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Prediction models for exacerbations in different COPD patient populations : Comparing results of five large data sources

Hoogendoorn, Martine; Feenstra, Talitha L.; Boland, Melinde; Briggs, Andrew H.; Borg, Sixten LU ; Jansson, Sven Arne; Risebrough, Nancy A.; Slejko, Julia F. and Pmhrutten-van Mölken, Maureen P.M.H. (2017) In International Journal of COPD 12. p.3183-3194
Abstract

Background and objectives: Exacerbations are important outcomes in COPD both from a clinical and an economic perspective. Most studies investigating predictors of exacerbations were performed in COPD patients participating in pharmacological clinical trials who usually have moderate to severe airflow obstruction. This study was aimed to investigate whether predictors of COPD exacerbations depend on the COPD population studied. Methods: A network of COPD health economic modelers used data from five COPD data sources - two population-based studies (COPDGene® and The Obstructive Lung Disease in Norrbotten), one primary care study (RECODE), and two studies in secondary care (Evaluation of COPD Longitudinally to Identify Predictive Surrogate... (More)

Background and objectives: Exacerbations are important outcomes in COPD both from a clinical and an economic perspective. Most studies investigating predictors of exacerbations were performed in COPD patients participating in pharmacological clinical trials who usually have moderate to severe airflow obstruction. This study was aimed to investigate whether predictors of COPD exacerbations depend on the COPD population studied. Methods: A network of COPD health economic modelers used data from five COPD data sources - two population-based studies (COPDGene® and The Obstructive Lung Disease in Norrbotten), one primary care study (RECODE), and two studies in secondary care (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoint and UPLIFT) - to estimate and validate several prediction models for total and severe exacerbations (= hospitalization). The models differed in terms of predictors (depending on availability) and type of model. Results: FEV1% predicted and previous exacerbations were significant predictors of total exacerbations in all five data sources. Disease-specific quality of life and gender were predictors in four out of four and three out of five data sources, respectively. Age was significant only in the two studies including secondary care patients. Other significant predictors of total exacerbations available in one database were: presence of cough and wheeze, pack-years, 6-min walking distance, inhaled corticosteroid use, and oxygen saturation. Predictors of severe exacerbations were in general the same as for total exacerbations, but in addition low body mass index, cardiovascular disease, and emphysema were significant predictors of hospitalization for an exacerbation in secondary care patients. Conclusions: FEV1% predicted, previous exacerbations, and disease-specific quality of life were predictors of exacerbations in patients regardless of their COPD severity, while age, low body mass index, cardiovascular disease, and emphysema seem to be predictors in secondary care patients only.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
COPD, Exacerbations, Hospitalizations, Modeling, Validation
in
International Journal of COPD
volume
12
pages
12 pages
publisher
Dove Press
external identifiers
  • scopus:85032813327
  • wos:000414221900001
ISSN
1176-9106
DOI
10.2147/COPD.S142378
language
English
LU publication?
yes
id
360aab48-84c1-41a1-8ec6-ac447a584274
date added to LUP
2017-11-22 13:20:21
date last changed
2018-01-16 13:26:19
@article{360aab48-84c1-41a1-8ec6-ac447a584274,
  abstract     = {<p>Background and objectives: Exacerbations are important outcomes in COPD both from a clinical and an economic perspective. Most studies investigating predictors of exacerbations were performed in COPD patients participating in pharmacological clinical trials who usually have moderate to severe airflow obstruction. This study was aimed to investigate whether predictors of COPD exacerbations depend on the COPD population studied. Methods: A network of COPD health economic modelers used data from five COPD data sources - two population-based studies (COPDGene® and The Obstructive Lung Disease in Norrbotten), one primary care study (RECODE), and two studies in secondary care (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoint and UPLIFT) - to estimate and validate several prediction models for total and severe exacerbations (= hospitalization). The models differed in terms of predictors (depending on availability) and type of model. Results: FEV<sub>1</sub>% predicted and previous exacerbations were significant predictors of total exacerbations in all five data sources. Disease-specific quality of life and gender were predictors in four out of four and three out of five data sources, respectively. Age was significant only in the two studies including secondary care patients. Other significant predictors of total exacerbations available in one database were: presence of cough and wheeze, pack-years, 6-min walking distance, inhaled corticosteroid use, and oxygen saturation. Predictors of severe exacerbations were in general the same as for total exacerbations, but in addition low body mass index, cardiovascular disease, and emphysema were significant predictors of hospitalization for an exacerbation in secondary care patients. Conclusions: FEV<sub>1</sub>% predicted, previous exacerbations, and disease-specific quality of life were predictors of exacerbations in patients regardless of their COPD severity, while age, low body mass index, cardiovascular disease, and emphysema seem to be predictors in secondary care patients only.</p>},
  author       = {Hoogendoorn, Martine and Feenstra, Talitha L. and Boland, Melinde and Briggs, Andrew H. and Borg, Sixten and Jansson, Sven Arne and Risebrough, Nancy A. and Slejko, Julia F. and Pmhrutten-van Mölken, Maureen P.M.H.},
  issn         = {1176-9106},
  keyword      = {COPD,Exacerbations,Hospitalizations,Modeling,Validation},
  language     = {eng},
  month        = {11},
  pages        = {3183--3194},
  publisher    = {Dove Press},
  series       = {International Journal of COPD},
  title        = {Prediction models for exacerbations in different COPD patient populations : Comparing results of five large data sources},
  url          = {http://dx.doi.org/10.2147/COPD.S142378},
  volume       = {12},
  year         = {2017},
}