Development and validation of a multivariable mortality risk prediction model for COPD in primary care

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作者
Syed A. Shah
Bright I. Nwaru
Aziz Sheikh
Colin R. Simpson
Daniel Kotz
机构
[1] Usher Institute,
[2] The University of Edinburgh,undefined
[3] Krefting Research Centre,undefined
[4] Institute of Medicine,undefined
[5] University of Gothenburg,undefined
[6] Wallenberg Centre for Molecular and Translational Medicine,undefined
[7] Institute of Medicine,undefined
[8] University of Gothenburg,undefined
[9] School of Health,undefined
[10] Wellington Faculty of Health,undefined
[11] Victoria University of Wellington,undefined
[12] Institute of General Practice,undefined
[13] Addiction Research and Clinical Epidemiology Unit,undefined
[14] Centre for Health and Society (CHS),undefined
[15] Medical Faculty of the Heinrich-Heine-University Düsseldorf,undefined
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摘要
Risk stratification of chronic obstructive pulmonary disease (COPD) patients is important to enable targeted management. Existing disease severity classification systems, such as GOLD staging, do not take co-morbidities into account despite their high prevalence in COPD patients. We sought to develop and validate a prognostic model to predict 10-year mortality in patients with diagnosed COPD. We constructed a longitudinal cohort of 37,485 COPD patients (149,196 person-years) from a UK-wide primary care database. The risk factors included in the model pertained to demographic and behavioural characteristics, co-morbidities, and COPD severity. The outcome of interest was all-cause mortality. We fitted an extended Cox-regression model to estimate hazard ratios (HR) with 95% confidence intervals (CI), used machine learning-based data modelling approaches including k-fold cross-validation to validate the prognostic model, and assessed model fitting and discrimination. The inter-quartile ranges of the three metrics on the validation set suggested good performance: 0.90–1.06 for model fit, 0.80–0.83 for Harrel’s c-index, and 0.40–0.46 for Royston and Saurebrei’s RD2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_D^2$$\end{document} with a strong overlap of these metrics on the training dataset. According to the validated prognostic model, the two most important risk factors of mortality were heart failure (HR 1.92; 95% CI 1.87–1.96) and current smoking (HR 1.68; 95% CI 1.66–1.71). We have developed and validated a national, population-based prognostic model to predict 10-year mortality of patients diagnosed with COPD. This model could be used to detect high-risk patients and modify risk factors such as optimising heart failure management and offering effective smoking cessation interventions.
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