Predicting COPD Exacerbations With Primary Care Data

Preventing the periodic exacerbations of chronic obstructive pulmonary disease (COPD) symptoms that can result in worsening quality of life and increased medical costs has long been a goal of COPD management. Although, data on predictive risk factors has been limited until now, researchers from the United Kingdom recently developed a model for predicting exacerbation risk using data obtainable from primary care.

The study, backed by the Respiratory Effectiveness Group, was a follow-up with patients identified by the Optimum Patient Care Research Database (OPCRD) as having COPD. The OPCRD is a respiratory-focused database containing anonymous data from general practices in the UK.

The study, published in the International Journal of Chronic Obstructive Pulmonary Disease, was divided into model-building and model-validation components. Patients eligible for inclusion in the model-building phase exhibited potentially important characteristics/variables, as selected by the authors, on or before March 12, 2013. These variables included having at least 1 recorded eosinophil count, being older than 40 years old, having been diagnostically coded for COPD, and a forced expiratory volume in 1 second/forced vital capacity (FEV₁/FVC) ratio <0.7 within 5 years of last eosinophil count (or “index date”). Patients were included in the model-validation phase if they had all of the above identified between March 2013 and February 2014.

From the total eligible population, patients were divided into 2 subpopulations: patients without concomitant asthma, and patients who completed validated assessment questionnaires and showed data on symptoms (COPD Assessment Test). Both subpopulations had similar baseline characteristics.

Number of exacerbations was recorded for the total population and both subpopulations one year after index date (or “outcome year”). Exacerbations were defined as either 1) unscheduled hospital admission or accident/emergency attendance for COPD or lower respiratory events, 2) an acute course of oral corticosteroids prescribed with evidence of respiratory review, or 3) antibiotics prescribed with evidence of respiratory review.

Approximately 20% of the total population had two or more exacerbations in the outcome year. Almost a quarter experienced one exacerbation.

Logistic regression was used to analyze the different characteristics or variables for importance. Frequency of exacerbations in patients the previous year was found to be the major predictor of risk for future exacerbation. Other significant predictive factors included patient age, eosinophilia in noncurrent smokers, asthma, ischemic heart disease, anxiety, depression, and gastroesophageal reflux disease.

“The number of exacerbations in the preceding year showed a strong exposure—response relationship, highlighting the importance of detailed information on patients’ exacerbation history,” authors wrote.

While there has been significant previous clinical research on predictive factors of COPD, this latest study sets itself apart by enrolling a population that better reflects patients with COPD treated in routine primary care.

The other unique aim of the study was to evaluate data that is routinely collected and readily available. And indeed, findings suggest that routine electronic medical record data from most general practitioner clinical systems can be useful in identifying COPD patients at risk of exacerbation. This could indicate a step towards reducing the rising disability and costs associated with COPD in the future.

“Our model could be used to profile patients with COPD, or to underpin decision support tools, in general practice,” authors wrote. “Such a model could help in earlier targeting of patients for review to optimize drug therapy and other interventions, with the aim of reducing hospital admissions, decline in lung function, and the morbidity and mortality associated with COPD.”