Economic evaluation of a pharmacogenomic multi-gene panel test to optimize anti-hypertension therapy: simulation study

Abstract

Aims: Hypertension is the strongest modifiable risk factor for cardiovascular disease, affecting 80 million individuals in the US and responsible for ∼360,000 deaths, at total annual costs of $93.5 billion. Antihypertension therapies guided by single genotypes are clinically more effective and may avert more adverse events than the standard of care of layering anti-hypertensive drug therapies, thus potentially decreasing costs. This study aimed to determine the economic benefits of the implementation of multi-gene panel guided therapies for hypertension from the payer perspective within a 3-year time horizon.

Materials and methods: A simulation analysis was conducted for a panel of 10 million insured patients categorized clinically as untreated, treated but uncontrolled, and treated and controlled over a 3-year treatment period. Inputs included research data; empirical data from a 11-gene panel with known functional, heart, blood vessel, and kidney genotypes; and therapy efficacy and safety estimates from literature. Cost estimates were categorized as related to genetic testing, evaluation and management, medication, or adverse events.

Results: Multi-gene panel guided therapy yielding savings of $6,256,607,500 for evaluation and management, $908,160,000 for medications, and $37,467,508,716 for adverse events, after accounting for incremental genetic testing costs of $2,355,540,000. This represents total 3-year savings of $42,276,736,216, or a 47% reduction, and 3-year savings of $4,228 and annual savings of $1,409 per covered patient.

Conclusions: A precision medicine approach to genetically guided therapy for hypertension patients using a multi-gene panel reduced total 3-year costs by 47%, yielding savings exceeding $42.3 billion in an insured panel of 10 million patients. Importantly, 89% of these savings are generated by averting specific adverse events and, thus, optimizing choice of therapy in function of both safety and efficacy.

Keywords:

• Pharmacogenomics
• Genetic testing
• Hypertension
• Precision medicine
• Economics
• Simulation

JEL Classification:

• C15
• E17
• I11
• I15

Introduction

Hypertension is the strongest modifiable risk factor for cardiovascular disease (CVD) and is the leading cause of death and disability-adjusted life-years worldwide^1,2. Globally, 31.1% of the adult population (1.39 billion) had hypertension in 2010 (the last year that meaningful population data are available), and this number is projected to increase to 1.5 billion people worldwide by 2025^3,4. In the US, from 2000 to 2010, the prevalence of hypertension rose from 27.8% to 31.1% in men and 30.9% to 31.8% in women, creating an affected population size of ∼80 million individuals^3,5. The problem is compounded by the addition of more than 5 million new diagnoses made each year in the US alone^3,5,6. Furthermore, high blood pressure (BP) is responsible for ∼360,000 deaths annually and, in 2009, had a direct cost to the US healthcare system of ∼ $51 billion dollars^7,8. From 1979–1982 to 2003–2006, the proportion of hospitalizations associated with hypertension increased from 1.9% to 5.4%, resulting in cost increases from $40 billion to estimates as high as $113 billion^9,10. Although new BP standards were released in 2017¹¹, their adoption has been slow and the BP categorization as used in recent meta-analyses prevails: normal BP (systolic BP [SBP] < 120 mmHg and diastolic BP [DBP] < 80 mmHg), elevated BP (SBP = 120–129 mmHg, DBP <80 mmHg), stage 1 hypertension (SBP = 130–139 mmHg, DBP = 80–89 mmHg), and stage 2 hypertension (SBP ≥140 mm, DBP ≥90 mmHg)^12–15.

