The impact of using different symptom-based exacerbation algorithms in patients with COPD

Abstract

Not all exacerbations are captured by reliance on healthcare contacts. Symptom-based exacerbation definitions have shown to provide more adequate measures of exacerbation rates, severity and duration. However, no consensus has been reached on what is the most useful method and algorithm to identify these events. This article provides an overview of the existing symptom-based definitions and tests the hypothesis that differences in exacerbation characteristics depend on the algorithms used. We systematically reviewed symptom-based methods and algorithms used in the literature, and quantified the impact of the four most referenced algorithms on exacerbation-related outcome using an existing chronic obstructive pulmonary disease (COPD) cohort (n = 137). We identified 51 studies meeting our criteria using 14 widely varying symptom algorithms to define onset, severity and recovery. The most (71%) frequently referenced algorithm (modified Anthonisen) identified an incidence rate of 1.7 episodes·patient-yr⁻¹ (95% CI 1.4-2.1), while for requiring only one major or two major symptoms this was 1.9 episodes·patient-yr⁻¹ (95% CI 1.6-2.3) and 1.5 episodes·patient-yr⁻¹ (95% CI 0.6-1.0), respectively. Studies were generally lacking methods to enhance validity and accuracy of symptom recording. This review revealed large inconsistencies in definitions, methods and accuracy to define symptom-based COPD exacerbations. We demonstrated that minor changes in symptom criteria substantially affect incidence rates, clustering type and classification of exacerbations.