Abstract

Background: Despite the proven efficacy and safety of statins, nearly 250,000 Veterans at high-risk for cardiovascular disease (CVD) seen annually in primary care are not taking them leading to higher cholesterol levels, cardiovascular risk, and health care costs. Primary care providers and health systems have a critical and unmet need for pragmatic, scalable interventions to address gaps in their patients’ perceptions of the risks and benefits of statin therapy to improve appropriate statin utilization and to lower CVD risk. Important prior work by our group demonstrates that pharmacogenomic testing for statin toxicity is feasible, improves patients’ perceptions of statin therapy, leads to a doubling in appropriate statin prescribing, and lowers cholesterol levels. The central hypothesis of this proposal is that disclosure of statin pharmacogenomic test results for statin efficacy/toxicity and CVD risk to patients at high-risk for CVD will improve their perceptions of their CVD risk and statins risks/benefits and, in turn, the proportion of Veterans accepting and adhering to statin therapy to achieve a clinically significant low-density lipoprotein cholesterol (LDL) reduction. Significance: By using a feasible and inexpensive approach of pharmacogenomic testing for common genetic variants reporting on statin efficacy and toxicity and CVD risk, the work is significant as it will lead to more patients at high-risk for CVD accepting and adhering to statins. This work addresses HSR&D research priorities of quality and safety of health care and health care value, ORD priorities of increasing substantial real-world impact of VA research, and VHA quality measures around statin prescribing and controlling cholesterol levels in patients at high-risk for CVD. Innovation and Impact: This proposal uses an innovative approach of pharmacogenomic testing to address patients’ perceptions of the risks and benefits of statin therapy and their risk of CVD which are known barriers to statin acceptance and adherence. We expect a positive impact on reducing CVD risk in Veterans. Specific Aims: 1: Reduce cholesterol levels through a precision medicine approach of statin pharmacogenomic testing. 2: Improve acceptance of guideline-directed statin therapy through delivery of statin pharmacogenomic test results that communicates statin efficacy and toxicity. 3: Identify contextual and economic factors salient for implementing statin pharmacogenomic testing. Methodology: A randomized controlled trial focused on effectiveness while secondarily gathering implementation data will enroll 408 primary care patients who are at high-risk for CVD and recommended for statins based on guidelines but not prescribed them. Participants will be randomized 1:1 to intervention (guideline-based statin recommendations - “guidelines” - plus statin pharmacogenomic test results) vs. control (guidelines) stratified by prior statin use. The primary outcome is change in 12-month LDL. Secondary outcomes are new statin prescriptions and patients’ perceptions of risks and benefits of statins. Exploratory analyses will assess statin prescriptions and fills as potential mediators of the intervention. Qualitative data from trial participants and their providers will illuminate key factors to consider for future implementation. If effective, the cost-effectiveness and budget impact of the intervention on LDL during the trial period projected over 10-year and lifetime CVD risk horizons will be measured. Next steps/Implementation: An embedded primary care, patient-powered caucus and a VA operational stakeholder board representing primary care, cardiology, pharmacy, and the VA Pharmacogenomics Testing for Veterans (PHASER) clinical program will work with the investigative team to create an implementation “blueprint” package consisting of patient/provider educational portfolios, electronic medical record tools, Corporate Data Warehouse queries, and laboratory protocols for dissemination to Veterans and VHA facilities.

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DRA: Cardiovascular Disease

DRE: Genomics, TRL - Applied/Translational, Data Science

Keywords: Cardiovascular Disease, Decision Support, Patient-Provider Interaction, Pharmacology, Risk Factors

MeSH Terms: None at this time.