Introduction: Clinical utilization of pharmacogenomics (PGx) testing is highly institutionally dependent, and little information is known about provider practices of PGx testing in the Military Health System (MHS). In this study, we aimed to characterize Clinical Pharmacogenetics Implementation Consortium (CPIC) actionable prescription (Rx) patterns and their temporal relationship with PGx testing in the MHS.
Methods: Using data from the Military Health System Management Analysis and Reporting Tool (M2) database, this retrospective cohort study included all patients receiving at least one PGx test and at least one CPIC actionable Rx from January 2015 to August 2020 (845 patients, 1,471 PGx, 7,725 index CPIC actionable Rxs). Rx patterns and temporal relationships with PGx testing were characterized via descriptive statistics. Binomial regression was used to determine which patient and provider characteristics were associated with a patient receiving a PGx test within 30 days of an index Rx.
Results: Patients had a median of 9 index CPIC actionable Rx's (range 1-26). Pain medications were most commonly prescribed (N = 794, 94% patients with at least 1 Rx). However, pain medication had the lowest Rx-PGx match rate (40%) compared to an average of 62% Rx-PGx match rate for all CPIC drugs. Antidepressants were also commonly prescribed (N = 668, 79.1% patients with at least 1 Rx), and antidepressants had the highest Rx-PGx match rate of 86.7%. A minority of providers (20%, N = 249) ordered the majority of PGx tests (86.1%, N = 1,266) and only 8.3% of PGx tests (N = 398) matched to a CPIC actionable drug within 30 days of the test (defined by Rxs ordered within 30 days before or after the PGx test). However, approximately 39.8% of patients (N = 317) had at least one drug match to a PGx test within 30 days. The largest predictor of whether a patient received a PGx test within 30 days of any index Rx was whether or not a specific psychiatry provider ordered the PGx test (odds ratio; OR 3.7, 95% CI 2.13-6.54, P < 0.001). Neither the CPIC level of evidence nor FDA PGx actionable or informative labels had a significant effect on PGx test timing.
Conclusions: PGx testing was generally limited to high Rx-drug users and was found to be an under-utilized resource. PGx testing did not typically follow CPIC guidelines. Implementing PGx testing protocols, simplifying PGx test-ordering by incorporating at minimum CYP2D6, CYP2C19, and CYP2C9 into PGx-testing panels, and unifying providers' PGx knowledgebase in the MHS are feasible and would improve the clinical utilization of PGx tests in the MHS.
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http://dx.doi.org/10.1093/milmed/usab481 | DOI Listing |
J Pers Med
November 2024
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.
: The integration of pharmacogenetic (PGx) testing into primary care has not been widely implemented, despite its benefits for patients and providers. PGx testing could also reduce health disparities as patients with lower healthcare access are prescribed higher proportions of medications with PGx guidelines. Little is known about the preferences of patients who have experienced PGx testing to inform implementation across the care process.
View Article and Find Full Text PDFExp Biol Med (Maywood)
December 2024
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States.
Pharmacogenomics (PGx) holds the promise of personalizing medical treatments based on individual genetic profiles, thereby enhancing drug efficacy and safety. However, the current landscape of PGx research is hindered by fragmented data sources, time-consuming manual data extraction processes, and the need for comprehensive and up-to-date information. This study aims to address these challenges by evaluating the ability of Large Language Models (LLMs), specifically Llama3.
View Article and Find Full Text PDFInt J Pharm
December 2024
Pharmacogenomics (PGx) Laboratory, University of Puerto Rico, Medical Sciences Campus, San Juan, PR, 00936, United States; Department of Pharmaceutical Sciences, School of Pharmacy, University of Puerto Rico - Medical Sciences Campus, San Juan, PR 00936, United States. Electronic address:
Over the next decade, Precision Medicine (PM) is poised to become the standard of care in pharmaceutical therapy, necessitating a fundamental transformation in the design and development of innovative custom-made drug products. To date, a comprehensive review linking PM with practical personalized drug formulations is missing. This review attempts to provide an overview of state-of-the-art formulation approaches capable of translating PM evaluation and resulting recommendations (clinical research) into tailored drug products (non-clinical research) for real-world patients.
View Article and Find Full Text PDFNucleic Acids Res
November 2024
Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark.
Pharmacogenomics, the study of how an individual's genetic makeup influences their response to medications, is a rapidly evolving field with significant implications for personalized medicine. As researchers and healthcare professionals face challenges in exploring the intricate relationships between genetic profiles and therapeutic outcomes, the demand for effective and user-friendly tools to access and analyze genetic data related to drug responses continues to grow. To address these challenges, we have developed PGxDB, an interactive, web-based platform specifically designed for comprehensive pharmacogenomics research.
View Article and Find Full Text PDFAm J Health Syst Pharm
November 2024
Sanford Imagenetics, Sioux Falls, SD, and Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD, USA.
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