Adherence to Lipid-Lowering Treatment by Single-Pill Combination of Statin and Ezetimibe

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Abstract

Introduction

Although several studies have shown that a simplified cardiovascular drug treatment leads to better treatment adherence, limited and conflicting findings have been reported on the separate or single-pill combination of the now recommended association between a statin and ezetimibe. We addressed this issue in a large cohort of patients newly treated with statins to whom ezetimibe was additionally administered, either separately or as a single-pill combination.

Methods

A total of 256,012 patients (age 40–80 years) from the Lombardy Region (Italy) newly treated with statins during 2011–2013 were followed until 2018 to identify those to whom ezetimibe was added. The 2881 and 5351 patients who started a two-pill or a single-pill combination, respectively, of statin and ezetimibe were identified and matched for propensity score. Adherence to drug therapy at 1 year was measured as the ratio between the number of days in which the drug was available and the days of follow-up (the proportion of days covered; PDC). Patients who had a PDC > 75% or < 25% were, respectively, defined as highly and poorly adherent to drug therapy. Analysis was extended to the association between adherence and the risk of fatal/non-fatal cardiovascular events.

Results

Compared to those prescribed a two-pill combination, those prescribed a single-pill combination had an 87% (75–99%) greater odds of being highly adherent and a 79% (72–84%) lower odds of being poorly adherent to treatment. These advantages were manifest in all strata of age, sex, and clinical profile. The risk of cardiovascular outcomes decreased by 55% in patients with high adherence compared to those with low adherence.

Conclusion

Patients who were prescribed a single-pill combination of statin/ezetimibe more frequently exhibit a good adherence and less frequently bad adherence to treatment than those prescribed a two-pill combination of these drugs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-021-01892-7.

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Most cited references 30

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An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

Peter C Austin (2011)

The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses.

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Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

Peter C Austin (2009)

The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods for assessing whether the propensity score model has been correctly specified: comparing means and prevalences of baseline characteristics using standardized differences; ratios comparing the variance of continuous covariates between treated and untreated subjects; comparison of higher order moments and interactions; five-number summaries; and graphical methods such as quantile–quantile plots, side-by-side boxplots, and non-parametric density plots for comparing the distribution of baseline covariates between treatment groups. We describe methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero, thereby allowing one to determine the range of standardized differences that are plausible with the propensity score model having been correctly specified. We highlight the limitations of some previously used methods for assessing the adequacy of the specification of the propensity-score model. In particular, methods based on comparing the distribution of the estimated propensity score between treated and untreated subjects are uninformative. Copyright © 2009 John Wiley & Sons, Ltd.

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Medication compliance and persistence: terminology and definitions.

Joyce Cramer, Anuja Roy, Anita Burrell … (2008)

The aim of the study is to provide guidance regarding the meaning and use of the terms "compliance" and "persistence" as they relate to the study of medication use. A literature review and debate on appropriate terminology and definitions were carried out. Medication compliance and medication persistence are two different constructs. Medication compliance (synonym: adherence) refers to the degree or extent of conformity to the recommendations about day-to-day treatment by the provider with respect to the timing, dosage, and frequency. It may be defined as "the extent to which a patient acts in accordance with the prescribed interval, and dose of a dosing regimen." Medication persistence refers to the act of continuing the treatment for the prescribed duration. It may be defined as "the duration of time from initiation to discontinuation of therapy." No overarching term combines these two distinct constructs. Providing specific definitions for compliance and persistence is important for sound quantitative expressions of patients' drug dosing histories and their explanatory power for clinical and economic events. Adoption of these definitions by health outcomes researchers will provide a consistent framework and lexicon for research.

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Author and article information

Contributors

Federico Rea:

ORCID: http://orcid.org/0000-0001-7988-5101

federico.rea@unimib.it

Journal

Journal ID (nlm-ta): Adv Ther

Journal ID (iso-abbrev): Adv Ther

Title: Advances in Therapy

Publisher: Springer Healthcare (Cheshire )

ISSN (Print): 0741-238X

ISSN (Electronic): 1865-8652

Publication date (Electronic): 3 September 2021

Publication date PMC-release: 3 September 2021

Publication date (Print): 2021

Volume: 38

Issue: 10

Pages: 5270-5285

Affiliations

[1 ]GRID grid.7563.7, ISNI 0000 0001 2174 1754, National Centre for Healthcare Research and Pharmacoepidemiology, at the University of Milano-Bicocca Milan, ; Milan, Italy

[2 ]GRID grid.7563.7, ISNI 0000 0001 2174 1754, Unit of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, Department of Statistics and Quantitative Methods, , University of Milano-Bicocca, ; Via Bicocca degli Arcimboldi, 8, Edificio U7, 20126 Milan, Italy

[3 ]GRID grid.4643.5, ISNI 0000 0004 1937 0327, Department of Mathematics, MOX-Laboratory for Modeling and Scientific Computing, , Politecnico di Milano, ; Milan, Italy

[4 ]GRID grid.510779.d, ISNI 0000 0004 9414 6915, CADS-Center for Analysis Decisions and Society, , Human Technopole, ; Milan, Italy

[5 ]GRID grid.7563.7, ISNI 0000 0001 2174 1754, University of Milano-Bicocca (Emeritus Professor), ; Milan, Italy

[6 ]Policlinico di Monza, Monza, Italy

Author information

Federico Rea http://orcid.org/0000-0001-7988-5101

Article

Publisher ID: 1892

DOI: 10.1007/s12325-021-01892-7

PMC ID: 8478750

PubMed ID: 34480293

SO-VID: aaeaa655-8566-4968-8f79-2b143959b302

License:

Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

History

Date received : 8 July 2021

Date accepted : 6 August 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100003407, ministero dell’istruzione, dell’università e della ricerca;

Funded by: FundRef http://dx.doi.org/10.13039/501100003196, ministero della salute;

Award ID: NET- 2016-02363853

Award Recipient : Giovanni Corrao

Funded by: Università degli Studi di Milano - Bicocca

Open Access :

Open access funding provided by Università degli Studi di Milano - Bicocca within the CRUI-CARE Agreement.

Adherence to Lipid-Lowering Treatment by Single-Pill Combination of Statin and Ezetimibe

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Abstract

Introduction

Methods

Results

Conclusion

Supplementary Information

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Most cited references 30

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

Medication compliance and persistence: terminology and definitions.

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