Aggressive and intensive treatment for rapid reduction in BP is important for survival in patients with hypertension, as end organ damage occurs quickly, and small reductions (∼5 mmHg) in BP can markedly improve survival¹⁶. Unfortunately, only an estimated 70% of hypertension patients are treated, and ∼50% of those are defined as controlled (BP <140/90 mmHg), suggesting that the efficacy of anti-hypertensive therapy to achieve BP control goes beyond patient adherence and related medication behaviors¹⁷. Furthermore, each common class of prescribed BP medication (β-blockers, Ca⁺ channel blockers, ACE inhibitors, angiotensin II antagonists, diuretics) has an average effectiveness rate of ∼50%, clearly suggesting a genetic component to therapy efficacy¹⁸. The lack of universal effectiveness for each class of antihypertensive medications is further demonstrated in the bell-curve response to most hypertension therapies. This bell-curve response leads to a proportion of patients having a desired reduction in BP, but a significant proportion of patients (10–20%) experiencing no change or even an increase in BP^19,20. Therefore, the current standard of care to achieve the desired BP response is to increase dosage to the maximally tolerated dosage and then adding additional hypertension therapies when the prior line of therapy proves unsuccessful. Unfortunately, this approach of layering blood pressure drug therapies has many potential long- and short-term consequences in the form of increased side-effect profile, additional costs to the patient, increased healthcare service utilization, and reduced quality-of-life^21,22.

Like many diseases, research indicates a heritable component to the development of hypertension estimated at ∼50%, with data suggesting treatment for hypertension may be heritable as well^19,23–26. While genetics has been shown to improve responsiveness to antihypertensive monotherapy, few studies have explored the impact of genotype on responsiveness to therapy employing multiple genes and drug classes concurrently^19,27. Much of this genetics work focused initially on genome-wide association studies (GWAS) and was followed later by studies of response rates to independent drug classes, typically in isolation^27–31. This proves problematic, as recent meta-analyses have identified ∼50 loci associated with hypertension, with each individual locus accounting for a small fraction (∼ 2%) of heritability³². While GWAS have historically been valuable in clinical research, few variants identified as being associated with hypertension, or a response to pharmacotherapy, have been validated to demonstrate a meaningful functional response in follow-up prospective trials^24,27. However, the exploration into gene–gene interactions of known functional variants selected with candidate-gene studies may explain more variance than a single locus alone³³. Current enthusiasm for the field of pharmacogenetics remains high, but few commercial pharmacogenetic tests have completed research studies to provide evidence of effectiveness, and even fewer have provided economic analyses on how their panels can reduce healthcare costs, when compared to the standard of care.

We have developed a multi-gene panel that identifies functional genotypes within the heart, vasculature, and kidney that have previously demonstrated pharmacogenetic differences in target therapy. DNA is collected using buccal swabs. From the buccal swab, 14 alleles in 11 genes are assessed: two SNPs in ADRB1 (rs1801252 and rs1801253), two SNPS in ADRB2 (rs1042713 and rs1042714), SCNN1A (rs2228576), alpha-adducin (ADD1, rs4961), SLC12A3 (rs1529927), two in WNK1 (rs1159744 and rs2107614), angiotensin-converting enzyme (ACE, rs1799752), angiotensin (AGT, rs699), angiotensin receptor (AGTR1, rs5186), cytochrome P450 2D6 (CYP2D6*4, rs3892097), and renin (REN, rs12750834). We have demonstrated that the use of this panel to guide therapy is associated with improved BP medication success in hypertension patients³⁴. In a Phase-I retrospective analysis we demonstrated that the multi-gene panel showed improvements in both changes in blood pressure (from the time of diagnosis until the time of office blood pressure measurement in the study) and control rates (using both 140/90 mmHg and 120/80 mmHg to determine “control”). In this study, using both survey data and chart review, we found that patients with a functional genotype within our multi-gene panel had better control rates (<140/90 mmHg) and a greater drop in blood pressure when compared to patients with functional genotypes who are not on the target therapy. The level of blood pressure reduction (SBP = 9 mmHg; DBP = 6.4 mmHG) has been shown to be associated with a 20–40% decrease in the risk of cardiovascular incidents in patients with uncomplicated hypertension and a 50–60% decrease in risk of cardiovascular incidents in patients with other co-morbidities^35,36.

