUP
2016-10-21 09:03:12
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2017-10-22 05:20:48
@article{d96616eb-bf28-4654-bff3-f5189d176503,
  abstract     = {<p>Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being -124 to -15 mL/yr for smokers and -83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD.</p>},
  author       = {Zafari, Zafar and Sin, Don D. and Postma, Dirkje S. and Löfdahl, Claes Göran and Vonk, Judith and Bryan, Stirling and Lam, Stephen and Tammemagi, C. Martin and Khakban, Rahman and Man, S. F Paul and Tashkin, Donald and Wise, Robert A. and Connett, John E. and McManus, Bruce and Ng, Raymond and Hollander, Zsuszanna and Sadatsafavi, Mohsen},
  issn         = {0820-3946},
  language     = {eng},
  month        = {10},
  number       = {14},
  pages        = {1004--1010},
  publisher    = {Cma-Canadian Medical Assoc},
  series       = {Canadian Medical Association Journal},
  title        = {Individualized prediction of lung-function decline in chronic obstructive pulmonary disease},
  url          = {http://dx.doi.org/10.1503/cmaj.151483},
  volume       = {188},
  year         = {2016},
}