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Statin adherence improves with age and subsequent treatment sequences: A retrospective cohort study using Proportion of Days Covered (PDC)

A. Tichopád, G. Donin, J. Žigmond, J. Ráfl, M. Rybář, P. Šedová, M. Vrablík

. 2025 ; 20 (6) : e0325293. [pub] 20250625

Language English Country United States

Document type Journal Article

BACKGROUND: Dyslipidaemia is a key risk factor for atherosclerotic cardiovascular disease (ASCVD), necessitating effective statin therapy. Despite statins' proven safety and efficacy, adherence remains suboptimal, with significant gaps between clinical practice and guideline recommendations. METHODS: This retrospective cohort study analysed anonymized health administrative claims data from six employee health funds in the Czech Republic, covering approximately 40% of the insured population from January 1, 2017, to December 31, 2020. We identified statin-incident as well as prevalent cohort of patients. Adherence to statin therapy was assessed using the proportion of days covered (PDC) metric, with factors such as age, gender, sequence of use, and treatment intensity considered as modifiers. RESULTS: Among the statin-prevalent cohort (SP, n = 890,180), 83.5% achieved a PDC ≥ 50%, and 61.0% reached a PDC ≥ 80%. In the statin-incident cohort (SI, n = 287,871), a clear trend of increasing adherence with age and medication sequence was observed: in adults aged 18-39 median PDC rose from 84.1% (IQR: 57-100) in the first to 94.7% (IQR: 75.6-100) in the third sequence; in those aged 80 + median PDC rose from 95.0% (IQR: 68.9-100) in the first to 100% (IQR: 78.3-100) in the third sequence. Logistic regression identified age (OR=1.011 per year), female gender (OR=0.896), high-intensity treatment (OR=0.975), and second (OR=1.267) or later treatment sequences (OR=1.704) as significant predictors of adherence (all p < 0.001). CONCLUSION: Adherence to statin therapy improves with subsequent treatment sequences and age. These findings highlight the need for targeted interventions to enhance adherence, particularly among younger patients. The PDC metric is recommended for integration into clinical practice to monitor and improve medication adherence.

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$a BACKGROUND: Dyslipidaemia is a key risk factor for atherosclerotic cardiovascular disease (ASCVD), necessitating effective statin therapy. Despite statins' proven safety and efficacy, adherence remains suboptimal, with significant gaps between clinical practice and guideline recommendations. METHODS: This retrospective cohort study analysed anonymized health administrative claims data from six employee health funds in the Czech Republic, covering approximately 40% of the insured population from January 1, 2017, to December 31, 2020. We identified statin-incident as well as prevalent cohort of patients. Adherence to statin therapy was assessed using the proportion of days covered (PDC) metric, with factors such as age, gender, sequence of use, and treatment intensity considered as modifiers. RESULTS: Among the statin-prevalent cohort (SP, n = 890,180), 83.5% achieved a PDC ≥ 50%, and 61.0% reached a PDC ≥ 80%. In the statin-incident cohort (SI, n = 287,871), a clear trend of increasing adherence with age and medication sequence was observed: in adults aged 18-39 median PDC rose from 84.1% (IQR: 57-100) in the first to 94.7% (IQR: 75.6-100) in the third sequence; in those aged 80 + median PDC rose from 95.0% (IQR: 68.9-100) in the first to 100% (IQR: 78.3-100) in the third sequence. Logistic regression identified age (OR=1.011 per year), female gender (OR=0.896), high-intensity treatment (OR=0.975), and second (OR=1.267) or later treatment sequences (OR=1.704) as significant predictors of adherence (all p < 0.001). CONCLUSION: Adherence to statin therapy improves with subsequent treatment sequences and age. These findings highlight the need for targeted interventions to enhance adherence, particularly among younger patients. The PDC metric is recommended for integration into clinical practice to monitor and improve medication adherence.
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$a Donin, Gleb $u Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University, Prague, Czech Republic
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$a Rybář, Marian $u Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University, Prague, Czech Republic
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