The ineffectiveness of the current standard of care implies that implementing a multi-gene panel that takes into consideration common and functional genotypes of the organ systems important in mechanistic hypertension (heart, vasculature, and kidneys) could have significant economic benefits by decreasing costs of evaluation and management, medication usage, and adverse event costs incurred by payers. We report here on a simulation analysis to estimate the economic benefit of using a multi-gene panel to guide clinical decision-making about antihypertensive therapy. This simulation used data from a 100-individual trial comparing the standard of care vs genetically-guided antihypertensive treatment to determine the net savings that could be achieved from using a multi-gene panel. The analysis was conducted from the payer perspective, over a 3-year time horizon, for an insured panel of 10 million hypertension patients.

Methods

Economic analysis assumptions

To inform the simulation, the following assumptions regarding patient numbers in the US were made: 77,900,000 patients have hypertension; 82.7% of these patients are aware of their hypertension, having been diagnosed as such; 77.3% of these patients are treated for their hypertension, with 47.2% of these having their hypertension under control; and 5.4% of aware patients go untreated³⁷. As shown in Figure 1, of the patients aware of their hypertension and receiving the standard of care, 60% are under control and 40% are not and are effectively hypertensive³⁷. Further, previous data suggests the use of a multi-gene panel to guide hypertension therapy would improve the percentage of patients being treated and being under control to 85% (Table 1)^34,38 because of (1) choosing the correct medication first, (2) decreasing the total number of medications prescribed, and (3) telling a patient their drug regimen is based on their personal genetic make-up³⁹.

Figure 1. Distribution of treatment groups, interventions, and outcomes. Populations are represented as indicated from meta-analyses and retrospective clincal data. Interventions and risk were informed from these same data.

Table 1. Hypertension population.

Number and percentage of hypertension patients
Number of patients with hypertension	77,900,000^37 82.7% 5.4%^a 77.3%^37 47%^37
Patients aware of hypertension
Patients aware of hypertension but not treated
Patients with hypertension and being treated
Total percentage of hypertension patients under control
	Standard of care	Multi-gene panel
Care classification
Treated/uncontrolled hypertension patients	40%^a	15%^b
Treated/controlled hypertension patients	60%^37	85%^b

^aPer available data.

^bEstimate.

The following assumptions regarding costs associated with hypertension were made. Patients make 55 million annual visits for treatment of hypertension, resulting in $46 billion annual direct costs^10,40. Adding $47.5 billion in indirect costs (loss of productivity due to presenteeism, work absence, and short-term disability) yields total annual hypertension costs of $93.5 billion; allowing a calculation of $590.50 per patient per year^10,40. Medication costs were based on four 3-month generic prescription refills per year for each drug class at $16 each for treated patients⁴⁰. The cost per clinic visit was assumed to be $143⁴⁰. Previous research suggests an average of five visits to achieve BP control with standard of care⁴¹, which we assumed would decrease to 2.5 visits if a multi-gene panel to guide hypertension therapy was implemented. Per expert opinion, treated patients were assumed to be on an average of two drug classes in standard of care practices, which would be decreased to an average of 1.5 drug classes with the use of a multi-gene panel. The cost of a multi-gene panel test was set at $249 (Table 2).

Table 2. Annual costs associated with hypertension.

Annual estimates
Cost associated with hypertension  Cost associated with visits to treat hypertension	$46 billion^10^,^40 $55 million^10^,^40 $590.50^a $93.5 billion^10^,^40
Cost per patient
Direct and indirect costs
	Standard of care	Multi-gene panel
Care classifications
Average visits to BP control	5^b	2.5^a
Average number of drug classes	2^a	1.5^a

^aPer available data above.

^bGeneticure Phase I data.

To calculate the probability of adverse events, 2-year incidence rates for men aged 30–39 (3.3%), women aged 30–39 (1.5%), men aged 70–79 (6.2%), and women aged 70–79 (8.6%) were used⁴². This allowed a weighted average 2-year incidence rate of 3.9% with a 4,833,483 assumed annual incidence and an estimated cost of $369,000 per adverse event. We assumed that the implementation of a multi-gene panel to guide hypertension therapy would result in a 20% decrease in adverse events in treated but uncontrolled patients, and a 40% decrease in treated and controlled patients (Table 3). The simulation was performed over 3 years, because this is the average time of impact to a payer-provider, and was performed using extrapolated 2-year data, because this is the most robust comprehensive data available on hypertension.

