HMG-CoA reductase inhibitors, commonly known as statins, are some of the most widely prescribed medications worldwide and have been shown to be effective at lowering cholesterol in numerous long-term prospective trials, yet there are significant limitations to their use. First, patients receiving statin therapy have relatively low levels of medication adherence compared with other drug classes. Next, numerous statin formulations are available, each with its own unique safety and efficacy profile, and it may be unclear to prescribers which treatment is optimal for their patients. Finally, statins have class-wide side effects of myopathy and rhabdomyolysis that have resulted in a product recall and dosage limitations. Recent evidence suggests that two genomic markers, KIF6 and SLCO1B1, may inform the therapy choice of patients initiating statins. Given the prevalence of statin usage, their potential health advantages and their overall cost to the healthcare system, there could be significant clinical benefit from creating personalized treatment regimens. Ultimately, if this approach is effective it may encourage higher adoption of generic statins when appropriate, promote adherence, lower rates of myopathy, and overall achieve higher value cardiovascular care. This paper will review the evidence for personalized prescribing of statins via KIF6 and SLCO1B1 and consider some of the implications for testing these markers as part of routine clinical care.

Background-Patients treated with clopidogrel who have ≥1 loss of function alleles for CYP2C19 have an increased risk for adverse cardiovascular events. In 2010, the US Food and Drug Administration issued a boxed warning cautioning against the use of clopidogrel in such patients. We sought to assess the impact of CYP2C19 genetic testing on prescribing patterns for antiplatelet therapy among patients with acute coronary syndrome or percutaneous coronary intervention.

Healthcare payers represent stakeholders who can act as either a bridge or a gate to the translation of personalized medicine into routine clinical practice. To date, the slow realization of the promise of personalized medicine has been partly attributable to the lack of clear evidence supporting the clinical utility of genetic and genomic tests and the lag in development of clinical guidelines for the use and interpretation of tests. These factors, along with a paucity of clear guidance from healthcare payers and clinical experience with genomic tests, serve as impediments to timely and consistent reimbursement decisions. The design of alternative strategies for collaborative evidence-generation, clinical decision support and educational initiatives for healthcare providers, patients and the payers themselves are critical needs to achieve the full benefit of personalized medicine in day-to-day healthcare settings.