Improved survival prediction from lung function data in a large population sample

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Improved survival prediction from lung function data in a large population sample. / Miller, M.R.; Pedersen, O.F.; Lange, P.; Vestbo, J.

I: Respiratory Medicine, Bind 103, Nr. 3, 2008, s. 442-448.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Miller, MR, Pedersen, OF, Lange, P & Vestbo, J 2008, 'Improved survival prediction from lung function data in a large population sample', Respiratory Medicine, bind 103, nr. 3, s. 442-448. https://doi.org/10.1016/j.rmed.2008.09.016

APA

Miller, M. R., Pedersen, O. F., Lange, P., & Vestbo, J. (2008). Improved survival prediction from lung function data in a large population sample. Respiratory Medicine, 103(3), 442-448. https://doi.org/10.1016/j.rmed.2008.09.016

Vancouver

Miller MR, Pedersen OF, Lange P, Vestbo J. Improved survival prediction from lung function data in a large population sample. Respiratory Medicine. 2008;103(3):442-448. https://doi.org/10.1016/j.rmed.2008.09.016

Author

Miller, M.R. ; Pedersen, O.F. ; Lange, P. ; Vestbo, J. / Improved survival prediction from lung function data in a large population sample. I: Respiratory Medicine. 2008 ; Bind 103, Nr. 3. s. 442-448.

Bibtex

@article{950fb480898e11df928f000ea68e967b,
title = "Improved survival prediction from lung function data in a large population sample",
abstract = "Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease mortality in the Copenhagen City Heart Study data. Cox regression models were derived for survival over 25 years in 13,900 subjects. Age on entry, sex, smoking status, body mass index, previous myocardial infarction and diabetes were putative predictors together with FEV1 either as raw data, standardised by powers of height (FEV1/ht(n)), as percent of predicted (FEV1PP) or as standardised residuals (FEV1SR). Quintiles of FEV1/ht(2) were better at predicting all, cause mortality in multivariate models than FEV1PP and FEV1SR, with the hazard ratio (HR) for the worst quintiles being 2.8, 2.0 and 2.1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP. In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method of expressing FEV1 impairment best reflects hazard for subsequent death. (C) 2008 Elsevier Ltd. All rights reserved Udgivelsesdato: 2009/3",
author = "M.R. Miller and O.F. Pedersen and P. Lange and J. Vestbo",
note = "Times Cited: 1ArticleEnglishMiller, M. RUniv Hosp Birmingham NHS Trust, Selly Oak Hosp, Dept Med, Raddlebarn Rd, Birmingham B29 6JD, W Midlands, EnglandCited References Count: 23416XVW B SAUNDERS CO LTD32 JAMESTOWN RD, LONDON NW1 7BY, ENGLANDLONDON",
year = "2008",
doi = "http://dx.doi.org/10.1016/j.rmed.2008.09.016",
language = "English",
volume = "103",
pages = "442--448",
journal = "Respiratory Medicine",
issn = "0954-6111",
publisher = "Elsevier",
number = "3",

}

RIS

TY - JOUR

T1 - Improved survival prediction from lung function data in a large population sample

AU - Miller, M.R.

AU - Pedersen, O.F.

AU - Lange, P.

AU - Vestbo, J.

N1 - Times Cited: 1ArticleEnglishMiller, M. RUniv Hosp Birmingham NHS Trust, Selly Oak Hosp, Dept Med, Raddlebarn Rd, Birmingham B29 6JD, W Midlands, EnglandCited References Count: 23416XVW B SAUNDERS CO LTD32 JAMESTOWN RD, LONDON NW1 7BY, ENGLANDLONDON

PY - 2008

Y1 - 2008

N2 - Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease mortality in the Copenhagen City Heart Study data. Cox regression models were derived for survival over 25 years in 13,900 subjects. Age on entry, sex, smoking status, body mass index, previous myocardial infarction and diabetes were putative predictors together with FEV1 either as raw data, standardised by powers of height (FEV1/ht(n)), as percent of predicted (FEV1PP) or as standardised residuals (FEV1SR). Quintiles of FEV1/ht(2) were better at predicting all, cause mortality in multivariate models than FEV1PP and FEV1SR, with the hazard ratio (HR) for the worst quintiles being 2.8, 2.0 and 2.1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP. In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method of expressing FEV1 impairment best reflects hazard for subsequent death. (C) 2008 Elsevier Ltd. All rights reserved Udgivelsesdato: 2009/3

AB - Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease mortality in the Copenhagen City Heart Study data. Cox regression models were derived for survival over 25 years in 13,900 subjects. Age on entry, sex, smoking status, body mass index, previous myocardial infarction and diabetes were putative predictors together with FEV1 either as raw data, standardised by powers of height (FEV1/ht(n)), as percent of predicted (FEV1PP) or as standardised residuals (FEV1SR). Quintiles of FEV1/ht(2) were better at predicting all, cause mortality in multivariate models than FEV1PP and FEV1SR, with the hazard ratio (HR) for the worst quintiles being 2.8, 2.0 and 2.1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP. In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method of expressing FEV1 impairment best reflects hazard for subsequent death. (C) 2008 Elsevier Ltd. All rights reserved Udgivelsesdato: 2009/3

U2 - http://dx.doi.org/10.1016/j.rmed.2008.09.016

DO - http://dx.doi.org/10.1016/j.rmed.2008.09.016

M3 - Journal article

VL - 103

SP - 442

EP - 448

JO - Respiratory Medicine

JF - Respiratory Medicine

SN - 0954-6111

IS - 3

ER -

ID: 20683468