Table 3. Two-year adverse events incidence rates and reductions associated with multi-gene panel directed therapy.

Rates
Men (30–39 years)	3.3%^43
Women (30–39 years)	1.5%^43
Men (70–79 years)	6.2%^43
Women (70–79 years)	8.6%^43
Weighted average	3.9%^a
Assumed adult annual rate	4,833,483^a
Cost per event	$369,000^b
Multi-gene panel adverse event reduction
Treated/uncontrolled hypertension	20%^b
Treated/controlled hypertension	40%^b

^aPer available data.

^bEstimate.

Table 4. Simulation population.

Total Untreated patients	10,000,000 540,000
	Standard of care	Multi-gene panel
Care classification
Treated/uncontrolled patients	3,784,000	1,419,000
Treated/controlled patients	5,676,000	8,041,000

In total population: Untreated patients = 5.4% of total population; treated/uncontrolled = 40% (standard of care) and 15% (multi-gene panel); treated/controlled = 60% (standard of care) and 80% (multi-gene panel).

Economic simulation data

From these data, we ran simulations based on 10 million aware patients, using the above data to inform our classification of patients into three categories (Table 4): untreated patients (n = 540,000 for standard of care and multi-gene panel), treated and uncontrolled (n = 3,784,000 and n = 1,419,000 for standard of care and multi-gene panel, respectively), and treated and controlled (n = 5,676,000 and n = 8,041,000 for standard of care and multi-gene panel, respectively). This simulation was run utilizing data consistent with the standard of care and data consistent with the use of a multi-gene panel to guide hypertension therapy for the three categories.

Results

Untreated patients

For untreated patients (n = 540,000) at a 4% probability of adverse events, our simulation estimated 21,600 total adverse events at a cost of $369,000 per event; resulting in a total cost of $7,970,400,000 and a per patient cost of $14,760 over a 3-year period (Table 5).

Table 5. Cost of adverse events in untreated hypertension patients over a 3-year care period.

Number of untreated patients	540,000
Probability	4%
Number of events	21,600
Total cost of adverse events	$7,970,400,000
Cost per patient	$14,760

Treated and uncontrolled patients

For treated/uncontrolled patients receiving the standard of care (n = 3,784,000), on an average of two drug classes, with a 3.6% probability of adverse events, we estimated the 3-year costs for evaluation and management at $8,116,680,000, for medications at $1,453,056,000, and for adverse events at $50,266,656,000; for a total 3-year cost of $59,836,392,000 or $15,813 per patient (Table 6).

Table 6. Cost of treated/uncontrolled hypertension patients over a 3-year care period.

	Standard of care	Multi-gene panel
Simulation population	3,784,000	1,419,000
Geneticure testing^12	–	$353,331,000
Evaluation and management^12	$8,116,680,000	$3,043,755,000
Medications^12	$1,453,056,000	$408,672,000
Adverse events by care classification
Probability	3.6%	2.9%
Number of events	136,224	40,867
Total cost of adverse events	$50,266,656,000	$15,079,996,800
Total cost	$59,836,392,000	$18,885,754,800
Cost per patient	$15,813	$13,309

For treated/uncontrolled patients receiving hypertension therapy guided by a multi-gene panel (n = 1,419,000), on an average of 1.5 drug classes, with a 2.9% probability of adverse events, our simulation yielded 3-year costs for genetic testing at $353,331,000 for evaluation and management at $3,043,755,500, for medications at $408,672,000, and for adverse events at $15,079,996,800; for a total 3-year cost of $18,855,754,800 and $13,309 per patient.

Treated and controlled patients

For treated/controlled patients receiving the standard of care (n = 5,676,000); on an average of two drug classes, with a 0.7% probability of adverse events, we projected the 3-year cost for evaluation and management at $4,058,340,000, for medications at $2,179,584,000, and for adverse events at $15,205,663,440; for a total 3-year cost of $21,443,587,440 and $3,778 per patient (Table 7).

Table 7. Costs associated with treated/controlled hypertension patients over a 3-year care period.

