Assessing treatment effects of inhaled corticosteroids on medical expenses and exacerbations among COPD patients: longitudinal analysis of managed care claims.

Chronic obstructive pulmonary disease (COPD) is characterized by progressive airflow limitation and airway inflammation leading to a gradual loss in lung function (Global Initiative for Chronic Obstructive Lung Disease [GOLD] 2006). Acute exacerbations (i.e., sudden worsening of respiratory symptoms) are common for many COPD patients and are most often caused by respiratory tract infections (White, Gompertz, and Stockley 2003). These exacerbations are an important part of the morbidity, mortality, and disease progression. Patients with lower levels of lung function are more likely to experience more exacerbations, and frequent exacerbations may lead to reduced lung function (Seemungal et al. 2000; Calverley et al. 2005). Exacerbations are strongly related to increases in health care utilization, including inpatient admissions, emergency department visits, and use of rescue medications (Donaldson and Wedzicha 2006). Because airway inflammation is one aspect of COPD, anti-inflammatory agents such as inhaled corticosteroids (ICS) may slow disease progression and prevent exacerbations. Current treatment guidelines recommend a stepwise increase in drug treatment depending on the disease severity (GOLD 2006). In particular, ICS treatment should be used to augment regular bronchodilator treatment for patients with advanced disease and repeated exacerbations. However, unlike the use of ICS in asthma treatment, the evidence for ICS efficacy is mixed for COPD treatment (Calverley 2004). In six randomized clinical studies in which COPD patients were followed for more than 12 months, ICS treatment was associated with a 4–26 percent reduction in exacerbation events defined by either respiratory-related hospitalizations, emergency department visits, worsening of respiratory symptoms, or their combination (Vestbo et al. 1999; Burge et al. 2000; Lung Health Study Research Group [LHSRG] 2000; Szafranski et al. 2003; Calverley, Pauwels et al. 2003; Calverley, Boonsawat et al. 2003). The most recent randomized clinical study (TORCH study) showed that the combination therapy of ICS and an inhaled bronchodilator reduced the risks of dying ( p=.052) and of moderate and severe exacerbations ( p<.001) during the 3-year follow-up (Calverley et al. 2007). Because severe exacerbations are uncommon in COPD patients, large studies with adequate follow-up periods are required to detect statistically and clinically significant effects of drug treatments. Pooled analyses using more than 4,000 COPD patients from randomized clinical trials of ICS showed that ICS reduced exacerbation rates by 24–33 percent compared with a placebo (Sin et al. 2003; Gartlehner et al. 2006). On the other hand, observational studies using more than 4,000 COPD patients find no preventive effects associated with ICS (Bourbeau et al. 2003; Fan et al. 2003; de Melo, Ernst, and Suissa 2004; Suissa 2004) even though potential misclassification of ICS exposure status was carefully addressed by using either a time-dependent approach or a nested case–control study design. One possible explanation for these mixed results may be the lack of a consistent definition of exacerbation. Because substantial individual variation occurs in exacerbation patterns, exacerbation episodes are operationally defined in various ways across studies, ranging from “mild exacerbation” defined by increased use of rescue therapy to “severe exacerbation” defined by respiratory conditions that require hospitalization (Calverley 2004; Pauwels et al. 2004). Other reasons for these mixed results may be related to individual factors that are not observed in claims data but that influence disease prognosis. Important unobserved characteristics that could bias the previous estimations include socioeconomic characteristics, smoking behavior, and chronic comorbid conditions (Burney et al. 2003; Spencer et al. 2004; Mannino et al. 2006). In cross-sectional data analysis, omission of important factors from the regression model will lead to biased estimation. However, in longitudinal or panel data analysis, an individual has multiple observations of both exposure status and outcomes (Frees 2004). Each individual contributes time before drug exposure to the control group and time after drug exposure to the treatment group. Because each individual is his or her own control, potential bias due to person-specific omitted variables that do not change over time (e.g., education, historical health behaviors, and underlying health status) can be eliminated. With at least two observations per person, the treatment effect can be observed by measuring changes before and after the treatment (e.g., as a pre- and post-paired comparison), and thus time-invariant variables disappear by subtracting one from the other. One statistical approach to account for multiple observations per individual is called the “fixed-effects” model (Allison 2005). The model can be expressed as: (1) The notation i refers to different persons and t refers to different points in time; the term Yit is an outcome of interest, Xit is a main exposure of interest, αi is a dummy variable representing individual characteristics; Wit is a vector of time-variant variables of interest; and ɛit is a random error. In this model, because individual variations are considered fixed and are captured by the fixed-effect parameter, αi, omitted time-invariant variables are accounted for without measuring them. Wit, factors that change over time (e.g., disease symptoms) must be adjusted with common regression approaches, and unobserved time-varying factors may still cause bias. In previous observational studies using claims data, limited information was available to measure and adjust for the effects of important predictors of prognosis of COPD, such as smoking history or chronic conditions (Sin and Tu 2001; Bourbeau et al. 2003; Suissa 2004). In this study, however, we address the potential bias that is likely to exist in the cross-sectional studies by using monthly data from a managed care claims database to obtain repeated measures over time for each individual. We use an individual-level, fixed-effects model to estimate the unbiased effects of adding ICS treatment on monthly medical expenses and likelihood of severe exacerbations among COPD patients who were initially under treatment with regular bronchodilators. We use parameter estimates from these two models to determine the incremental cost per severe exacerbation avoided.