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Study Develops Predictive Model to Assess COPD Severe Exacerbations

Alison Rodriguez
Researchers recently aimed to develop a predictive model to identify patients at risk of developing severe COPD exacerbations, finding that for every 2 patients identified to be at risk of severe flare-up of disease, 1 patient may experience a severe exacerbation.
It is common for patients with chronic obstructive pulmonary disease (COPD) to experience severe exacerbations that lead to hospitalization from accelerated lung function decline and the reduction of patients’ quality of life. Researchers recently aimed to develop a predictive model to identify patients at risk of developing severe COPD exacerbations, finding that for every 2 patients identified to be at risk of severe exacerbation, 1 patient may experience a severe exacerbation.

“Exacerbations accelerate the decline in lung function and lower quality of life. Exacerbation frequency is also considered to be an indicator of COPD stage, with higher frequency of exacerbations indicating more severe disease,” explained the authors. “Correspondingly, exacerbations impose a significant economic burden by accounting for 50%–75% of the total COPD burden.”

The study developed the predictive model by using a retrospective cohort of COPD patients, ages 55 to 89 years old, who were identified between July 1, 2010 and June 30, 2013 using Humana’s claims data. The study used the 12 months postdiagnosis as the baseline period, while the prediction period covered months 12 through 24.

Using the patient data, the researchers compared patients with severe exacerbations to those without in the prediction period in order to identify characteristics associated with the severe exacerbations.

Of the 45,722 patients included in the study, 5317 had severe exacerbations during the prediction period. Those with severe exacerbations were found to have significantly higher comorbidity burden, use of respiratory medications, and tobacco-cessation counseling, when compared to those without severe exacerbations during the baseline period.

In addition, the predictive model considered 29 variables that were significantly linked to severe exacerbations, finding that the strongest predictors were prior severe exacerbations and higher Deyo-Charlson comorbidity score.

The researchers used a final model of their predictive model in order to analyze the data. The model had a sensitivity of 17%, specificity of 98%, positive predictive value of 48%, and negative predictive value of 90%.

“Of every two patients identified by the model to be at risk of severe exacerbations, one may have a severe exacerbation. This model may provide an efficient method of using claims data to identify patients with COPD who are at risk of future severe exacerbations,” concluded the study. “Once at-risk patients are identified, targeted and timely support may be provided to improve lung function and quality of life and reduce risk of exacerbations.”

The study suggested the need for disease management, education programs, such as pharmacologic interventions, transition-of-care programs, and smoking-cessation counseling, to be implemented in order to prevent future exacerbations.

Reference

Annavarapu S, Goldfarb S, Gelb M, Moretz C, Renda A, Kaila S. Development and validation of a predictive model to identify patients at risk of severe COPD exacerbations using administrative claims data. [published online July 11, 2018]. Int J Chron Obstruct Pulmon Dis.

Doi: 10.2147/COPD.S155773

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