05:24am Friday 20 October 2017

Study: Most At-Risk Patients Don’t Adhere To Statin Treatment, Despite Real Benefits

“We found that only 48 percent of patients who have been prescribed statins are taking their prescribed dose on a regular basis after one year – and that number dips to approximately 27 percent after 10 years,” says Jennifer Mason, a Ph.D. student at NC State and lead author of a paper describing the study. Statins are a component of many current cardiovascular medical treatment guidelines. They lower cholesterol levels and may significantly reduce the risk of heart attack and stroke, particularly in patients that are considered to be at high risk.

The researchers also found that, for high-risk patients, high adherence to a prescribed statin regimen may increase quality-adjusted life years (QALYs) by as much as 1.5 years compared to low adherence – and up to two years compared to not taking statins at all. Low adherence means a patient is taking the statins irregularly or at less than the prescribed dosage. QALYs are established metrics for measuring the effect of health conditions, such as heart disease and stroke, on quality of life.

The study used operations research models to look specifically at patients who have type 2 diabetes, because they are at particularly high risk for heart disease, heart attack and stroke.

“These findings suggest that adherence-improving interventions – such as patient education or electronic reminders to take medications – can significantly improve the quality and length of life, particularly for high-risk patients,” says Dr. Brian Denton, co-author of the paper and an associate professor in the Edward P. Fitts Department of Industrial & Systems Engineering at NC State.

The paper, “Optimizing Statin Treatment Decisions for Diabetes Patients in the Presence of Uncertain Future Adherence,” is forthcoming from the journal Medical Decision Making. The research was funded by the Agency for Healthcare Research and Quality (AHRQ) and the National Science Foundation (NSF). The paper was co-authored by Dr. Darin England; Drs. Steven Smith and Nilay Shah of the Mayo Clinic College of Medicine; and Mr. Murat Kurt of the University of Pittsburgh.


Note to editors: The study abstract follows.

“Optimizing Statin Treatment Decisions for Diabetes Patients in the Presence of Uncertain Future Adherence”

Authors: Jennifer E. Mason and Brian T. Denton, North Carolina State University; Darin A. England; Steven A. Smith and Nilay D. Shah, Mayo Clinic College of Medicine; Murat Kurt, University of Pittsburgh

Published: forthcoming, Medical Decision Making

Abstract: Background: Statins are an important part of the treatment plan for patients with type 2 diabetes. However, patients who are prescribed statins often take less than the prescribed amount or stop taking the drug altogether. This suboptimal adherence may decrease the benefit of statin initiation. Objective: To estimate the influence of adherence on the optimal timing of statin initiation for patients with type 2 diabetes. Method: The authors use a Markov decision process (MDP) model to optimize the treatment decision for patients with type 2 diabetes. Their model incorporates a Markov model linking adherence to treatment effectiveness and long-term health outcomes. They determine the optimal time of statin initiation that minimizes expected costs and maximizes expected quality-adjusted life years (QALYs). Results: In the long run, approximately 25% of patients remain highly adherent to statins. Based on the MDP model, generic statins lower costs in men and result in a small increase in costs in women relative to no treatment. Patients are able to noticeably increase their expected QALYs by 0.5 to 2 years depending on the level of adherence. Conclusions: Adherence-improving interventions can increase expected QALYs by as much as 1.5 years. Given suboptimal adherence to statins, it is optimal to delay the start time for statins; however, changing the start time alone does not lead to significant changes in costs or QALYs.

Matt Shipman | News Services | 919.515.6386

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