Table 1.
Characteristics of included studies.
| Source | Study design | Study description | Participants | Mean number of comorbidities | Mean number of medications |
|---|---|---|---|---|---|
| Randomised trials | |||||
| Elliott 2017 [66] United States | Randomised trial |
IG: Pharmacist-led MTM on patients undergoing PGx testing followed by development of DDI, DGI and DDGI risk profiles using YouScript CDST. PGx test results and prescribing suggestions forwarded to physicians. CG: Comparisons made against an untested group who received usual care (standard pharmacist MTM). Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5 and VKORC1. |
Elderly polypharmacy patients IG = 57 CG = 53 |
Not reported |
IG = 11.6 CG = 11.8 |
| Kim 2018 [65] United States | Randomised trial (post-hoc analysis) |
IG: Pharmacist-led MTM using YouScript with and without PGx (IG1 and IG2 respectively). IG1 underwent PGx testing followed by development of DDI, DGI and DDGI risk profiles. PGx test results and prescribing suggestions forwarded to their physicians. IG2 (untested for PGx) was used to assess effect of CDST alone. CG: Comparisons made against an untested group who received usual care (standard pharmacist MTM). Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5 and VKORC1. |
Polypharmacy patients IG1 = 58 IG2 = 180 CG = 104 |
IG1 = 6.5 ± 2.8 IG2 = 6.6 ± 2.6 CG = 6.2 ± 2.2 |
IG1 = 11.5 ± 4.1 IG2 = 11.5 ± 4.3 CG = 11.2 ± 3.8 |
| Saldivar 2016 [67] United States | Randomised trial (non-comparative results) |
All patients tested; those with passing results randomised to IG or CG. IG: Pharmacist-led MTM using IDgenetix to generate DDI and DGI recommendations. PGx test results and prescribing suggestions forwarded to their physicians. Results listed only for this group (n = 132). CG: PGx results withheld. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, VKORC1, CYP1A2, HTR2A, HTR2C, SLC6A4, SLC6A2, COMT, OPRM1, SLCO1B1, MTHFR, F2 and F5. |
Patients in a long-term care facility n = 132 |
Not reported | 12.0 |
| Non-randomised trials (observational and non-comparative studies) | |||||
| Brixner 2016 [64] United States | Non-concurrent cohort study |
IG: Pharmacist-led MTM on patients undergoing PGx testing followed by development of DDI, DGI and DDGI risk profiles using YouScript CDST. PGx test results and prescribing suggestions forwarded to their physicians. CG: Comparisons made against an untested historical cohort (matched on key variables via a propensity score method). Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5 and VKORC1. |
Elderly polypharmacy patients IG = 205 CG = 820 |
Not reported | 4.0a |
| Finkelstein 2016 [59] United States | Non-comparative case series study |
Participants offered PGx testing by their treating physician to optimise their therapy. GENETWORx was used for analysis. The testing facility provided detailed findings reports and basic education materials explaining the general principles of PGx testing. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5 and VKORC1. |
Elderly polypharmacy patients n = 3 |
7.0 | 20.3 |
| Finkelstein 2016 [63] United States | Nested case-control study |
Cases: chosen from eligible patients with high rates of hospitalisations. Controls: included eligible patients with infrequent hospitalisations matched to cases on age, race, ethnicity and chronic disease score. PGx testing performed on all patients. GENETWORx used for the analysis. The testing facility provided PGx reports and education materials explaining the general principles of PGx testing. DGI severity was confirmed by an independent pharmacist review. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5 and VKORC1. |
Elderly polypharmacy patients IG = 6 CG = 6 |
IG = 8.2 ± 1.2 CG = 8.2 ± 2.0 |
IG = 14.3 ± 5.3 CG = 14.0 ± 2.9 |
| Keine 2019 [60] United States | Non-comparative case series study |
