Improving COPD Outcomes: Using Real-World Data to Analyze Treatment Effectiveness, Safety, and Adherence

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Chronic obstructive pulmonary disease (COPD) is one of the leading causes of mortality worldwide and is associated with symptoms of dyspnea, cough, and reduced functional capacity. While numerous scientific advances have been made to improve the care of patients with COPD, considerable uncertainty remains about optimal management. For some questions, clinical trial data have been conflicting; for others, clinical trials have not been feasible. Uncertainty in the management of COPD has been further compounded by questions of generalizability in randomized controlled trials. Studies have demonstrated that the majority of patients with COPD would not qualify for such trials because of their strict inclusion criteria based on characteristics such as age, comorbidities, smoking status, and spirometry. Conflicting or absent clinical trial data and questions of generalizability prompt the need for “real-world” studies of patients treated for COPD in routine clinical practice. Given poor adherence to inhaler therapy outside of clinical trials, studies are also needed to understand why patients discontinue therapy. Improving the care of patients with COPD requires identifying which therapies are most likely to be safe and effective in routine clinical practice and developing interventions to target those least likely to be adherent. The ultimate goal of the proposed research is to supplement existing data from randomized controlled trials with pharmacoepidemiologic studies to refine treatment strategies in COPD. The proposed research will accomplish this goal by using large, longitudinal healthcare databases to pursue three specific aims: (1) To validate claims-based definitions of COPD exacerbations; (2) To compare the effectiveness and safety of therapies in the management of COPD, focusing on four areas of ongoing clinical uncertainty; and (3) To develop a clinical prediction rule of inhaler adherence that incorporates key variables across several domains, from out-of-pocket costs and insurance benefit design to therapy-related features (e.g., frequency of dosing) and COPD disease severity. By addressing treatment effectiveness, safety, and adherence among patients treated in routine clinical practice, the proposed research will glean novel insights into the management of COPD, particularly for patients who are underrepresented in clinical trials, including older adults, racial and ethnic minorities, women, and those with complex co-morbidities. Dr. Feldman has a unique background as a practicing pulmonologist with public health experience. This K08 proposes an education plan that will help him build new skills in pharmacoepidemiology. He will receive mentorship from Dr. Sebastian Schneeweiss, a pioneer in pharmacoepidemiology, and Dr. Aaron Kesselheim, a leading authority on pharmaceutical policy and use, and will rely on a team of scientific advisors with expertise in machine learning (Dr. Joshua Lin), data management (Dr. Shirley Wang), biostatistics (Dr. Robert Glynn), geriatric prescribing (Dr. Jerry Avorn), and COPD epidemiology (Dr. Edwin Silverman). This award will provide Dr. Feldman with the tools needed to become an independent investigator.