1. Volume 122, Pages 1-11 (January 2017)
Non-persistence and non-adherence to long-acting COPD medication therapy: A retrospective cohort study based on a large German claims dataset 
Sabrina Mueller, Thomas Wilke, Benno Bechtel, Yogesh Suresh Punekar, Karen Mitzner, J. Christian Virchow 
Respiratory Medicine 
Volume 122, Pages 1-11 (January 2017)
DOI: /j.rmed
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2. Fig. 1
Methodology of analysis. The figure shows the definitions of the reference period, the index date and the observational follow-up period. It also shows that the main treatment adherence analysis was carried out for periods of therapy continuation only.
Respiratory Medicine  , 1-11DOI: ( /j.rmed )
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3. Fig. 2
Kaplan-Meier curves for the percentage of COPD treatment-naïve patients persistent with their long-acting COPD therapy during 12 months after therapy initiation. The figure shows the percentage of treatment-naïve COPD patients still persistent with their newly started long-acting COPD medication therapy over time in two different scenarios. Figure 2a presents the results of a patient-level persistence analysis. Here, a switch between long-acting agents without a gap of >90 days was not interpreted as therapy discontinuation in a patient. In the second analysis, carried out on an agent class-specific level (Figure 2b), a switch to other agents was interpreted as therapy discontinuation. NP was generally defined as an agent-specific treatment gap of >90 days, and a comparison between agent class-specific persistence was made by means of Log Rank tests. In this analysis, patients were observed who started a treatment with the specific agents; pre-treatment with other agents was possible.
Respiratory Medicine  , 1-11DOI: ( /j.rmed )
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4. Fig. 3
Multivariable analyses to identify factors associated with NP or NA. The figures show the results of the multivariable Cox regression (NP) and logistic regression (NA) analyses. In the Cox regression analysis addressing treatment-naïve patients only, time to discontinuation of therapy on a patient level was used as the dependent variable. In the logistic regression analysis addressing all observed COPD patients with at least two prescriptions of a long-acting COPD agent, NA as a dichotomous variable (NA if MPR<80% during periods of treatment continuation) was used as the dependent variable.
Respiratory Medicine  , 1-11DOI: ( /j.rmed )
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5. Fig. 3
Multivariable analyses to identify factors associated with NP or NA. The figures show the results of the multivariable Cox regression (NP) and logistic regression (NA) analyses. In the Cox regression analysis addressing treatment-naïve patients only, time to discontinuation of therapy on a patient level was used as the dependent variable. In the logistic regression analysis addressing all observed COPD patients with at least two prescriptions of a long-acting COPD agent, NA as a dichotomous variable (NA if MPR<80% during periods of treatment continuation) was used as the dependent variable.
Respiratory Medicine  , 1-11DOI: ( /j.rmed )
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6. Fig. 4
Multivariable analyses of COPD-related outcomes associated with NP or NA. The figures show the results of the multivariable logistic regression analyses using any prescription of acute COPD medication in the second 6 months of the observational period as the dependent variable. NP (4a) and NA (4b), among others, were used as independent variables.
Respiratory Medicine  , 1-11DOI: ( /j.rmed )
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7. Fig. 4
Multivariable analyses of COPD-related outcomes associated with NP or NA. The figures show the results of the multivariable logistic regression analyses using any prescription of acute COPD medication in the second 6 months of the observational period as the dependent variable. NP (4a) and NA (4b), among others, were used as independent variables.
Respiratory Medicine  , 1-11DOI: ( /j.rmed )
Copyright © 2016 Elsevier Ltd Terms and Conditions