Patients with a family history of Alzheimer’s disease, mild cognitive decline or mild Alzheimer’s disease were enroled. uMethod Health’s precision medicine platform was used to analyse DDIs DGIs, anticholinergic burden and depression-inducing drugs. PGx prescribing suggestions reviewed by a physician and forwarded to patients. Genes: Gene panel is not detailed. |
Elderly polypharmacy patients n = 295 |
Not reported | 11.5 |
| Lee 2019 [61] United States | Non-comparative case series study |
Genotyped 1200 Patients Project participants analysed for hospitalisations (n = 20) to examine medication changes, actionable PGx information and potential prescribing actions using CPIC, FDA and Genomic Prescribing System CDST PGx information. Genes: CYP2C9, CYP2C19, CYP2D6, CYP4F2, VKORC1, SLCO1B1, KIF6, GNB3, LTC4S, ADD1 and GLCCI1. |
Polypharmacy outpatients n = 867 |
7.6 | 8.9 |
| Papastergiou 2017 [58] Canada | Non-comparative case series study |
Pharmacists trained in PGx enroled patients they thought would benefit from the service. Geneyouin provided the tests and evidence-based reports (CPIC and FDA) highlighting patients’ metabolic profiles and risk medications. PGx test results and prescribing suggestions forwarded to physicians. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, VKORC1, CYP1A2, OPRM1 and SLCO1B1. |
Community pharmacy patients n = 100 |
Not reported | 4.9 |
| Reynolds 2017 [56] United States | Non-comparative case series study |
Physicians ordered PGx testing for eligible patients; genotypes were correlated to predicted phenotypes on the PRIMER report. Pharmacists performed MTM (DDIs and DGIs) and ranked the severity of interactions. PGx test results and prescribing suggestions forwarded to physicians. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, VKORC1, CYP1A2, SLC6A4, COMT, OPRM1, SLCO1B1, F2, F5 and MTHFR. |
Polypharmacy patients n = 705 |
Not reported | 12.0 |
| Sugarman 2016 [57] United States | Non-comparative case series study |
Pharmacist-led MTM using IDgenetix to generate DDI and DGI recommendations. PGx test results and prescribing suggestions forwarded to their physicians. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, VKORC1, CYP1A2, HTR2A, HTR2C, SLC6A4, SLC6A2, COMT, OPRM1, SLCO1B1, and MTHFR. |
Patients in a long-term care facility n = 112 |
Not reported | 19.0 |
| Van der Wouden 2019 [62] The Netherlands | Cross-sectional study |
Pharmacists requested PGx tests for eligible patients to guide therapy. DPWG guidelines provided the recommendations that were sent to pharmacists and patients’ physician. PGx data was saved in both electronic medical records for future use; follow-up was 2.5 years. Patients put into three groups: [1] did not encounter a DGI or encountered a DGI and healthcare professional [2] adhered or [3] did not adhere to guidelines. Genes: CYP2C9, CYP2C19, CYP2D6, CYP3A5, SLCO1B1, TPMT, VKORC1 and DPYD. |
Community pharmacy patients G1 = 138 G2 = 49 G3 = 9 |
G1 = 4.4 ± 2.4 G2 = 4.9 ± 2.6 G3 = 4.4 ± 2.3 |
G1 = 3.9 ± 3.4 G2 = 4.0 ± 2.9 G3 = 4.4 ± 3.0 |
ADD alpha-adducin, CDST clinical decision support tool, CG control group, COMT catechol-O-methyltransferase, CPIC Clinical Pharmacogenetics Implementation Consortium, CYP cytochrome P450, DPWG Dutch Pharmacogenetic Working Group, DPYD dihydropyrimidine dehydrogenase, DDI drug-drug interaction, DDGI drug-drug-gene interaction, DGI drug-gene interaction, ED emergency department, F2 Factor II prothrombin, F5 Factor V Leiden, FDA, U.S. Food and Drug Administration, G group, GLCCI glucocorticoid induced, GNB G protein subunit beta, HTR 5-hydroxytryptamine receptor, IG intervention group, KIF kinesin family member, LTC4S leukotriene C4 synthase, MTHFR methylenetetrahydrofolate reductase, MTM medication therapy management, PGx pharmacogenetic, OASIS Outcome and Assessment Information Set, OPRM opioid receptor mu, SLC solute carrier (serotonin transporter), SLCO solute carrier organic anion transporter, TPMT thiopurine methyltransferase, VKORC vitamin K epoxide reductase complex.
aD. Brixner contacted; estimated the majority were on four or more medications.