	Standard of care	Multi-gene panel
Simulation population	5,676,000	8,041,000
Geneticure testing^12	–	$2,002,209,000
Evaluation and management^12	$4,058,340,000	$2,874,657,500
Medications^12	$2,179,584,000	$2,315,808,000
Adverse events
Probability	0.7%	0.4%
Number of events	41,208	35,027
Total cost of adverse events	$15,205,663,440	$12,924,813,924
Total cost	$21,443,587,440	$20,117,488,424
Cost per patient	$3,778	$2,502

For treated/controlled patients receiving hypertension therapy guided by a multi-gene panel (n = 8,041,000), on an average of 1.5 drug classes, with a 0.4% probability of adverse events, the simulation estimated the 3-year cost for genetic testing at $2,002,209,000, for evaluation and management at $2,874,657,500, for medications at $2,315,808,000, and for adverse events at $12,924,813,924; for a total 3-year cost of $20,117,488,424 and $2,502 per patient (Table 7).

Cost reductions and savings achieved from multi-gene panel guided antihypertensive therapy

In this simulation for a panel of 10 million covered beneficiaries, for patients receiving the standard of care for hypertension management with layering blood pressure medications, the estimated costs of evaluation and management were $12,175,020,000, of medications were $3,632,640,000, and of adverse events were $73,442,719,440; for a total 3-year cost of $89,250,379,440. This results in a 3-year total cost per patient of $8,952, and an annual cost per patient of $2,975 (Table 8).

Table 8. Cost savings achieved with multi-gene enabled hypertension management over a 3-year care period.

	Standard of care	Genetic testing	Savings (loss)
Genetic testing
Untreated patients	–	–	–
Treated/uncontrolled patients	–	$353,331,000	($353,331,000)
Treated/controlled patients	–	$2,002,209,000	($2,002,209,000)
Total		$2,355,540,000	($2,355,540,000)
Evaluation and management
Untreated patients	–	–	–
Treated/uncontrolled patients	$8,116,680,000	$3,043,755,000	$5,072,925,000
Treated/controlled patients	$4,058,340,000	$2,874,657,500	$1,183,682,500
Total	$12,175,020,000	$5,918,412,500	$6,256,607,500
Medications
Untreated patients	–	–	–
Treated/uncontrolled patients	$1,453,056,000	$408,672,000	$1,044,384,000
Treated/controlled patients	$2,179,584,000	$2,315,808,000	($136,224,000)
Total	$3,632,640,000	$2,724,480,000	$908,160,000
Adverse events
Untreated patients	$7,970,400,000	$7,970,400,000	–
Treated/uncontrolled patients	$50,266,656,000	$15,079,996,800	$35,186,659,200
Treated/controlled patients	$15,205,663,440	$12,924,813,924	$2,280,849,516
Total	$73,442,719,440	$35,975,210,724	$37,467,508,716
Aggregated
Untreated patients	$7,970,400,000	$7,970,400,000	–
Treated/uncontrolled patients	$59,836,392,000	$18,885,754,800	$40,950,637,200
Treated/controlled patients	$21,443,587,440	$20,117,488,424	$1,326,099,016
Total	$89,250,379,440	$46,973,643,224	$42,276,736,216

In contrast, for patients receiving hypertension therapy guided by multi-gene panel genetic testing, the incremental 3-year cost of genetic testing was $2,355,540,000, whereas the 3-year treatment costs were $5,918,412,500 for evaluation and management, $2,724,480,000 for medication, and $35,975,210,724 for adverse events management; for a total 3-year cost of $46,973,643,224. This corresponds to a 3-year cost per patient of $4,697, and an annual cost per patient of $1,566 (Table 8).

Reconciling these 3-year figures, managing hypertension patients with multi-gene panel guided hypertension therapy returned decreases of 51% in evaluation and management costs for savings of $6,256,607,500; of 25% in medication costs for savings $908,160,000; and of 51% in adverse event costs for savings of $37,467,508,716 over 3 years, and this after accounting for the incremental $2,355,540,000 cost of genetic testing in the multi-gene panel scenario. Aggregated across cost categories, multi-gene panel guided hypertension management generated a 47% reduction in total 3-year costs, corresponding to total net savings of $42,276,736,216 for a panel of 10 million covered patients. This equals a 3-year net saving of $4,228 per patient, or $1,409 annual net savings (Table 8).

