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External Validation of a COPD Risk Measure in a Commercial and Medicare Population: The COPD Treatment Ratio

Overview
Specialties Pharmacology
Pharmacy
Date 2018 Dec 28
PMID 30589629
Citations 6
Authors
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Abstract

Background: Chronic obstructive pulmonary disease (COPD) exacerbations can accelerate disease progression and lead to higher health care costs. To improve patient survival and reduce cost, risk assessment measures should be developed to identify patients at risk for exacerbations and prevent future exacerbations.

Objectives: To (a) externally validate the COPD treatment ratio (CTR) as a measure of COPD exacerbation risk based on predictive models previously tested and (b) assess the measure's capability to assess risk using only pharmacy claims for use in Medicare Part D programs.

Methods: This was a retrospective observational study conducted using the Humana research datasets. Separate assessments were performed using pharmacy-only models that excluded risk factors derived from medical claims. Patients were aged ≥ 40 years, with ≥ 1 inpatient hospitalization or ≥ 2 physician's office, emergency department, or urgent care visits with a COPD diagnosis. Using logistic regression models, risk factors (age, exacerbation history, COPD and concomitant medication use, and comorbidities) were assessed during the baseline period (year 1) and were used to predict the risk of exacerbation during year 2. Continuous and dichotomized CTRs were analyzed. A cut-point of 0.3 was initially used for dichotomizing CTR, and subsequently receiver operating characteristics (ROC) analysis was used to determine the optimal cut-point for CTR.

Results: A total of 92,496 patients were identified, the majority of which (96.2%) were Medicare members with a mean age of 69 years. During the baseline period, 14.0% and 11.2% of patients had ≥ 1 moderate or severe exacerbation, respectively. Overall, the CTR performed well in predicting future COPD exacerbations, especially severe exacerbations. ROC analysis suggested that 0.7 was the optimal cut-point for dichotomizing CTR. Patients with a CTR ≥ 0.7 had a 7.9% (OR = 0.921; 95% CI = 0.852-0.995) lower risk of a severe exacerbation, compared with those with a CTR < 0.7. Stronger effects were seen in pharmacy-only models, with patients 17% less likely to experience a severe exacerbation with a CTR ≥ 0.7 compared with patients with a CTR < 0.7.

Conclusions: This study validated the use of CTR as a modifiable measure of risk of COPD exacerbation in a large commercial and Medicare population and remained a robust predictor when pharmacy-only claims data were available. A CTR of ≥ 0.7 may be a useful target to help reduce the risk of severe exacerbations, and its use by payer or quality organizations has the potential to improve COPD management.

Disclosures: This study was funded by GlaxoSmithKline (GSK; study number HO-15-16651). GSK had a role in the study design, collection, analysis, and interpretation of data and in the writing of the study report but did not place any restrictions on access to the data or on the statements made in the manuscript. The authors were in full editorial control of publication target journal and content and conclusions, accepted full responsibility for final approval of a manuscript describing this GSK-sponsored research, and had final responsibility for the decision to submit for publication. Stanford and Lau are employees of GSK and hold GSK stocks/shares. Li and Stemkowski are employees of Comprehensive Health Insights, which was contracted to conduct the study but did not receive funding for manuscript development. This manuscript was presented in part at the American Thoracic Society 2017 International Conference; May 19-24, 2017; Washington, DC.

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References
1.
Hurst J, Vestbo J, Anzueto A, Locantore N, Mullerova H, Tal-Singer R . Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med. 2010; 363(12):1128-38. DOI: 10.1056/NEJMoa0909883. View

2.
Santibanez M, Garrastazu R, Ruiz-Nunez M, Helguera J, Arenal S, Bonnardeux C . Predictors of Hospitalized Exacerbations and Mortality in Chronic Obstructive Pulmonary Disease. PLoS One. 2016; 11(6):e0158727. PMC: 4928940. DOI: 10.1371/journal.pone.0158727. View

3.
Garcia-Aymerich J, Farrero E, Felez M, Izquierdo J, Marrades R, Anto J . Risk factors of readmission to hospital for a COPD exacerbation: a prospective study. Thorax. 2003; 58(2):100-5. PMC: 1746561. DOI: 10.1136/thorax.58.2.100. View

4.
Brusse-Keizer M, van der Palen J, van der Valk P, Hendrix R, Kerstjens H . Clinical predictors of exacerbation frequency in chronic obstructive pulmonary disease. Clin Respir J. 2010; 5(4):227-34. DOI: 10.1111/j.1752-699X.2010.00234.x. View

5.
Motegi T, Jones R, Ishii T, Hattori K, Kusunoki Y, Furutate R . A comparison of three multidimensional indices of COPD severity as predictors of future exacerbations. Int J Chron Obstruct Pulmon Dis. 2013; 8:259-71. PMC: 3674751. DOI: 10.2147/COPD.S42769. View