UAMS Doctor Receives VA Merit Award to Address Overprescribing of Thyroid Medication
| UAMS’ Spyridoula Maraka, M.D., has been awarded a Veterans Affairs (VA) Merit Award of $830,000 over four years to address the widespread overprescribing of levothyroxine (LT4), one of the most prescribed drugs in the United States.
LT4 is used to treat hypothyroidism, a condition where the thyroid produces too few hormones. However, many patients are prescribed LT4 based solely on a single abnormal test, even when thyroid function is normal, Maraka said, which can lead to unnecessary treatment and financial burden, disruptive lifestyle changes, cardiovascular risks and even death.
About 20 million people in the United States receive LT4. Among those starting LT4, about 31% have normal thyroid function, meaning LT4 should not have been prescribed, according to a 2021 article in the Journal of the American Medical Association Internal Medicine that Maraka co-authored.
“There is widespread, wasteful and harmful overprescribing of LT4,” said Maraka, an associate professor in the UAMS College of Medicine Division of Endocrinology and Metabolism and director of the Endocrinology Fellowship Program. She is also chief of the Section of Endocrinology at the Central Arkansas Veterans Healthcare System (CAVHS).
Maraka’s project, “Minimizing Levothyroxine Overuse,” will use machine learning to determine the factors driving LT4 overuse and develop evidence-based prescribing strategies.
“Our preliminary data show that a lack of informed discussion between patients and their doctors and gaps in doctors’ knowledge of guidelines are a big factor,” Maraka said.
Using machine-learning methods, her team will be able to identify clusters of risk factors that traditional analyses might miss.
“With conventional statistical methods it may be very hard to figure out who is at risk for levothyroxine overuse,” Maraka said. “With machine learning, we can see through the data and identify subgroups of patients who are more at risk for levothyroxine overuse. Having this important information should allow us to tailor our prescribing strategies towards those groups.”
For example, she said, machine learning can identify multiple factors, such as the combination of gender, race and tobacco use, as a key driver of LT4 overuse.
Maraka gathered the preliminary data for the VA Merit Award application as a recent participant in the UAMS Translational Research Institute’s two-year Implementation Science Scholar Program. She also used her time in the program to get buy-in from clinicians and leaders at CAVHS, where her project will be focused.
“I’m excited to work directly with patients and clinicians on this project,” she said. “This work will enhance clinical decision-making and bridge the gap between guidelines and practice.”
She credits her CAVHS research team and the implementation science training for equipping her with the tools to translate research into actionable solutions.
“I believe I received a strong foundation in implementation science,” she said. “It has helped me develop a solid research approach and a well thought out strategy. I wouldn’t have received this grant if I didn’t have a good understanding of implementation science or the frameworks of how we do this research.”