Pharmacogenetic polymorphism as an independent risk factor for frequent hospitalizations in older adults with polypharmacy: a pilot study

Abstract

Pharmacogenetic testing identifies genetic biomarkers that are predictive of individual sensitivity to particular drugs. A significant proportion of medications that are widely prescribed for older adults are metabolized by enzymes that are encoded by highly polymorphic genes. Pharmacogenetic testing is increasingly used to optimize the medication regimen; however, its potential in older adults with polypharmacy has not been systematically explored. Following the initial case–series study, this study hypothesized that frequently hospitalized older adults with polypharmacy have higher frequency of pharmacogenetic polymorphism as compared to older adults with polypharmacy who are rarely admitted to a hospital. To test this hypothesis, a nested case–control study was conducted with pharmacogenetic polymorphism as an exposure and hospitalization rate as an outcome. In this study, frequently hospitalized older adults (≥65 years of age) with polypharmacy were matched with rarely hospitalized older adults with poly-pharmacy by age, gender, race, ethnicity, and chronic disease score. Average age and number of prescription drugs did not differ in cases and controls (77.2±5.0 and 78.3±5.1 years, 14.3±5.3 and 14.0±2.9 medications, respectively). No statistically significant difference in sociodemographic, clinical, and behavioral characteristics that are known to affect hospitalization risk was found between the cases and controls. Major pharmacogenetic polymorphism defined as presence of at least one allelic combination resulting in poor or rapid metabolizer status was identified in all the cases. No major pharmacogenetic polymorphisms were detected in controls. Based on the exact McNemar’s test, the difference in major pharmacogenetic polymorphism frequency between cases and controls was statistically significant (p<0.05). In 50% of cases, more than one major pharmacogenetic polymorphism was found. The frequency of CYP2C19 rapid metabolizer, CYP3A4/5 poor metabolizer, VKORC1 low sensitivity, and CYP2D6 rapid metabolizer status in cases was 67%, 33%, 33%, and 17%, respectively, which significantly exceeded respective prevalence in general population. The mean number of major gene–drug interactions found in cases was 2.8±2.2, whereas no major drug–gene interactions were identified in controls. The difference in the number of major drug–gene interactions between cases and controls was statistically significant (p<0.05). The pilot data supported the hypothesis that pharmacogenetic polymorphism may represent an independent risk factor for frequent hospitalizations in older adults with polypharmacy. Due to small sample size, the results of this proof-of-concept study cannot be conclusive. Further work on the utility of pharmacogenetic testing for optimization of medication regimens in this vulnerable group of older adults is warranted.

Incidence and Determinants of Dental Implant Failure: A Review of Electronic Health Records in a U.S. Dental School

“…The nested case-control study design used in our multivariable analyses is a frequently used approach to address limitations of EHR data. 24,25 Overall, our findings conformed with previous studies that found high potential of EHR in improving quality of dental care delivery 26,27 and outlined existing barriers and pitfalls of secondary analysis of EHR data. [28][29][30] Future work on knowledge extraction from electronic dental records and data science applications incorporating information from large biorepositories will further promote evidencebased dentistry, improve dental education, and facilitate continuous dental care improvement.…”

Pharmacogenetic Information in Clinical Guidelines: The European Perspective

“…Of these the 1,200 Patient Project showed that PGx‐informed prescribing supported by electronic decision support significantly changed prescribing behavior for medications with high pharmacogenomics risk . In addition to these large programs, there are a number of small studies that suggest that a preemptive panel approach leads to a reduction in drug‐related morbidity and costs . The clinical utility of a preemptive PGx panel is investigated using a randomized controlled study design in 8,100 patients recruited from seven EU countries in the PREPARE study coordinated by the U‐PGx consortium…”

Estimated nationwide impact of implementing a preemptive pharmacogenetic panel approach to guide drug prescribing in primary care in The Netherlands

“…Results indicate that > 95% of all individuals carry at least one actionable phenotype when tested for a panel of up to 12 genes (including, e.g., CYP2C9 , CYP2C19 , CYP2D6 , SLCO1B1 , and VKORC1 ) [17–19]. This panel-based approach has also been favorably evaluated in a number of small pilot studies in a primary care setting [20–22].…”