Discussion

The principal finding of this economic simulation analysis of a precision medicine approach to optimizing antihypertensive treatment is that genetic testing with a multi-gene panel and targeting treatment based on the genetic profile thus identified reduces the total cost of hypertension management by almost 50%. Importantly, 89% of these savings are generated by averting specific adverse events and, thus, optimizing choice of therapy in function of both safety and efficacy.

Specifically, under conservative assumptions, our economic simulation for 10,000,000 covered patients demonstrated that the use of a multi-gene panel to guide hypertension therapy would result in substantial net savings of $42.3 billion (rounded) over 3 years of treatment (a common duration of covering a patient), despite the incremental cost of $2.4 billion for the genetic testing. One significant benefit of the proposed genetic testing is the one-time upfront cost as opposed to the recurring differential costs of evaluation and management, medications, and adverse events in non-tested patients. For instance, we assumed an improved time to BP control (5 vs 2.5 clinic visits per patient) would result in an estimated saving of $6.3 billion in evaluation and management costs, or a 51% reduction. We also projected that therapies guided by a multi-gene panel would be more effective, thus reducing drug layering and dosing. This reduced both adverse event rates and medication costs. Interestingly, our data revealed an increase of $136 million in medication costs for treated/controlled patients, which is attributable to improved efficacy of multi-gene enabled therapies in terms of increasing treated/controlled patients in numbers and as a proportion of the covered population. This incremental cost is small compared to both medication cost-savings and total overall cost-savings in treated/uncontrolled patients. The subsequent increase in the percentage of treated/controlled patients taking fewer drug classes was reflected in a greatly reduced adverse event rate, and, therefore, the costs of managing these adverse events. Economically, reduced adverse event rates are the main benefit of more effective hypertension therapies, constituting $37.5 billion of the $42.3 billion in total 3-year net savings. This amounts to $4,228 3-year net savings per patient and annual net savings of $1,409 per patient.

Hypertension is ∼50% heritable (with a range of 20–65%)⁴⁴. The heritable nature of hypertension and the limited clinical effectiveness of the current standard of care suggest a genetically tailored approach to hypertension therapy may be indicated for both clinical and safety reasons, and, therefore, be cost-effective over the standard of care. A great deal of the research on the genetics of hypertension has focused on genome-wide association studies that have demonstrated that genes in or within an area of proteins, enzymes, and receptors important to BP therapy are also important in the development of hypertension^45,46. Previous work has demonstrated that single genes can help guide hypertensive therapy^44,47, and that multi-gene scoring can improve the response to common BP medications²⁷.

Current research examining genetic determinants to the response to hypertension therapy primarily focuses on genetic variations of thiazide and thiazide-like diuretic response. This includes lysine deficient protein kinase 1 (WNK1), alpha adducin (ADD1), sodium-chloride symporter (SLC12A3), and alpha subunit of the epithelial sodium channel (SCNN1A) variants^24,28,29. These studies suggest genetic variations of WNK1 result in an ∼6 mmHg difference in BP response to hydrochlorothiazide treatment²⁹. Additionally, genetic variations of ADD1 and SLC12A3 have been shown to affect patient responsiveness to a diuretic⁴⁸. Similarly, genetic variations in the β-adrenoceptors (both β₁ and β₂-adrenergic receptors, ADRB1 and ADRB2, respectively) have also been shown to mediate the response to β-blockade^48,49. Specifically, evidence for the benefit of a multi-gene approach lies in the study of genetic variants of ADRB1 and β-blockade. Patients who are homozygous for functional variants at positions 49 and 389 (ser49/arg389) have an average reduction in blood pressure of 15 mmHg with β-blockade, while patients heterozygous for this haplotype demonstrate almost no reduction in blood pressure with β-blockers, and some combination of homozygosity for functionality and heterozygosity lie between these two extremes in a step-wise manner. Lastly, the response to vasodilation has primarily focused on genetic variation of the angiotensin-converting enzyme (ACE)-inhibitor, angiotensin, and the angiotensin-II receptor, demonstrating genetic variation alters the response to ACE-inhibition and angiotensin receptor antagonism^50,51. Collectively, these previous findings demonstrate genetic variation plays a functional role in the variability of hypertension therapy efficacy and further supports the promise of genetically guided hypertension therapies. An interesting point of future research in multi-gene pharmacogenetics in hypertension is a focus on side-effect profiles. Most of the common hypertension therapies have well-established side-effect profiles, ranging from the development of type-II diabetes and bradycardia to development of an ACE-induced cough and angioedema. Interestingly, some of the variants that have been shown to be associated with improved response to treatment, from a blood pressure perspective, may also be those that can increase side-effect incident rates.

