Pharmacogenetic Testing in a 70-Year-Old Woman with Polypharmacy and Multiple Comorbidities: A Case Report.

BACKGROUND Comorbidities and polypharmacy are difficult to manage, as polypharmacy hinders identification and prevention of medication-related problems. Risk for adverse drug events (ADEs) can be minimized through pharmacogenomic (PGx) testing and related therapeutic adjustments. CASE REPORT A 70-year-old woman with comorbidities and medications enrolled in the Program of All-inclusive Care for the Elderly presented with left lower extremity (LLE) pain, generalized weakness, and major depressive disorder. The provider requested a medication safety review, where the clinical pharmacist-recommended PGx testing given the LLE pain and weakness while taking a statin and inconsistent INR readings taking warfarin. The pharmacist recommended switching atorvastatin to pravastatin to minimize the risk for statin-associated ADEs due to CYP3A4 inhibition and switching fluoxetine to citalopram due to uncontrolled depression/anxiety and to mitigate drug-drug interactions with carvedilol to reduce the risk of orthostatic hypotension. Recommendations were accepted and upon follow-up the patient reported minor LLE pain and improved wellbeing on citalopram. Following PGx testing, the patient had decreased function at SLCO1B1 and was an intermediate metabolizer for CYP2C9 and CYP2D6. This case demonstrates how preemptive PGx testing would have identified drug-gene interactions (DGIs) at the time of prescribing and reduced the risk of statin-associated muscular symptoms, highlighting the utility of panel-based PGx testing in older adults at high risk for ADEs and/or therapy failure. CONCLUSIONS Decreased function at SLCO1B1 increases exposure to statins, leading to statin-induced myalgias, as displayed in this case. PGx testing can help identify DGIs, choose optimal therapies in medically complex older adults, and minimize ADE risk.

Case Report: Performing a Medication Safety Review Assisted by Pharmacogenomics to Explain a Prescribing Cascade Resulting in a Patient Fall.

Pharmacotherapy for major depressive disorder (MDD) typically consists of trial-and-error and clinician preference approaches, where patients often fail one or more antidepressants before finding an optimal regimen. Pharmacogenomics (PGx) can assist in prescribing appropriate antidepressants, thereby reducing the time to MDD remission and occurrence of adverse drug events. Since many antidepressants are metabolized by and/or inhibit cytochrome P450 enzymes (e.g., CYP2C19 or CYP2D6), drug-induced phenoconversion is common in patients on antidepressant combinations. This condition influences the interpretation of a patient's PGx results, overall risk of ineffective/adverse medication response due to multi-drug interactions, and the recommendations. This complex case describes a patient with MDD, generalized anxiety disorder, and chronic pain who experienced a fall due to excessive sedation following a prescribing cascade of fluoxetine, bupropion, and doxepin. These antidepressants delivered a significant additive sedative effect and interacted with the patient's hydrocodone, potentially contributing to uncontrolled pain, upward dose titration of hydrocodone, and a higher overall sedative burden. The PGx results and drug-induced phenoconversion described in this case report explain the patient's excessive sedation and possibly ineffective/toxic antidepressant and opioid treatment. This case report also illustrates how a more timely multi-drug interaction assessment (preferably in conjunction with preemptive PGx testing) may have informed a different prescribing pattern, reduced/avoided a prescribing cascade, and potentially prevented a drug-related fall.

Utilizing Pharmacogenomics Results to Determine Opioid Appropriateness and Improve Pain Management in a Patient with Osteoarthritis.

The opioid epidemic in the United States has exposed the need for providers to limit opioid dispensing and identify at-risk patients prior to prescribing opioids. With pharmacogenomic testing, clinicians can analyze hundreds of medications-including commonly prescribed opioids-against genetic results to understand and predict risk and response. Moreover, knowledge of genotypic variants and altered function can help decrease trial and error prescribing, identify patients at-risk for adverse drug events, and improve pain control. This patient case demonstrates how pharmacogenomic test results identified drug-gene interactions and provided insight about a patient's inadequate opioid therapy response. With pharmacogenomic information, the patient's healthcare team discontinued opioid therapy and selected a more appropriate regimen for osteoarthritis (ie, celecoxib), resulting in improved pain control and quality of life.

Medication-related problems encountered in the Program of All-Inclusive Care for the Elderly: An observational study.

OBJECTIVE: To evaluate pharmacist-encountered medication-related problems (MRPs) among the participants of the Program of All-Inclusive Care for the Elderly (PACE). DESIGN: This was a retrospective analysis of proprietary pharmacy records detailing pharmacist encounters with PACE clinical staff. SETTING AND PARTICIPANTS: A national provider of pharmacy services to more than 75 PACE organizations. In total, 1057 PACE participants at 69 PACE sites across the United States with documented pharmacist encounters between March and May 2018. OUTCOME MEASURES: MRPs were classified using the Hepler-Strand taxonomy, and pharmacists' recommendations made to prescribers to resolve these MRPs were classified using a modified Hoth taxonomy. In addition, pharmacists' communication methods and prescribers' responses were analyzed. RESULTS: Overall, 2004 MRPs were encountered. The most frequent MRPs identified were related to medication safety concerns, including drug interactions (720, 35.9%), adverse drug reactions (ADRs, 356, 17.8%), high doses (270, 13.5%), and unindicated drugs (252, 12.6%). Drug interactions frequently involved competitive inhibition, 3 or more drugs, opioids, anticoagulants, antiplatelets, and antidepressants. Deprescribe medication (561, 24.8%), start alternative therapy (553, 24.4%), change doses (457, 20.2%), and monitor (243, 10.7%) were the top 4 types of recommendations made by pharmacists. Among 1730 responses obtained from PACE prescribers, 78.1% (n = 1351) of pharmacists' recommendations were accepted. Compared with electronic communication, telephonic communication was associated with more acceptance and less prescriber nonresponse (χ2 = 78.5, P < 0.001). CONCLUSION: Pharmacists identified a substantial number of MRPs in PACE, especially those related to medication safety such as drug interactions and ADRs. In this practice setting, significant collaboration occured between pharmacists and PACE prescribers, as evidenced by the rate of prescribers' acceptance of pharmacists' recommendations. Further research is needed to fully evaluate the economic, clinical, and humanistic outcomes associated with pharmacists' encounters in PACE.