Researchers are using a new pharmacogenetic-based algorithm to predict patients who are abnormal metabolizers of statins and thus at risk for accumulating high blood levels of the drug, leading to debilitating, even fatal, cases of myopathy.
“One of the common well-known side effects [of statins] is muscle aches, pains and weakness, which can occur in a large number of people—up to 10% or 15% of the patients who take them,” senior author Richard B. Kim, MD, a professor of medicine at the University of Western Ontario, London, Canada, told Pharmacy Practice News. “Although the vast majority are able to take statins, a small subset of those patients can go on to have ... rhabdomyolysis that sometimes leads to kidney failure and, in very rare cases, death. So the question then comes down to [whether] there [is] a way of predicting those who may experience these types of side effects.”
In the study, the researchers prospectively recruited 299 outpatients taking atorvastatin or rosuvastatin (Circ Cardiovasc Genet 2013;6:400-408). Forty-fivefold interpatient variability in statin concentration was found among patients taking the same drug and dose. Nearly 90% of the explainable variability in rosuvastatin concentration could be accounted for by two reduced-function transporter polymorphisms, one in the uptake transporter gene SLCO1B1 and the other in the efflux transporter gene ABCG2. Explainable variability in atorvastatin level was almost equally divided between two polymorphisms in SLCO1B1 and activity of cytochrome enzyme CYP450 3A4.
From these findings, the investigators designed an algorithm that includes recommendations for maximum atorvastatin and rosuvastatin doses, based on the patient’s age and transporter genotype. The doses were predicted to result in plasma concentrations of statins that would be lower than the 90th percentile, a value that reflects the fact that 10% of patients taking statins have statin-related muscle complaints.
The researchers also retrospectively genotyped 579 patients from primary and specialty care databases in Canada and the United States. Genotypes associated with statin concentration were not differently distributed by statin dose, suggesting that clinicians had not optimized each patient’s statin serum level and that use of the algorithm thus might be beneficial.
‘A Great Paper’
“I think it’s a great paper,” said Jasmine Talameh, PharmD, PhD, a postdoctoral researcher at Ohio State University, in Columbus, who was not associated with the study. “There’s a lot of data in the literature on genetic variants associated with statin-induced myopathy. But a model combining those genetic variants for predicting statin-induced myopathy hasn’t been established yet. This paper takes a step forward in doing that.”
Asked whether the algorithm is ready to be used clinically, Dr. Kim said, “We do think the information provided in our published research can be [applied to patients]. What our algorithm does is serve as a statin selection and dosing decision-support tool for clinicians.”
Dr. Talameh countered that “more research is needed. Concentration predictions need to be validated prospectively in an independent patient population. The gold standard after that would be prospectively validating the algorithm for association with not just concentration, but the clinical outcome of statin-induced myopathy.”
Clinical use of the algorithm requires genotyping of the patient, which Dr. Kim said would cost $100 to $300. In the future, he noted, as a result of advances in the development of next-generation sequencing technology, “statin genotyping will be included as a part of a [large diagnostic] panel that could be done at once. So you basically buy the whole encyclopedia, and this [statins] would be just a chapter.” Insurers might pay for genotyping, but only “if there is increasing evidence that this is cost-effective.”
Limitations of the study include a focus on only two of several commonly used statins and a predominantly white patient population, Dr. Kim noted. He added that he would like to see “a larger multicenter trial using our predictive algorithm versus standard care,” as well as research exploring the prevention of adverse reactions and severe muscle injury, overall health care costs, and noninferior or better cardiovascular outcomes and cholesterol lowering.
Drs. Kim and Talameh reported no relevant financial conflicts of interest.