In this era of precision medicine, an effective multi-gene panel that includes functional variants in the three organ systems that are mechanistically important in hypertension (the heart, the vasculature, and the kidney) could guide individualized treatment decision-making considering both efficacy and adverse event profiles and medication. Therefore, contrary to the current standard of care of layering drugs and the likelihood of an worse side-effect profile, increased costs to the patient, increased healthcare service utilization, and reduced quality-of-life, with genetic testing patients can be prescribed drug classes based on their genetics, thus improving both efficacy and safety. The potential benefits of employing a multi-gene panel to guide pharmacological therapy in hypertension include: fewer clinic visits to achieve BP control; a higher percentage of treated patients with controlled BP; reduced adverse event rates; fewer drug classes prescribed per patient; and improved adherence rates through improved effectiveness, reductions in medications used, and lower adverse events. Cumulatively, this would result in lower costs associated with evaluation and management, medications, and managing adverse events, even after accounting for the incremental costs associated with genetic testing. In turn, as we demonstrated in this simulation, this translates into major reductions in the total cost incurred by payers.

Despite the short-term analysis of our study over a 3-year time horizon, an analysis with a longer time horizon is needed to estimate the extended savings that can be achieved by performing multi-gene panel genetic testing. Cost-effectiveness analyses over a lifetime horizon may support the long-term clinical and economic benefits of multi-gene panel genetic testing.

One limitation of this study is the need to use estimates for some inputs as there is limited research examining the efficacy of multi-gene panel guided therapies in hypertension. Therefore, we relied on data pertaining to gene panels and gene–gene interactions in other pathologies as well as results from a Phase I trial on the multi-gene hypertension panel. Preventively, we used conservative assumptions to minimize the risk of bias. Additionally, it is likely that the increased blood pressure reduction from genetically-guided therapy will also improve adherence (less trial-and-error), which could further augment the economic benefits of such a panel. While further studies are needed on the association of multi-gene panel guided therapies to BP medication efficacy and safety in hypertension, our data suggests the potential for large economic impacts.

Conclusions

Collectively, our payer-focused economic simulation for the US of the implementation of multi-gene panel enabled therapies for hypertension patients demonstrates cost reductions of nearly 50% over 3 years in the management of hypertension. While certainly these findings are substantive to payers, the benefits to patients are just as significant in terms of targeted treatment, reductions in adverse events, and fewer clinic visits, not to mention the corresponding improvements in quality-of-life.

Transparency

Declaration of funding

The study was supported by funds from Geneticure Inc., which has developed multi-gene panels for blood pressure prescribing using pharmacogenetics. NSA and IA provided independent economic analysis advice to Geneticure Inc. pro bono without any monetary or other benefits.

Disclosure of financial/other interests

EFK declares no conflict of interest. EMS, SCS, RS, and TPO have significant financial interests in Geneticure Inc. NSA and IA provided independent economic analysis advice to Geneticure Inc. pro bono without any monetary or other benefits. They have no other conflicts to declare. Peer reviewers on this manuscript have received an honorarium from JME for their review work, but have no other relevant financial relationships to disclose.

Acknowledgments

No assistance in the preparation of this article is to be declared. Publication of this study does not represent an endorsement of Geneticure, Inc. by this journal or any professional organization.