Development and validation of a model to predict the 10-year risk of general practitioner-recorded COPD

There is increasing interest in the earlier detection of, and intervention in, patients at highest risk of developing chronic obstructive pulmonary disease (COPD). The objective of this research was to develop and validate a risk prediction model for general practitioner (GP)-recorded diagnosis of COPD. We 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. There 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. We 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. A model to assess the risk of developing chronic obstructive pulmonary disease (COPD) has been developed. Lung diseases such as emphysema and chronic bronchitis, collectively known as COPD, are responsible for 6% of all deaths annually worldwide. Smoking is a key risk factor but there is no tool available to doctors that accurately predicts who will develop the disease. Now, Daniel Kotz at Maastricht University Medical Centre, together with an international team of researchers, has developed the first prediction model for assessing COPD risk in patients. Using data from 10 years' worth of general practice records following 728,658 patients in Scotland, the model determined those most likely to develop COPD with 85% accuracy. Female smokers were most at risk, with social deprivation and a history of asthma also important risk factors.