Randomized Controlled Trials of Pharmacological Treatments to Prevent COPD Exacerbations

Applicability to Real-Life Patients

Laurie Pahus; Pierre-Régis Burgel; Nicolas Roche; Jean-Louis Paillasseur; Pascal Chanez; on behalf of Initiatives BPCO scientific committee

Disclosures

BMC Pulm Med. 2019;19(127) 

In This Article

Abstract and Introduction

Abstract

Background: In patients with chronic obstructive pulmonary disease, all efforts should be made to prevent exacerbations because each event modifies the trajectory of the disease. Treatment recommendations are mostly built on results from randomized controlled trials (RCTs) whose methodology ensure internal validity. However, their relevance may be compromised by the lack of generalizability, due to poor representability of study populations compared to real-life patients.

In order to delimit to whom the results of studies on current and future treatments apply, we sought to identify and characterize the fraction of COPD population that would be eligible for inclusion into RCTs aiming at decreasing exacerbation risk.

Methods: We used the Initiatives-BPCO database, a French cohort of 1309 real-life COPD patients monitored in academic centers. We identified industry-sponsored phase III and IV trials that enrolled more than 500 patients, lasted at least one year and used exacerbations related endpoints. Eligibility criteria were extracted from each trial and applied to the patients.

Results: The eligibility criteria of 16 RCTs were applied to the 1309 patients. The most discriminating eligibility criteria were FEV1, minimum exacerbation rate in the previous year and smoking history, responsible for the exclusion of 39.9, 36.7 and 16.8% of patients, respectively. Altogether, 2.3 to 46.7% of our patients would have satisfied all eligibility criteria.

Conclusion: These analyses confirm that an important gap exists between real-life patients and clinical trials populations in COPD, which limits the relevance of results and therefore should be considered when grading levels of evidence and designing future studies.

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