Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

BackgroundThere is increasing interest in the earlier detection of, and intervention in, patients at highest risk of developing chronic obstructive pulmonary disease (COPD).AimsThe objective of this research was to develop and validate a risk prediction model for general practitioner (GP)-recorded diagnosis of COPD.MethodsWe used data from 239 Scottish GP practices; two-thirds were randomly allocated to a derivation cohort and the other third to a validation cohort. We included patients aged 35-74 years at the cohort entry date, and excluded patients with a recorded diagnosis of COPD prior to the entry date and with missing data on smoking status.ResultsThere were 480,903 patients in the derivation cohort and 247,755 in the validation cohort. The incidence of COPD in the total cohort was 5.53/1,000 patient-years of follow-up (95% confidence interval (CI), 5.46-5.60). In the derivation cohort, the COPD risk for ever- versus never-smokers was substantially higher in women (hazard ratio (HR)=9.61, 95% CI, 8.92-10.34) than in men (HR=6.72, 95% CI, 6.19-7.30). Other risk factors for both sexes were level of deprivation and a previously recorded asthma diagnosis. In the validation cohort, the model discriminated well between patients who did and those who did not develop COPD: area under the receiver operating characteristics curve=0.845 (95% CI, 0.840-0.850) for females and 0.832 (95% CI, 0.827-0.837) for males.ConclusionsWe have developed and validated the first risk prediction model for COPD, which has the major advantage of being populated entirely by routinely collected data and consequently may be used for clinical practice.

Original publication

DOI

10.1038/npjpcrm.2014.11

Type

Journal article

Journal

NPJ primary care respiratory medicine

Publication Date

05/2014

Volume

24

Addresses

1] Department of Family Medicine, CAPHRI School for Public Health and Primary Care, Maastricht University Medical Centre, Maastricht, The Netherlands [2] Allergy & Respiratory Research Group, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK.

Keywords

Humans, Pulmonary Disease, Chronic Obstructive, Models, Statistical, Risk Assessment, Risk Factors, Reproducibility of Results, Smoking, Age Factors, Sex Factors, Socioeconomic Factors, Adult, Aged, Female, Male, General Practice