Tool Finds Best Heart Disease, Stroke Treatments for Patients with Diabetes
Researchers from North Carolina State University and Mayo Clinic have developed a computer model that medical doctors can use to determine the best time to begin using statin therapy in diabetes patients to help prevent heart disease and stroke.
“The research is significant because patients with diabetes are at high risk for cardiovascular disease and statins are the single most commonly used treatment for patients at risk of heart disease and/or stroke,” says Dr. Brian Denton, “and this model can help determine the best course of action for individual patients based on their risk of developing cardiovascular disease.” Denton is an assistant professor in NC State’s Edward P. Fitts Department of Industrial & Systems Engineering and lead author of the study.
Statins are a key component of current cardiovascular medical treatment guidelines, Denton says. 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 developed a new mathematical model that examines various possible treatment policies to see how they influence short-term and long-term health outcomes for patients. The model shows how people are affected by diabetes, and how their health changes over time as the disease advances and patients age.
The new model incorporates patient-specific data. An established risk model calculates each patient’s probability of heart attack and stroke based on risk factors, such as their cholesterol, blood pressure, etc. This overall risk “score” is used to weigh the medical advantages of beginning statin therapy against the financial cost of the statins.
Overall, by accounting for the progression of diabetes, the patient’s specific risk score and the cost-benefit analysis, the new model may help patients and doctors decide on the optimal time to begin statin therapy.
Denton says the new model has not yet been put into practice, but that the research team plans to develop a pilot to put the tool into the hands of medical professionals.
The research, “Optimizing the Start Time of Statin Therapy for Patients with Diabetes,” was funded in part by the Agency for Healthcare Research and Quality and the National Science Foundation, and was published earlier this month in the journal Medical Decision Making. The research was co-authored by Denton from NC State; Nilay D. Shah, Sandra C. Bryant and Steven A. Smith of the Mayo Clinic College of Medicine; and University of Pittsburgh graduate student Murat Kurt.
– shipman –
Note to editors: The study abstract follows.
“Optimizing the Start Time of Statin Therapy for Patients with Diabetes”
Authors: Brian T. Denton, North Carolina State University; Murat Kurt, University of Pittsburgh; Nilay D. Shah, Sandra C. Bryant and Steven A. Smith, the Mayo Clinic College of Medicine
Published: June, 2009, Medical Decision Making
Abstract: Background. Clinicians often use validated risk models to guide treatment decisions for cardiovascular risk reduction. The most common risk models for predicting cardiovascular risk are the UKPDS, Framingham, and Archimedes models. In this article, the authors propose a model to optimize the selection of patients for statin therapy of hypercholesterolemia, for patients with type 2 diabetes, using each of the risk models. For each model, they evaluate the role of age, gender, and metabolic state on the optimal start time for statins. Method. Using clinical data from the Mayo Clinic electronic medical record, the authors construct a Markov decision process model with health states composed of cardiovascular events and metabolic factors such as total cholesterol and high density lipoproteins. They use it to evaluate the optimal start time of statin treatment for different combinations of cardiovascular risk models and patient attributes. Results. The authors find that treatment decisions depend on the cardiovascular risk model used and the age, gender, and metabolic state of the patient. Using the UKPDS risk model to estimate the probability of coronary heart disease and stroke events, they find that all white male patients should eventually start statin therapy; however, using Framingham and Archimedes models in place of UKPDS, they find that for male patients at lower risk, it is never optimal to initiate statins. For white female patients, the authors also find some patients for whom it is never optimal to initiate statins. Assuming that age 40 is the earliest possible start time, the authors find that the earliest optimal start times for UKPDS, Framingham, and Archimedes are 50, 46, and 40, respectively, for women. For men, the earliest optimal start times are 40, 40, and 40, respectively. Conclusions. In addition to age, gender, and metabolic state, the choice of cardiovascular risk model influences the apparent optimal time for starting statins in patients with diabetes.
